WO2022086784A1 - Méthodes et systèmes pour traiter des états de santé gastro-intestinaux et inflammatoires faisant appel à des thérapies numériques sur prescription en association avec d'autres thérapies - Google Patents

Méthodes et systèmes pour traiter des états de santé gastro-intestinaux et inflammatoires faisant appel à des thérapies numériques sur prescription en association avec d'autres thérapies Download PDF

Info

Publication number
WO2022086784A1
WO2022086784A1 PCT/US2021/054984 US2021054984W WO2022086784A1 WO 2022086784 A1 WO2022086784 A1 WO 2022086784A1 US 2021054984 W US2021054984 W US 2021054984W WO 2022086784 A1 WO2022086784 A1 WO 2022086784A1
Authority
WO
WIPO (PCT)
Prior art keywords
patient
data
components
therapeutic treatment
therapeutic
Prior art date
Application number
PCT/US2021/054984
Other languages
English (en)
Inventor
Robert Bradley Paull
Gaurav Kumar
Christopher Michael Browning
Megan Leigh Oser
Ann Harriet Montgomery
Jennifer Lily Shim
Simon Levy
Original Assignee
Mahana Therapeutics, Inc.
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Priority claimed from US17/499,576 external-priority patent/US20220028541A1/en
Application filed by Mahana Therapeutics, Inc. filed Critical Mahana Therapeutics, Inc.
Publication of WO2022086784A1 publication Critical patent/WO2022086784A1/fr

Links

Classifications

    • G—PHYSICS
    • G16—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
    • G16H—HEALTHCARE INFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR THE HANDLING OR PROCESSING OF MEDICAL OR HEALTHCARE DATA
    • G16H15/00—ICT specially adapted for medical reports, e.g. generation or transmission thereof
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00—Measuring for diagnostic purposes; Identification of persons
    • A61B5/0002—Remote monitoring of patients using telemetry, e.g. transmission of vital signals via a communication network
    • A61B5/0015—Remote monitoring of patients using telemetry, e.g. transmission of vital signals via a communication network characterised by features of the telemetry system
    • A61B5/0022—Monitoring a patient using a global network, e.g. telephone networks, internet
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00—Measuring for diagnostic purposes; Identification of persons
    • A61B5/16—Devices for psychotechnics; Testing reaction times ; Devices for evaluating the psychological state
    • A61B5/165—Evaluating the state of mind, e.g. depression, anxiety
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00—Measuring for diagnostic purposes; Identification of persons
    • A61B5/42—Detecting, measuring or recording for evaluating the gastrointestinal, the endocrine or the exocrine systems
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00—Measuring for diagnostic purposes; Identification of persons
    • A61B5/48—Other medical applications
    • A61B5/4806—Sleep evaluation
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00—Measuring for diagnostic purposes; Identification of persons
    • A61B5/48—Other medical applications
    • A61B5/4824—Touch or pain perception evaluation
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00—Measuring for diagnostic purposes; Identification of persons
    • A61B5/48—Other medical applications
    • A61B5/4833—Assessment of subject's compliance to treatment
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00—Measuring for diagnostic purposes; Identification of persons
    • A61B5/48—Other medical applications
    • A61B5/4836—Diagnosis combined with treatment in closed-loop systems or methods
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00—Measuring for diagnostic purposes; Identification of persons
    • A61B5/72—Signal processing specially adapted for physiological signals or for diagnostic purposes
    • A61B5/7235—Details of waveform analysis
    • A61B5/7264—Classification of physiological signals or data, e.g. using neural networks, statistical classifiers, expert systems or fuzzy systems
    • A61B5/7267—Classification of physiological signals or data, e.g. using neural networks, statistical classifiers, expert systems or fuzzy systems involving training the classification device
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00—Measuring for diagnostic purposes; Identification of persons
    • A61B5/74—Details of notification to user or communication with user or patient ; user input means
    • A61B5/742—Details of notification to user or communication with user or patient ; user input means using visual displays
    • A61B5/7435—Displaying user selection data, e.g. icons in a graphical user interface
    • G—PHYSICS
    • G16—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
    • G16H—HEALTHCARE INFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR THE HANDLING OR PROCESSING OF MEDICAL OR HEALTHCARE DATA
    • G16H10/00—ICT specially adapted for the handling or processing of patient-related medical or healthcare data
    • G16H10/20—ICT specially adapted for the handling or processing of patient-related medical or healthcare data for electronic clinical trials or questionnaires
    • G—PHYSICS
    • G16—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
    • G16H—HEALTHCARE INFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR THE HANDLING OR PROCESSING OF MEDICAL OR HEALTHCARE DATA
    • G16H20/00—ICT specially adapted for therapies or health-improving plans, e.g. for handling prescriptions, for steering therapy or for monitoring patient compliance
    • G16H20/10—ICT specially adapted for therapies or health-improving plans, e.g. for handling prescriptions, for steering therapy or for monitoring patient compliance relating to drugs or medications, e.g. for ensuring correct administration to patients
    • G—PHYSICS
    • G16—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
    • G16H—HEALTHCARE INFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR THE HANDLING OR PROCESSING OF MEDICAL OR HEALTHCARE DATA
    • G16H50/00—ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics
    • G16H50/20—ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for computer-aided diagnosis, e.g. based on medical expert systems
    • G—PHYSICS
    • G16—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
    • G16H—HEALTHCARE INFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR THE HANDLING OR PROCESSING OF MEDICAL OR HEALTHCARE DATA
    • G16H50/00—ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics
    • G16H50/30—ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for calculating health indices; for individual health risk assessment
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00—Measuring for diagnostic purposes; Identification of persons
    • A61B5/48—Other medical applications
    • A61B5/4836—Diagnosis combined with treatment in closed-loop systems or methods
    • A61B5/4839—Diagnosis combined with treatment in closed-loop systems or methods combined with drug delivery
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00—Measuring for diagnostic purposes; Identification of persons
    • A61B5/74—Details of notification to user or communication with user or patient ; user input means
    • A61B5/742—Details of notification to user or communication with user or patient ; user input means using visual displays
    • A61B5/744—Displaying an avatar, e.g. an animated cartoon character
    • G—PHYSICS
    • G16—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
    • G16H—HEALTHCARE INFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR THE HANDLING OR PROCESSING OF MEDICAL OR HEALTHCARE DATA
    • G16H20/00—ICT specially adapted for therapies or health-improving plans, e.g. for handling prescriptions, for steering therapy or for monitoring patient compliance
    • G16H20/60—ICT specially adapted for therapies or health-improving plans, e.g. for handling prescriptions, for steering therapy or for monitoring patient compliance relating to nutrition control, e.g. diets
    • G—PHYSICS
    • G16—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
    • G16H—HEALTHCARE INFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR THE HANDLING OR PROCESSING OF MEDICAL OR HEALTHCARE DATA
    • G16H20/00—ICT specially adapted for therapies or health-improving plans, e.g. for handling prescriptions, for steering therapy or for monitoring patient compliance
    • G16H20/70—ICT specially adapted for therapies or health-improving plans, e.g. for handling prescriptions, for steering therapy or for monitoring patient compliance relating to mental therapies, e.g. psychological therapy or autogenous training

Definitions

  • a patient when a patient is diagnosed with one or more medical conditions, the patient may be referred to additional health professionals for further care and treatment.
  • a patient may be referred to a psychologist, psychiatrist, counselor, or other mental health professional.
  • a patient may also be directed to one or more support groups to assist with any psychological distress that the patient may be experiencing. While these traditional face-to- face options may be greatly beneficial to a patient, often times they do not provide enough psychological support.
  • a patient when a patient is alone, at home, or not otherwise engaged directly with their mental health professional or support group, they may experience a significant degree of one or more negative emotional states, such as fear, anxiety, panic, and depression. Additionally, left unidentified and untreated, these negative emotional states often exacerbate the physical symptoms associated with a patient’s diagnosis, which in turn can lead to greater psychological distress.
  • GI health conditions and inflammatory health conditions have significant impact on the quality of life of patients worldwide.
  • current approaches typically focus on reducing or eliminating physiological symptoms, by implementation of medication regimens, supplement regimens, diet changes, and/or lifestyle changes.
  • GI and/or inflammatory health conditions have other adverse effects on lives of patients due to the nature of symptoms, and current approaches to treatment fail to address such adverse effects.
  • current methods of improving patient states associated with GI and/or inflammatory health conditions are limited in relation to: educating patients regarding standard and non-standard treatment options; detecting, in real or near-real time, states of symptom severity in non-invasive manners; and delivering therapy in a customized and adaptive manner.
  • behavioral therapy is also a valuable tool for addressing a variety of mental health issues, including anxiety and depression, and improving an individual’s ability to manage and respond effectively to external stimuli, such as stress.
  • behavioral therapy is administered via a mental health professional, such as a therapist, for example through regular sessions between an individual and their therapist.
  • a mental health professional such as a therapist
  • Such interactions can be time consuming, inconvenient, and costly, thereby limiting accessibility of behavioral therapy treatment.
  • Embodiments of the present disclosure provide a technical solution to the technical problem of effectively, efficiently, and remotely treating gastrointestinal and inflammatory health conditions using prescription digital therapeutics in combination with other therapies, in order to ensure that patients receive adequate care, support, and treatment.
  • the inventions covered by the system and method disclosed herein can confer several benefits over conventional systems and methods, and such inventions are further implemented into many practical applications related to improvement of technologies utilized for patient healthcare.
  • the systems and methods disclosed herein allow behavioral therapy to be remotely administered to patients suffering from gastrointestinal (GI) and/or inflammatory health conditions in a convenient and flexible, yet structured fashion, via a prescription digital therapeutics (PDT) system in combination with one or more non-behavioral therapies.
  • GI gastrointestinal
  • PDT prescription digital therapeutics
  • the invention(s) disclosed herein can employ non-traditional systems and methods for providing services such as interventions to patients exhibiting symptoms associated with one or more GI and/or inflammatory health conditions.
  • the invention(s) can deliver psychological-based interventions to patients, such as, but not limited to, cognitive behavioral therapy (CBT)-based interventions, as well as other types of interventions, which are described in more detail below, by way of a platform having components implemented in a mobile device environment and/or other computer or internet-based architecture.
  • CBT cognitive behavioral therapy
  • the invention(s) use components of the platform to process large amounts of user data, remotely deliver personalized interventions, and remotely monitor user interactions with such interventions in near real-time in a manner that cannot be practically implemented by the human mind.
  • prescription digital therapeutics (PDT) technologies may be used to administer behavioral therapy treatments in combination with a variety of non-behavioral therapy treatments in a controlled fashion, as treatment for one or more conditions described herein.
  • provided technologies address physiological conditions (e.g., conditions with one or more physical symptoms, features, or manifestations) that may be affected by a subject’s mental health state, for example, presence of a mental health condition such as, but not limited to anxiety, depression, and/or stress.
  • the PDT technologies disclosed herein can be used to administer guided behavioral therapies in combination with a variety of non- behavioral therapies to treat individuals suffering from certain particular physiological conditions.
  • guided behavioral therapy approaches disclosed herein may be administered, in combination with non-behavioral therapies, to individuals suffering from one or more GI and/or inflammatory health conditions. In this manner, approaches described herein may be used to ameliorate symptoms associated with a variety of GI and/or inflammatory health conditions.
  • the PDT system disclosed herein may be used to improve efficacy of other types of therapies and/or ameliorate side effects of other types of therapies.
  • guided behavioral therapy tools provided by the PDT system disclosed herein may facilitate adherence to various treatment regimens (e.g., of pharmaceutical compositions), and/or management of dosing (e.g., providing insight and/or guidance relevant to dosage adjustments).
  • a patient is provided with a user interface to a prescription digital therapeutics (PDT) system wherein the PDT system remotely administers guided behavioral therapy to the patient.
  • PDT prescription digital therapeutics
  • a pre-assessment of a patient exhibiting one or more GI and/or inflammatory health condition symptoms is performed by the PDT system to generate patient profile and pre-assessment data.
  • the patient profile and pre-assessment data is processed by the PDT system to generate patient condition data, wherein the patient condition data includes an identification of the patient’s condition, condition sub-type, and/or condition severity.
  • the patient profile and pre-assessment data and the patient condition data are processed by the PDT system to identify one or more complementary non- behavioral therapy components to be administered to the patient in combination with behavioral therapy components.
  • the patient profile and pre-assessment data and the patient condition data are processed by the PDT system to generate a personalized intervention regimen for the patient, wherein the personalized intervention regimen defines both behavioral therapy components and non-behavioral therapy components to be administered to the patient.
  • the one or more behavioral therapy components are administered, through the user interface of the PDT system, to the patient according to the personalized intervention regimen generated for the patient.
  • the one or more non-behavioral therapy components are administered to the patient in combination with the one or more behavioral therapy components according to the personalized intervention regimen generated for the patient.
  • the patient’s interactions with the one or more behavioral therapy components and the one or more non-behavioral therapy components are monitored remotely in near real-time to generate patient interaction data.
  • the patient interaction data is processed by the PDT system to generate intervention modification data representing recommended modifications to the patient’s personalized intervention regimen.
  • aspects of the behavioral therapy and/or the non-behavioral therapy components defined by the patient’s personalized intervention regimen are dynamically modified.
  • the invention(s) can also provide interventions that are tailored to individual users/patients suffering from a variety of symptoms, such as, but not limited to, symptoms associated with digestion, defecation, various stooling symptoms, pain, social/interpersonal effects, emotional effects, cognitive effects, and behavioral effects, in a customized manner, with implementation of real-time or near real-time assessments of data from multiple sources, including, but not limited to, electronic health record sources, self-report sources, and sensor sources.
  • symptoms such as, but not limited to, symptoms associated with digestion, defecation, various stooling symptoms, pain, social/interpersonal effects, emotional effects, cognitive effects, and behavioral effects, in a customized manner, with implementation of real-time or near real-time assessments of data from multiple sources, including, but not limited to, electronic health record sources, self-report sources, and sensor sources.
  • the invention(s) can also be used for acquisition of user/patient data from multiple data sources, including, but not limited to, health data, biometric data, user demographic data, and user behavior data.
  • the invention(s) can also be used for generation of training datasets, whereby the training datasets can be used for training machine learning models (e.g., neural networks, etc.) that take input data pertaining to users/patients and produce outputs that can be used to guide customization of interventions.
  • machine learning models e.g., neural networks, etc.
  • the invention(s) can also be used to provide automated delivery of health-promoting or improving interventions, automated tracking/monitoring of user interactions with such interventions, automated communications with users (e.g., through transmission of notifications), and/or automated delivery of modified interventions to users, through a mobile device application platform and/or other platform (e.g., web platform).
  • such interventions can also be delivered as digital therapeutics, alone as a monotherapy or in combination with other therapeutics, such as medications and/or medical devices, through technical systems intended to diagnose and/or treat and/or improve symptoms or health-related quality of life, in collaboration with healthcare providers, health insurers, and/or other entities in the healthcare system.
  • the invention(s) can also employ non-traditional systems and methods for delivering prescription digital therapeutics (PDT) for improving patient health (e.g., in relation to disease management), whereby digital therapeutics are prescribed through healthcare providers (e.g., with associated billing codes).
  • PDT prescription digital therapeutics
  • the invention(s) can include systems and methods for improving patient states (e.g., in the context of health, symptoms, disease progression, quality of life, and other contexts).
  • the system and/or method can confer any other suitable benefit.
  • the present disclosure provides methods for remotely administering behavioral therapy to a user/patient via a controlled progression of interactive therapy modules, through a graphical user interface (GUI) of a prescription digital therapeutics (PDT) system.
  • GUI graphical user interface
  • technologies described herein allow an individual user/patient to access and take part in a series of guided lessons that provide training in various behavioral skills.
  • these guided lessons may be presented as a sequence of interactive lesson modules that provide training and practice via a graphical user interface (GUI) of a PDT system.
  • GUI graphical user interface
  • approaches described herein provide structured behavioral therapy that is targeted at managing triggers and/or symptoms associated with specific physical conditions. Accordingly, in some embodiments, a behavioral therapy toolkit as provided by the systems and methods described herein can be tailored for a particular physical condition.
  • the present disclosure provides methods for providing for interactive creation of a user personal model via a graphical user interface (GUI) of a PDT system, allowing a user to identify cycles of behaviors, thoughts, emotions, and stressors that influence the frequency and/or severity of symptoms associated with a particular physical condition from which the user is suffering,
  • GUI graphical user interface
  • technologies described herein can increase access to and/or facilitate effective administration of behavioral therapy, and moreover can achieve effective impact on physiological conditions through guided behavioral therapy in combination with other types of therapies.
  • the present disclosure provides improvements to technologies and methods for administering cognitive behavioral therapy (CBT).
  • CBT cognitive behavioral therapy
  • the present disclosure provides improvements to technologies for administering a wide variety of therapy modalities, individually, or in combination with other modalities.
  • embodiments of the present disclosure provide a technical solution to the technical problem of effectively, efficiently, and remotely treating gastrointestinal and inflammatory health conditions using prescription digital therapeutics in combination with other therapies, in order to ensure that patients receive adequate care, support, and treatment.
  • FIG. 1 A depicts a schematic of a system for treating gastrointestinal and inflammatory health conditions using prescription digital therapeutics in combination with other therapies, according to one or more embodiments.
  • FIG. IB depicts a block diagram of a production environment for treating gastrointestinal and inflammatory health conditions using prescription digital therapeutics in combination with other therapies, according to one or more embodiments.
  • FIG. 2 A depicts a flowchart of a method for treating gastrointestinal and inflammatory health conditions using prescription digital therapeutics in combination with other therapies, according to one or more embodiments.
  • FIG. 2B depicts a flowchart of a method for providing adaptive interventions for gastrointestinal and inflammatory health conditions, according to one or more embodiments.
  • FIG. 2C depicts a flowchart of a method for providing adaptive interventions for gastrointestinal and inflammatory health conditions, according to one or more embodiments.
  • FIG. 3 A depicts a schematic of architecture implemented for delivery of intervention regimen components and/or modules, according to one or more embodiments.
  • FIG. 3B depicts examples of individual sections that may make up an introduction and education module of an intervention regimen, according to one or more embodiments.
  • FIG. 3C depicts examples of individual sections that may make up a pain management module of an intervention regimen, according to one or more embodiments.
  • FIG. 4 depicts an example of formation of a personal disease model, according to one or more embodiments.
  • FIG. 5 A depicts a flowchart of a process for determining severity of a gastrointestinal and/or inflammatory health condition, according to one or more embodiments.
  • FIG. 5B depicts examples of a process for determining severity of a gastrointestinal and/or inflammatory health condition, according to one or more embodiments.
  • FIG. 6 depicts a flowchart of a pre-assessment and onboarding process of a method for providing adaptive interventions, according to one or more embodiments.
  • FIG. 7 depicts examples of system aspects of a program for personalized health condition monitoring and improvement, according to one or more embodiments.
  • FIG. 8A, FIG. 8B, FIG. 8C, FIG. 8D, and FIG. 8E depict example schematics of conditional branching architecture implemented for delivery of intervention regimen components, according to one or more embodiments.
  • FIG. 9A, FIG. 9B, FIG. 9C, and FIG. 9D are screenshots of several portions of an exemplary GUI for a system for treating gastrointestinal and/or inflammatory health conditions using digital therapeutics, according to one or more embodiments..
  • FIG. 10A, FIG. 10B, FIG. 10C, and FIG. 10D are screenshots of example user interactions with an initial lesson module for content tailored for a patient with IBS, according to one or more embodiments.
  • FIG. 11 A and FIG. 1 IB are screenshots showing gate features of an exemplary GUI for a system for treating gastrointestinal and/or inflammatory health conditions using digital therapeutics, in accordance with one or more embodiments.
  • FIG. 12A, FIG. 12B, FIG. 12C, and FIG. 12D are screenshots of an exemplary GUI for a symptom diary lesson module, according to one or more embodiments.
  • FIG. 13 A, FIG. 13B, FIG. 13C, and FIG. 13D are screenshots of example user interactions with a symptom diary practice module, in accordance with one or more embodiments.
  • FIG. 14A, FIG. 14B, FIG. 14C, and FIG. 14D are screenshots of an exemplary GUI for introducing a personal model lesson module, in accordance with one or more embodiments.
  • FIG. 15A, FIG. 15B, FIG. 15C, and FIG. 15D are screenshots of an exemplary GUI for a personal model lesson module, according to one or more embodiments.
  • FIG. 16A, FIG. 16B, and FIG. 16C are screenshots of an exemplary personal model graphical representation, according to one or more embodiments.
  • FIG. 17A, FIG. 17B, FIG. 17C, and FIG. 17D are screenshots of an exemplary GUI for a reflections section of a personal model lesson module, according to one or more embodiments.
  • FIG. 18A, FIG. 18B, FIG. 18C, and FIG. 18D are screenshots of an exemplary GUI for a symptom management lesson module, according to one or more embodiments.
  • FIG. 19 A, FIG. 19B, FIG. 19C, and FIG. 19D are screenshots of an exemplary GUI for an unhelpful thought pattern lesson module, according to one or more embodiments.
  • the systems and methods disclosed herein allow behavioral therapy to be administered to patients suffering from gastrointestinal (GI) and/or inflammatory health conditions in a convenient and flexible, yet structured fashion, via a prescription digital therapeutics (PDT) system in combination with one or more non-behavioral therapies.
  • GI gastrointestinal
  • PDT digital therapeutics
  • behavioral therapy may include therapies such as, but not limited to, psychotherapy, cognitive behavioral therapy (CBT), acceptance commitment therapy (ACT), dialectical behavioral therapy (DBT), exposure therapy, mindfulness-based cognitive therapy (MCBT), hypnotherapy, experiential therapy, and psychodynamic therapy.
  • CBT cognitive behavioral therapy
  • ACT acceptance commitment therapy
  • DBT dialectical behavioral therapy
  • MCBT mindfulness-based cognitive therapy
  • hypnotherapy experiential therapy
  • psychodynamic therapy may include therapies such as, but not limited to, psychotherapy, cognitive behavioral therapy (CBT), acceptance commitment therapy (ACT), dialectical behavioral therapy (DBT), exposure therapy, mindfulness-based cognitive therapy (MCBT), hypnotherapy, experiential therapy, and psychodynamic therapy.
  • CBT cognitive behavioral therapy
  • ACT acceptance commitment therapy
  • DBT dialectical behavioral therapy
  • MCBT mindfulness-based cognitive therapy
  • such guided behavioral therapy technologies are based at least in part on cognitive behavioral therapy (CBT), and provide structured modules and/or lessons via a graphical user interface (GUI) of a prescription digital therapeutics (PDT) system, for example to allow patients to develop a skillset for treating a physiological disease, disorder and/or condition, and for managing stress and/or other psychological symptoms associated with such disease, disorder and/or condition.
  • GUI graphical user interface
  • a relevant disease, disorder or condition may be or comprise an inflammatory health condition and/or a GI health condition.
  • approaches described herein provide patients with structured behavioral therapy that is targeted at managing triggers and/or symptoms associated with specific physical and/or physiological conditions.
  • physiological conditions such as GI and/or inflammatory health conditions
  • symptoms and effects of these physiological conditions may trigger and/or worsen related mental health conditions and can be a source of significant stress for many patients.
  • This feedback loop can create a vicious cycle, in which symptoms of a particular physiological condition trigger and/or worsen mental health states, causing issues such as anxiety and/or depression, which, in turn, trigger and/or worsen physical/physiological symptoms.
  • Feedback loops of this kind are particularly relevant to GI and inflammatory health conditions.
  • IBS irritable bowel syndrome
  • a behavioral therapy toolkit as provided by technologies (e.g., systems and methods) disclosed herein can be tailored for a particular physical/physiological condition.
  • particular behavioral therapy lesson modules can be designed to facilitate tracking of specific symptoms, tracking and elucidating specific stressors, and/or providing targeted exercises (e.g., breathing, progressive relaxation, etc.), which are well suited for managing specific triggers and symptoms of the particular physiological condition.
  • behavioral therapy lesson modules targeted at a GI health condition may include specially designed symptom diaries, meal trackers, personal model interfaces and/or other types of therapy modules, which allow a user to discover and reflect upon combinations of stressors, triggers, thoughts, and symptoms that contribute to their own, personal, vicious cycle.
  • the technologies, methods, and systems disclosed herein provide a valuable complement to physician visits and recommendations (e.g., with regard to lifestyle changes) and standard of care therapies (e.g., administration of medication(s)). Furthermore, technologies disclosed herein can increase access to and/or facilitate effective administration of behavioral therapy to achieve effective impact on physiological conditions such as, but not limited to, GI and/or inflammatory health conditions, through guided behavioral therapy.
  • the term “patient,” and/or “subject,” may include an individual who is suffering from a relevant disease, disorder or condition.
  • a patient/ subject is an individual who is susceptible to a disease, disorder, or condition.
  • a patient/ subject displays one or more symptoms or characteristics of a disease, disorder or condition.
  • a patient/ subject does not display any symptom or characteristic of a disease, disorder, or condition.
  • a patient/ subject is someone with one or more features characteristic of susceptibility to or risk of a disease, disorder, or condition.
  • a patient/ subject is an individual to whom diagnosis and/or therapy is and/or has been administered.
  • a patient/ subject is an individual who has been diagnosed with one or more diseases, disorders, and/or conditions and is the recipient of one or more therapies in a clinical or non-clinical setting. In some embodiments, a patient/ subject is an individual who has not been diagnosed with a health condition, but is a recipient of one or more therapies in a clinical or non-clinical setting.
  • the term “therapeutics system,” “prescription digital therapeutics (PDT)” and/or “prescription digital therapeutics (PDT) system,” may include a system utilized for remotely administering a therapy to a patient, wherein the PDT system is required to be approved by a government agency before it can be marketed for administration to humans.
  • a PDT system requires FDA approval and rigorous clinical evidence to substantiate intended use and impact on disease state.
  • a PDT system is typically a system for which a medical prescription is required for administration to patients.
  • the term “user” may include a patient/ subject who utilizes a therapeutics system or a prescription digital therapeutics (PDT) system.
  • a therapeutics system or a prescription digital therapeutics (PDT) system.
  • PDT prescription digital therapeutics
  • an individual who is “suffering from” a disease, disorder, and/or condition displays one or more symptoms of a disease, disorder, and/or condition and/or has been diagnosed with the disease, disorder, or condition.
  • the term “therapy,” “behavioral therapy,” and/or “guided behavioral therapy” may include psychological techniques, methodologies, and/or modalities intended or demonstrated to achieve impact on and/or alteration of one or more behaviors of a patient/subject.
  • therapies may include, but are not limited to, psychotherapy, cognitive behavioral therapy (CBT), acceptance commitment therapy (ACT), dialectical behavioral therapy (DBT), exposure therapy, mindfulness-based cognitive therapy (MCBT), hypnotherapy, experiential therapy, and psychodynamic therapy.
  • the term “mind-body intervention,” may include one or more therapeutic practices that employ a variety of techniques designed to facilitate the mind’s capacity to affect bodily function and systems.
  • Examples of mind-body interventions may include, but are not limited to, relaxation, imagery, biofeedback, meditation, hypnosis, tai, chi, and yoga.
  • the phrase “administration” may include providing, delivering, and/or applying a therapy to a patient.
  • a therapy may be administered to a patient directly by a health practitioner.
  • a therapy may be administered to a patient remotely, for example, over the internet or through a computer system, without the direct involvement of a health practitioner.
  • the therapy may be self-administered by the patient.
  • a therapy may also be administered to a patient remotely with partial involvement of a health practitioner.
  • the therapy to be administered may be selected by a health practitioner, but the therapy may then be self-administered by the patient, utilizing a computer system, or the therapy may be administered to the patient by a computer system, but a health practitioner may monitor the patient’s response data.
  • a variety of routes are available for administration of compositions; for example, some compositions may be administered by one or more routes such as ocular, oral, parenteral, topical, etc.
  • the present disclosure in some embodiments, describes administration of behavioral therapy, for example via interaction with a counselor (e.g., a therapist) and/or with a device or computing system as described herein.
  • administration may involve dosing, application, or interaction that is intermittent (e.g., a plurality of doses separated in time) and/or periodic (e.g., individual doses separated by a common period of time) dosing.
  • administration may involve continuous dosing (e.g., perfusion), application or interaction for at least a selected period of time.
  • the term “treat,” “treatment,” or “treating” may include administration of therapy that has been established to partially or completely alleviate, ameliorate, relieve, inhibit, prevent, delay onset of, reduce severity of, and/or reduce incidence of one or more symptoms or features of a disease, disorder, and/or condition (e.g., when administered to a relevant population).
  • treatment may be administered to a patient who is not exhibiting (and/or has not exhibited) one or more signs of a relevant disease, disorder, and/or condition.
  • treatment may be administered to a patient who exhibits only early signs of the disease, disorder, and/or condition, for example for the purpose of decreasing risk of developing one or more features of pathology associated with the disease, disorder, and/or condition.
  • a treatment is termed “therapeutic” when administered to a patient who is displaying or has displayed one or more features, symptoms, or other characteristics of a relevant disease, disorder and/or condition.
  • a treatment is termed “prophylactic” when administered to a patient who has not displayed features, symptoms, or other characteristics of a relevant disease, disorder and/or condition.
  • the term “protocol” or “therapeutic protocol” may include procedures and/or systems of rules for administration of a therapy.
  • a therapeutic protocol defines the rules, syntax, semantics, and synchronization of communications with a patient.
  • a therapy may include a series of modules, lessons, questionnaires, and exercises, and a related protocol may dictate the order, speed, and/or frequency in which various modules, lessons, exercises and questionnaires are presented to a patient.
  • a protocol may also dictate the specific layout, content and general presentation of the various lessons, exercises and questionnaires.
  • a protocol can be as specific as to dictate each word or sequence of words selected for use in the therapy.
  • a therapy may be administered to a patient according to any number of protocols or any number of combinations of protocols.
  • the term “therapeutic regimen” or “intervention regimen” may include a therapy for administration to a patient as part of a therapeutic treatment, wherein the therapy is administered to the patient according to a specific set of therapeutic protocols.
  • a therapeutic/intervention regimen for a behavioral therapy may include a specific set of modules, lessons, questionnaires, exercises, and other content, which may be administered to a patient in a particular order, at a particular frequency, utilizing a particular layout, etc.
  • a therapeutic/intervention regimen for a non-behavioral therapy may include administration of a non-behavioral therapy, such as a pharmaceutical or nutraceutical composition, in a particular amount, according to a particular dosing schedule.
  • a therapeutic/intervention regimen may be correlated with a desired or beneficial therapeutic outcome.
  • a therapeutic/intervention regimen may be personalized or tailored to meet the needs of a specific patient.
  • the term “combination therapy” may include situations in which a subject is simultaneously exposed to two or more therapeutic regimens (e.g., two or more therapeutic modalities and/or agents).
  • the two or more regimens may be administered simultaneously; in some embodiments, such regimens may be administered sequentially (e.g., all “doses” of a first regimen are administered prior to administration of any doses of a second regimen); in some embodiments, such modalities and/or agents are administered in overlapping dosing regimens.
  • “administration” of combination therapy may involve administration of one or more agent(s) or modality(ies) to a subject receiving the other agent(s) or modality(ies) in the combination.
  • combination therapy does not require that individual agents be administered together in a single composition (or even necessarily at the same time), although in some embodiments, two or more agents, or active moieties thereof, may be administered together in a combination composition, or even in a combination compound (e.g., as part of a single chemical complex or covalent entity).
  • the term “therapeutic agent” may include any agent that elicits a desired effect when administered to an organism, e.g., in a pharmaceutical composition, via a prescription digital therapeutics (PDT) system, and/or according to a therapeutic regimen as described herein.
  • an agent is considered to be a therapeutic agent if it demonstrates a statistically significant effect across an appropriate population.
  • the appropriate population may be a population of model organisms.
  • an appropriate population may be defined by various criteria, such as a certain age group, gender, genetic background, preexisting conditions, etc.
  • a therapeutic agent can be used to alleviate, ameliorate, relieve, inhibit, prevent, delay onset of, reduce severity of, and/or reduce incidence of one or more symptoms or features of a disease, disorder, and/or condition.
  • the term “dosing regimen” and/or “dosing schedule” may include a set of unit doses (typically more than one) that are administered individually to a subject, typically separated by periods of time.
  • a given therapeutic agent or modality has a recommended dosing regimen, which may involve one or more doses.
  • a dosing regimen comprises a plurality of doses each of which is separated in time from other doses.
  • individual doses are separated from one another by a time period of the same length; in some embodiments, a dosing regimen comprises a plurality of doses and at least two different time periods separating individual doses.
  • all doses within a dosing regimen are of the same unit dose amount. In some embodiments, different doses within a dosing regimen are of different amounts. In some embodiments, a dosing regimen comprises a first dose in a first dose amount, followed by one or more additional doses in a second dose amount different from the first dose amount. In some embodiments, a dosing regimen comprises a first dose in a first dose amount, followed by one or more additional doses in a second dose amount same as the first dose amount In some embodiments, a dosing regimen is correlated with a desired or beneficial outcome when administered across a relevant population (i.e., is a therapeutic dosing regimen).
  • the term “pharmaceutical composition” may include a composition in which an active agent is formulated together with one or more pharmaceutically acceptable carriers.
  • the active agent is present in unit dose amount appropriate for administration in a therapeutic regimen that has been established a statistically significant probability of achieving a predetermined therapeutic effect when administered to a relevant population.
  • a pharmaceutical composition may be specially formulated for administration in a particular form (e.g., in a solid form or a liquid form), and/or may be specifically adapted for, for example: oral administration (for example, as a drenche [aqueous or non-aqueous solutions or suspensions], tablet, capsule, bolus, powder, granule, paste, etc., which may be formulated specifically for example for buccal, sublingual, or systemic absorption); parenteral administration (for example, by subcutaneous, intramuscular, intravenous or epidural injection as, for example, a sterile solution or suspension, or sustained-release formulation, etc.); topical application (for example, as a cream, ointment, patch or spray applied for example to skin, lungs, or oral cavity); intravaginal or intrarectal administration (for example, as a pessary, suppository, cream, or foam); ocular administration; nasal or pulmonary administration, etc.
  • oral administration for example, as a drenche
  • the term “nutraceutical composition” may include a composition comprising one or more food(s) and/or food component(s), and/or one or more microbiome components, that provide medical or health benefits.
  • a nutraceutical is or comprises a component selected from the group consisting of microorganisms, proteins, vitamins, and combinations thereof, such as bacteria.
  • nutraceutical compositions are dietary supplements.
  • nutraceutical compositions are medical foods.
  • the term “amelioration” may include prevention (e.g., delay), reduction (e.g., in frequency and/or intensity), improvement, and/or palliation of a state, or one or more features thereof, experienced by a patient. Amelioration may include, but does not require, complete recovery or complete prevention of a disease, disorder or condition (e.g., radiation injury).
  • an appropriate reference measurement may be or may comprise a measurement in a particular system (e.g., in a single individual) under otherwise comparable conditions absent (e.g., prior to and/or after addition of) a particular agent or treatment, or in presence of an appropriate comparable reference agent.
  • an appropriate reference measurement may be or may comprise a measurement in a comparable system known or expected to respond in a particular way, for example in presence of the relevant agent or treatment.
  • prevention when used in connection with the occurrence of a disease, disorder, and/or condition, may include reducing a risk of developing the disease, disorder and/or condition and/or to delaying onset of one or more characteristics or symptoms of the disease, disorder or condition. Prevention may be considered complete when onset of a disease, disorder or condition has been delayed for a predefined period of time.
  • patient illness narrative may include a narrative expressed by a patient regarding the patient’s personal experiences with a disease, disorder, and/or condition.
  • An illness narrative is typically a narrative solicited from a patient, which enables a healthcare practitioner to build a more complete picture of the patient’s past and present health state in the context of the patient’s life, while providing the patient with an opportunity for self-reflection and validation.
  • the term “personal model” and/or “personal disease model” may include a construction built based on patient input, which enables the patient to identify stressors, counter-productive behaviors, unhelpful thoughts, and negative emotions as associated with the patient’s disease, disorder, and/or condition.
  • a personal model is constructed as a graphical representation, which comprises text corresponding to patient-selected counter-productive behavior(s), unhelpful thought(s), and negative emotion(s), superimposed on a flow diagram illustrating links between the patient’s behaviors, thoughts, and emotions.
  • a personal model graphical representation comprises text corresponding to causes and/or stressors of symptoms.
  • a personal model may be utilized to help a patient identify links between their behaviors, thoughts, and emotions, and to help a patient consider possible changes in their behavior that could be implemented to address their symptoms.
  • the term “ecological momentary assessment” may include repeatedly sampling a subject’s current behaviors and experiences in real time, in the subject’s natural environment, with the aim of minimizing recall bias and allowing study of microprocesses that influence behavior in real-world contexts.
  • machine learning module may include a computer implemented process that implements one or more particular machine learning algorithms, such as supervised, unsupervised, and semi-supervised systems, an artificial neural network (ANN), random forest, decision trees, support vector machines, and the like, in order to determine, for a given input, one or more output values.
  • machine learning algorithms such as supervised, unsupervised, and semi-supervised systems, an artificial neural network (ANN), random forest, decision trees, support vector machines, and the like, in order to determine, for a given input, one or more output values.
  • FIG. 1 A depicts a schematic of a system 100 A for treating gastrointestinal and inflammatory health conditions using prescription digital therapeutics in combination with other therapies, according to one or more embodiments.
  • system 100A includes: an online system 110 for digital content associated with the adaptive interventions, one or more client devices including client device 120 for delivering the behavioral therapy and skills training to one or more users, one or more external systems including external system 130, and a network 140 for data transmission between the online system 110, the client device(s) 120, and the external system(s) 130.
  • the system 100A includes functionality for educating patients (e.g., patients, users of the platform, etc.) regarding treatment and therapy options in the context of improving symptoms associated with GI and/or inflammatory health conditions; detecting, in real or near-real time, states of GI and/or inflammatory health condition symptom severity in non-invasive manners; and delivering therapeutic interventions in a customized, and adaptive manner to one or more users/patients exhibiting GI and/or inflammatory health condition symptoms.
  • the system 100A can provide tailored cognitive behavioral therapies (CBTs) and/or other therapeutic modalities, such as psychotherapy, acceptance commitment therapy (ACT), dialectical behavioral therapy (DBT), exposure therapy, mindfulness-based cognitive therapy (MCBT), hypnotherapy, experiential therapy, and psychodynamic therapy for patients in an adaptive and customizable manner.
  • CBTs cognitive behavioral therapies
  • ACT acceptance commitment therapy
  • DBT dialectical behavioral therapy
  • MCBT mindfulness-based cognitive therapy
  • hypnotherapy hypnotherapy
  • experiential therapy and psychodynamic therapy
  • components of the above-listed therapeutic modalities may be combined to tailor a therapeutic intervention regimen to the needs of a particular patient.
  • GI and/or inflammatory health conditions are indicated herein, variations of the system 100A can be adapted for generation and provision of interventions for systems associated with other health conditions.
  • the online system 110 functions to generate, store, and transmit digital content associated with the behavioral therapy and related adaptive interventions, according to algorithms that allow the online system 110 to administer (or guide administration) of interventions to patients in a timely and customized manner.
  • the online system 110 thus procures digital content associated with one or more therapeutic interventions and allows users/patients of the system 100 A to access the digital content in an active or passive manner, in order to improve the patient(s)’ ability to manage GI and/or inflammatory health condition symptoms.
  • the online system 110 can include content generation components 112, content storage components 114, content transmission components 116, communication elements 118, and/or analytic platform 119 elements, implemented in computer architecture.
  • the online system 110 can additionally or alternatively include any other suitable subsystems or components associated with administration of guided therapy, adaptive interventions, and/or monitoring of patient health condition states.
  • the online system 110 can include computing architecture configured for generation of interactive digital objects in computer-readable formats, where such interactive digital objects can be included in modules of therapeutic interventions provided to patients exhibiting one or more GI and/or inflammatory health condition symptoms.
  • the content generation components 112 can include architecture for generation of content in one or more of: visual formats (e.g., with image objects, video objects, etc.), audible formats, haptic formats, and any other suitable formats.
  • Such content can be delivered through output devices of other components of the system 100A, such as display components (e.g., of a device, of an augmented reality device, of a virtual reality device, etc.), speaker components, haptic output device components, and/or any other suitable components.
  • display components e.g., of a device, of an augmented reality device, of a virtual reality device, etc.
  • speaker components e.g., of a headset, etc.
  • haptic output device components e.g., haptic output device components, and/or any other suitable components.
  • the online system 110 can include architecture for storage and retrieval of computer-readable media associated with digital content and/or other objects.
  • Data storage systems can be associated with any suitable format, and include components configured for cloud and/or non-based cloud computing.
  • the information stored in the content storage components 114 can be organized according to specific data structures (e.g., with relational, columnar, correlation, or other suitable architecture).
  • Stored content can be associated with various digital objects (e.g., graphical/textual/audio/visual/haptic objects associated with content, and/or rearrangement of objects within particular environments, as associated with therapeutics and/or communications between entities, as described in more detail below).
  • the online system 110 can be configured to transmit content over wired and/or wireless interfaces, through network 140 (described in more detail below).
  • the content transmission components 116 of the online system 110 can include interfaces to the network 140, for content transmission to client devices 120 and/or external systems 130.
  • the online system 110 can include elements that enable communications between patients and other entities (e.g., care providers, coaches associated with health interventions, other patients, etc.) in text format, in audio format, and/or in any other suitable formats.
  • the online system 110 can support messaging, calling, and/or any other suitable communication types using web or other computer-based communication subsystems.
  • the online system 110 can include architecture for an analytics platform 119 for performing analytics in relation to generation of interventions (e.g., digital therapeutics as monotherapies, digital therapeutics as combinatorial therapies), evaluation of performance of interventions (e.g., in relation to performance, in relation to effectiveness, etc.), modification of interventions (e.g., in relation to content aspects, in relation to frequency aspects, etc.), provision of interventions (e.g., delivery method, etc.), generating and processing training data for refinement of models for intervention generation and provision, and other architecture for performing analytics.
  • interventions e.g., digital therapeutics as monotherapies, digital therapeutics as combinatorial therapies
  • evaluation of performance of interventions e.g., in relation to performance, in relation to effectiveness, etc.
  • modification of interventions e.g., in relation to content aspects, in relation to frequency aspects, etc.
  • provision of interventions e.g., delivery method, etc.
  • generating and processing training data for refinement of models for intervention generation and provision e.g., delivery method, etc.
  • one or more portions of the online system 110 can include processing subsystem components comprising non-transitory media storing instructions for executing one or more method operations described below.
  • the processing subsystem components can be distributed across the online system 110, client devices 120, and external systems 130, or organized in any other suitable manner.
  • the online system 110 can be implemented in a network- addressable computing system that can host one or more components for generating, storing, receiving, and sending data (e.g., content-related data, user-related data, data related to entities associated with various therapeutics, etc.).
  • the online system 110 can thus be accessed by the other components of the system 100 A either directly or via network 140 described below.
  • the online system 110 can include one or more servers (e.g., unitary servers, distributed servers spanning multiple computers or multiple datacenters, etc.).
  • the servers can include one or more server types (e.g., web server, messaging servers, advertising servers, file servers, application servers, exchange servers, database servers, proxy servers, etc.) for performing functions or processes described.
  • each server can thus include one or more of: hardware, software, and embedded logic components for carrying out the appropriate functionalities associated with the method(s) described below.
  • the client device(s) 120 function to deliver the behavioral therapy and/or adaptive interventions generated and/or stored by the online system 110 to patients exhibiting GI and/or inflammatory health condition symptoms in a timely manner.
  • the client device(s) 120 can include computing components, input devices, and/or output devices providing interfaces for receiving patient inputs and transmitting digital content data and/or sensor-derived data over the network 140 (described in more detail below).
  • the client device(s) 120 can include one or more of: mobile computing devices (e.g., a smartphone a personal digital assistant); a conventional computing system (e.g., desktop computer, laptop computer); a tablet computing device; a wearable computing device (e.g., a wrist-borne wearable computing device, a head-mounted wearable computing device, an apparel-coupled wearable computing device); a toilet-interfacing computing device; and any other suitable computing device.
  • mobile computing devices e.g., a smartphone a personal digital assistant
  • a conventional computing system e.g., desktop computer, laptop computer
  • a tablet computing device e.g., a wearable computing device (e.g., a wrist-borne wearable computing device, a head-mounted wearable computing device, an apparel-coupled wearable computing device); a toilet-interfacing computing device; and any other suitable computing device.
  • a wearable computing device e.g., a wrist-borne wearable computing device, a head-mounted wearable computing device
  • the client device(s) 120 can be configured to store and/or execute an application (e.g., mobile application, web application) that allows a user of the client device 120 to interact with the online system 110 by way of the network 140, in order to receive digital content associated with one or more therapeutic interventions and/or provide data associated with survey responses, sensor-derived data associated with interactions with such interventions, and/or any other suitable data.
  • the client device(s) 120 can include operation modes for administering treatments to the user (e.g., in relation to providing prescription digital therapeutics upon diagnosis of the GI and/or inflammatory health condition of the user, in relation to providing medications, in relation to providing pain management therapies, etc.).
  • the external system(s) 130 function to transmit data (e.g., 3 rd party data) and/or receive data (e.g., 3 rd party data) associated with therapeutic interventions and/or user data (e.g., patient data).
  • the external system(s) 130 can include systems associated with electronic health records (EHRs) of the patient(s), systems associated with collection and/or storage of patient data (e.g., biometric data, behavioral data, social network data, communication data, etc.), systems associated with care providers (e.g., health insurance providers, health care practitioners, etc.), and/or any other suitable systems.
  • EHRs electronic health records
  • care providers e.g., health insurance providers, health care practitioners, etc.
  • the external system(s) can provide applications for communicating data in a manner that is protective of personal health information (PHI) and/or other sensitive patient data. Additionally or alternatively, the external system(s) can be associated with 3 rd party content generators and generate digital content in visual formats, audible formats, haptic formats, and/or any other suitable formats.
  • PHI personal health information
  • the external system(s) can be associated with 3 rd party content generators and generate digital content in visual formats, audible formats, haptic formats, and/or any other suitable formats.
  • the external system(s) 130 and/or client device(s) 120 can be configured to interact with the online system 110 by way of an application programming interface (API) executing on a native operating system of the external system(s) 130 and/or client device(s), in order to access API-associated data associated with the therapeutic interventions, patient health records, and/or other data (e.g., biometric data, patient behavior data through social networks, communication data through communication subsystems, etc.).
  • API application programming interface
  • the external system(s) 130 and/or client devices 120 can further include sensing components configured to generate data from which patient biometrics and/or behaviors can be extracted.
  • the external system(s) 130 and/or client devices 120 can include sensing components associated with one or more of: activity of a patient (e.g., through accelerometers, gyroscopes, motion coprocessing devices, etc.); facial expressions of the patient (e.g., through eye tracking, through image/video processing) for determination of cognitive states (e.g., associated with depression, anxiety, emotions, etc.) and/or performance of activities and/or interacting with content provided through the intervention regimen; physiological and/or psychological stress of a patient (e.g., in relation to respiration parameters, in relation to cardiovascular parameters, in relation to galvanic skin response, in relation to neurological activity, in relation to other stress biometrics, etc.); sleep behavior of a patient (e.g., with a sleep-monitoring
  • the external system(s) 130 and/or client devices 120 can include components for extracting behavioral data associated with communications and social behavior, which can be indicative of changes in patient health associated with different symptoms.
  • Such components can include location sensors (e.g., direct location sensors, location sensing modules based on connections to local networks, triangulation systems, etc.) for tracking user motility and/or other behavior patterns, components associated with API access to social networking data, components associated with messaging communication behavior (e.g., components for accessing SMS or other messaging application data of a patient, with respect to messaging entities, messaging content, etc.), components associated with calling communication behavior (e.g., in relation to inbound/outbound calls, in relation to call duration, in relation to call content, etc.), data from digital assistants (e.g., voice- activated digital assistants) and any other suitable components from which behavioral data can be extracted.
  • location sensors e.g., direct location sensors, location sensing modules based on connections to local networks, triangulation systems, etc.
  • components associated with API access to social networking data
  • the network 140 functions to enable data transmission between the online system 110, the client device(s) 120, and the external system(s) 130, in relation to detection of patient states of wellbeing (e.g. with respect to GI and/or inflammatory health condition symptoms).
  • the network 140 can include a combination of one or more of local area networks and wide area networks, and/or can include wired and/or wireless connections to the network 140.
  • the network 140 can implement communication linking technologies including one or more of: Ethernet, worldwide interoperability for microwave access (WiMAX), 802.11 architecture (e.g., Wi-Fi, etc.), 3G architecture, 4G architecture, 5G architecture, long term evolution (LTE) architecture, code division multiple access (CDMA) systems, digital subscriber line (DSL) architecture, and any other suitable technologies for data transmission.
  • WiMAX worldwide interoperability for microwave access
  • 802.11 architecture e.g., Wi-Fi, etc.
  • 3G architecture 4G architecture
  • 4G architecture 5G architecture
  • long term evolution (LTE) architecture long term evolution
  • CDMA code division multiple access
  • DSL digital subscriber line
  • the network 140 can be configured for implementation of networking protocols and/or formats including one or more of: hypertext transport protocol (HTTP), multiprotocol label switching (MPLS), transmission control protocol/Internet protocol (TCP/IP), file transfer protocol (FTP), simple mail transfer protocol (SMTP), hypertext markup language (HTML), extensive markup language (XML), and any other suitable protocol/format.
  • HTTP hypertext transport protocol
  • MPLS multiprotocol label switching
  • TCP/IP transmission control protocol/Internet protocol
  • FTP file transfer protocol
  • SMTP simple mail transfer protocol
  • HTTP hypertext markup language
  • XML extensive markup language
  • the system 100 A can include or be configured to interface with other system components associated with generation and/or delivery of behavioral therapy and related adaptive interventions.
  • the system 100A can include or be associated with environmental control devices configured to affect patient states of wellbeing passively or actively, in relation to the intervention types described in more detail below.
  • such devices can include environmental control devices, including one or more of lighting control devices, audio output devices, temperature control devices, and any other suitable environmental control devices.
  • the system 100A can coordinate operation of such devices with delivery of adaptive interventions to patients, such that aspects of the patient’s environment can be modulated in coordination with other therapeutic measures to improve patient wellbeing in relation to GI and/or inflammatory health condition symptoms.
  • the system 100A can include and/or communicate control instructions for devices in the environment of the patient, in order to facilitate control of pain volume, in relation to magnitude of pain/intensity of pain (e.g., by focusing the user on real time environmental changes) and/or to cause improvements in lives of patients in another suitable manner.
  • the system 100A can include an output device (e.g., component of client device 120, component of external system 130, etc.) that functions as an environmental control device in an environment of the patient, where the processing subsystem further includes instructions for adjusting the operation mode in coordination with monitoring a change in symptoms (e.g., pain symptoms) of the patient. Modulation of output device operation modes can thereby produce an adjustment in symptoms (e.g., pain volume) associated with the condition of the patient.
  • the environmental control device can modulate one or more of an audio output, a thermal parameter adjustment, a visually-observed output, a haptic output, and a light output in the environment.
  • the system 100A can include an output device (e.g., component of client device 120, component of external system 130, etc.) that functions as a communication device for transmitting communications between the patient and an entity associated with the patient, where the processing subsystem further includes instructions for generating a scripted communication for transmission to an entity associated with the patient, in coordination with monitoring a change in a physiological symptoms of the patient.
  • an output device e.g., component of client device 120, component of external system 130, etc.
  • the processing subsystem further includes instructions for generating a scripted communication for transmission to an entity associated with the patient, in coordination with monitoring a change in a physiological symptoms of the patient.
  • the system 100 A can be configured to interface or include any other suitable system components.
  • Embodiments, variations, and examples of one or more components of the system 100 A described above can implement one or more embodiments, variations, and examples of the methods 200A, 200B, and/or 200C, as described below.
  • the system 100A can additionally or alternatively be configured to implement other methods.
  • FIG. IB depicts a block diagram of a production environment 100B for treating gastrointestinal and inflammatory health conditions using prescription digital therapeutics in combination with other therapies, according to one or more embodiments.
  • production environment 100B includes PDT computing environment 141, patient 142, and patient computing systems 144.
  • production environment 100B optionally includes patient monitoring devices 146, health practitioner 148, and/or health practitioner computing systems 149.
  • production environment 100B includes communications channels 143, which facilitate communication between PDT computing environment 141 and one or more of patient computing systems 144, patient monitoring devices 146, and health practitioner computing systems 149.
  • PDT computing environment 141 includes PDT user interface 150, patient monitoring system 152, patient condition determination system 166, personalized regimen generation system 168, content selection system 170, and module gating system 172.
  • PDT computing environment 141 further includes patient database 156.
  • patient database 156 includes patient profile and preassessment data 158, patient condition data 162, patient personalized regimen data 164, and patient interaction data 154.
  • PDT computing environment 141 further includes therapeutic module database 174.
  • therapeutic module database 174 includes therapeutic module data 176, which further includes first therapeutic module 178, and second therapeutic module 184 through Nth therapeutic module 190.
  • first therapeutic module 178 includes module 1 content data 180 and module 1 protocol data 182
  • second therapeutic module 184 includes module 2 content data 186 and module 2 protocol data 188
  • /? therapeutic module 190 includes module N content data 192 and module N protocol data 194.
  • PDT computing environment 141 further includes processor 196 and physical memory 198, which together coordinate the operation and interaction of the data and data processing systems associated with PDT computing environment 141.
  • processor 196 and physical memory 198 which together coordinate the operation and interaction of the data and data processing systems associated with PDT computing environment 141.
  • patient 142 is provided with a prescription digital therapeutics (PDT) system, wherein the PDT system remotely administers guided behavioral therapy through an adaptive intervention regimen including a plurality of interactive therapy modules.
  • the PDT computing environment 141 communicates with patient 142 via one or more communications channels 143 between patient computing systems 144 and a user interface of the PDT system, such as PDT user interface 150.
  • therapeutic module database 174 contains a repository of data related to each of the available therapy modules, including module content data and module protocol data.
  • a therapeutic protocol defines the rules, syntax, semantics, and synchronization of communications with a patient.
  • the therapeutic module database may be populated and/or updated periodically by health practitioner 148, for example, through health practitioner computing systems 150.
  • module gating system 172 is responsible for determining which parts of the intervention regimen patient 142 has already completed, if any, as well as determining which modules and/or module content should be gated, locked, and/or unlocked. The operation of module gating system 172 will be discussed in additional detail below.
  • content selection system 170 may select module 1 content data 180 from first therapeutic module 178 of therapeutic module database 174. Content selection system 170 may then administer module 1 content data 180 to patient 142 through PDT user interface 150. In one embodiment, module 1 content data 180 is administered to patient 142 according to one or more therapeutic protocols defined by module 1 protocol data 182.
  • first therapeutic module 178 may be an introduction and education module, which introduces the patient to the system features, and provides education to the patient relating to the methods utilized by the system and/or relating to the patient’s particular disease, disorder, and/or condition.
  • first therapeutic module 178 also generates patient profile and pre-assessment data 158 by virtue of interaction between patient 142 and the content provided through PDT user interface 150 of the PDT system.
  • patient profile and pre-assessment data is generated independently of first therapeutic module 178. Additional details regarding first therapeutic module 178 (the introduction and education module) will be provided below.
  • content selection system 170 may select module 2 content data 186 from second therapeutic module 184 of therapeutic module database 174. Content selection system 170 may then administer module 2 content data 186 to patient 142 through PDT user interface 150. In one embodiment, module 2 content data 186 is administered to patient 142 according to one or more therapeutic protocols defined by module 2 protocol data 188.
  • second therapeutic module 184 may be a physical illness narrative module, which, in some embodiments, solicits narratives from the patient regarding the impact that the patient’s disease, disorder, and/or condition has had on their lifestyle, mental state, and overall well-being.
  • second therapeutic module 184 generates patient illness narrative data (not shown) by virtue of interaction between patient 142 and the content provided through PDT user interface 150 of the PDT system.
  • second therapeutic module 184 also introduces the patient to the concept of a personal disease model, and guides the user through the process of creating a personal model.
  • second therapeutic module 184 solicits additional data from the patient for use in creation of the personal model, such as data related to the patient’s counter-productive behaviors, unhelpful thoughts, and negative emotions. Additional details regarding second therapeutic module 184 (the physical illness narrative module) will be provided below.
  • patient profile and pre-assessment data 158 is processed by patient condition determination system 166 of the PDT system to generate patient condition data 162, as will be discussed in additional detail below.
  • personalized regimen generation system 168 utilizes patient profile and pre-assessment data 158 and patient condition data 162 to generate a personalized intervention regimen for the patient, which is represented in FIG. IB by patient personalized regimen data 164.
  • patient personalized regimen data 164 includes data representing regimen details such as, but not limited to, which of the available remaining therapy modules to administer to the patient, in what order to administer the therapy modules, a time schedule for when/how often to administer the therapy modules, what content to include in each of the therapy modules, and how to present the therapy module content to the patient.
  • personalized regimen generation system 168 may further process patient profile and pre-assessment data 158 and patient condition data 162 to identify one or more current or potential complementary therapies to be administered to patient 142 in combination with the behavioral therapy components represented by therapeutic module data 176.
  • complementary therapies may include one or more non- behavioral therapies, such as pharmaceutical and/or nutraceutical compositions, and personalized regimen generation system 168 may incorporate data related to administration of such therapies (e.g. therapy type, dosage amount, and dosage schedules) into patient personalized regimen data 164. Additional details regarding generation of a personalized intervention regimen for the patient will be discussed below.
  • patient personalized regimen data 164 is provided to module gating system 172 to determine which components of the intervention should be gated, locked, or unlocked, and content selection system 170 may then administer content data related to the appropriate therapeutic module to patient 142 through PDT user interface 150.
  • content selection system 170 may provide one or more options, notifications, alerts, and/or recommendations to patient 142 through PDT user interface 150, wherein the one or more options, notifications, alerts, and/or recommendations relate to current or potential complementary (non-behavioral) therapies to be administered in combination with the behavioral therapy modules/components.
  • the patient’s interactions with the behavioral therapy components and/or the patient’s interactions with and/or reactions to the non-behavioral therapy components of the personalized intervention regimen may be monitored remotely, either at fixed intervals, or in near real-time.
  • the patient’s interactions with the regimen components such as through a patient monitoring system 152 of the PDT system, or through external patient monitoring devices 146, such as sensors, etc., which may then transmit patient data and/or patient interaction data 154 over one or more communications networks 143.
  • the progression of the user through the through the therapeutic modules may be dynamically and remotely controlled, for example, though a system such as module gating system 172.
  • module gating system 172 may be programmed to gate, lock, or unlock various modules and module components at set intervals. If the patient interaction data 154 indicates that the user would benefit from shorter or longer intervals between lesson modules, module gating system 172 may dynamically adjust how often to unlock new content. A more detailed description of the module gating system used to dynamically and remotely control user progression through the modules will be provided below.
  • the patient’s personalized intervention regimen may be modified and/or updated.
  • user input in one module might change the recommendation for how to present subsequent modules, and a patient’s reactions to one more non-behavioral therapy components may change the recommendations for the dosing of that particular component.
  • this allows for the personalized intervention regimen to be dynamically adaptive, thus resulting in administration of the guided therapy in combination with other types of GI and/or inflammatory therapies in a manner that is most efficient and effective for the patient. Additional details regarding dynamically modifying the patient’s personalized intervention regimen will be discussed in further detail below.
  • FIG. 2A depicts a flowchart of a method 200A for treating gastrointestinal and inflammatory health conditions using prescription digital therapeutics in combination with other therapies, according to one or more embodiments.
  • the method 200 A can include operations for: providing a patient with a user interface to a prescription digital therapeutics (PDT) system wherein the PDT system remotely administers guided behavioral therapy to the patient 204; performing, by the PDT system, a pre-assessment of a patient exhibiting one or more GI and/or inflammatory health condition symptoms to generate patient profile and preassessment data 206; processing, by the PDT system, the patient profile and pre-assessment data to generate patient condition data, wherein the patient condition data includes an identification of the patient’s condition, condition sub-type and/or condition severity 208; processing, by the PDT system, the patient profile and pre-assessment data and the patient condition data to identify one or more complementary non-behavioral therapy components to be administered to the patient in combination with behavioral therapy components 210; processing, by the PDT system, the patient profile and pre-assessment data and the patient condition data to generate a personalized intervention regimen for the patient,
  • PDT prescription digital therapeutics
  • method 200 A functions to educate users regarding treatment and therapy options in the context of improving symptoms associated with a variety of health conditions; detect, in real or near-real time, states of health condition symptom severity in non-invasive manners; and administer therapeutic interventions in a customized, and adaptive manner to one or more patients exhibiting health condition symptoms.
  • the method 200A can be used to provide tailored behavioral therapy to patients in an adaptive and customizable manner.
  • the method 200A can be used to provide behavioral therapy to patients in combination with other types of complementary, non- behavioral therapies. Method 200A will be discussed in additional detail below.
  • providing guided behavioral therapy and skills training includes providing adaptive interventions for patients with gastrointestinal (GI) and/or inflammatory health conditions.
  • GI gastrointestinal
  • FIG. 2B depicts a flowchart of a method 200B for providing adaptive interventions for gastrointestinal and inflammatory health conditions, according to one or more embodiments.
  • a method 200B can include operations for: performing a pre-assessment of a patient exhibiting one or more GI and/or inflammatory health condition symptoms 226; generating an intervention regimen for the patient upon processing data from the pre-assessment with an intervention-determining model 228; delivering the intervention regimen to the patient 230; monitoring a set of interactions between the patient and modules of the intervention regimen and a health status progression of the patient contemporaneously with delivery of the intervention regimen 232; and in response to at least one of the set of interactions and the health status progression, performing an action configured to improve wellbeing of the patient with respect to the GI and/or inflammatory health condition 234.
  • Method 200B will be discussed in additional detail below.
  • FIG. 2C depicts a flowchart of a method 200C for providing adaptive interventions for gastrointestinal and inflammatory health conditions, according to one or more embodiments.
  • a method 200C can include operations for: establishing an interface between a device and a user 240; from the interface, receiving a set of signals associated with a GI and/or inflammatory health condition of the user, wherein the set of signals encodes physiological data, behavioral data, environmental stress data, emotional data, and cognitive data of the user 242; determining a characterization of the GI and/or inflammatory health condition upon processing the set of signals with a model 244; based upon the characterization, modulating content of a treatment comprising a set of components, the set of components comprising a subset of cognitive behavioral therapy (CBT) components for improving a state of the user 246; and administering the treatment to the user 248.
  • CBT cognitive behavioral therapy
  • Methods 200B and 200C function to educate patients regarding treatment and therapy options in the context of improving symptoms associated with GI and/or inflammatory health conditions; detect, in real or near-real time, states of GI and/or inflammatory health condition symptom severity in non-invasive manners; and deliver interventions in a customized, and adaptive manner to one or more users exhibiting GI and/or inflammatory health condition symptoms.
  • methods 200B and 200C can be used to provide tailored cognitive behavioral therapy (CBT) and/or other therapeutic modalities to patients in an adaptive and customizable manner. While GI and/or inflammatory health condition symptoms are described, variations of the methods 200B and 200C can be adapted for generation and provision of interventions for systems associated with other health conditions.
  • aspects of methods 200A, 200B, and 200C can be performed at desired frequencies (e.g., weekly, more often than weekly, less often than weekly).
  • desired frequencies e.g., weekly, more often than weekly, less often than weekly.
  • the method can promote interactions more often than weekly (e.g., daily, 2 times a week, 3 times a week, four times a week, five times a week, six times a week, etc.) or less often than weekly, in relation to reinforcement of skills acquired by the patients.
  • received data can be processed in real time, or non-real time.
  • the methods 200A, 200B, and 200C can have delivery and processing aspects associated with other suitable frequencies.
  • the methods 200 A, 200B, and 200C can be performed by an embodiment, variation, or example of the system 100A described in above (e.g., in relation to processing subsystem components with instructions stored in non-transitory media and other input/output devices); however, the methods 200A, 200B, and 200C can additionally or alternatively be performed using any other suitable system components.
  • FIG. 2 A depicts a flowchart of a method 200 A for treating gastrointestinal and inflammatory health conditions using prescription digital therapeutics in combination with other therapies, according to one or more embodiments.
  • method 200 A begins at BEGIN 202, and method flow proceeds to operation 204.
  • a patient is provided with a user interface to a prescription digital therapeutics (PDT) system wherein the PDT system remotely administers guided behavioral therapy to the patient.
  • PDT prescription digital therapeutics
  • a patient may consult with one or more healthcare practitioners regarding symptoms that the patient is experiencing, and the healthcare practitioner may determine that the patient is suffering from one or more health-related conditions.
  • some health-related conditions can be managed or alleviated through administration of a variety of therapies, such as, but not limited to, psychotherapy, cognitive behavioral therapy (CBT), acceptance commitment therapy (ACT), dialectical behavioral therapy (DBT), mindfulness-based cognitive therapy (MCBT), exposure therapy, hypnotherapy, experiential therapy, and psychodynamic therapy.
  • therapies such as, but not limited to, psychotherapy, cognitive behavioral therapy (CBT), acceptance commitment therapy (ACT), dialectical behavioral therapy (DBT), mindfulness-based cognitive therapy (MCBT), exposure therapy, hypnotherapy, experiential therapy, and psychodynamic therapy.
  • components of the above listed modalities may be combined to form a hybrid type of therapy.
  • a hybrid therapy may utilize particular components taken from CBT, ACT, and DBT, wherein the components are selected based on the specific needs of the patient.
  • behavioral therapies can also be combined with other types of non-behavioral therapies, as will be discussed in detail below.
  • CBT cognitive behavioral therapy
  • Those skilled in the art will be aware that behavioral therapy, and in particular cognitive behavioral therapy (CBT), has traditionally been considered effective for treatment of psychological conditions such as, for example, alcohol and drug use problems, anxiety disorders, depression, eating disorders, emotional trauma, grief or loss, marital or other relationship problems, mental illness, obsessive-compulsive disorder, pain, phobias, post- traumatic stress disorder (PTSD), schizophrenia, sexual disorders, sleep disorders, etc.
  • behavioral therapy has traditionally involved counseling by a mental health provider such as a psychiatrist, psychologist, or other provider; typically, behavioral therapy provides a structured format and a limited (i.e., finite) number of sessions.
  • the present disclosure provides new behavioral therapy technologies which may, in some embodiments, be provided to an individual via non-human interactions, such as via a computer-based system.
  • such computer-based systems are designed to mimic portions of interactions, such as useful exercises, assessments, and techniques that may traditionally be carried out in the context of counseling sessions with a mental health provider and/or via exercises recommended thereby (e.g., ‘homework,’ such as values inventories, journaling exercises, self-assessments, and the like).
  • provided behavioral therapies may be useful in the treatment of certain physiological conditions, such as, but not limited to, inflammatory and/or GI health conditions (e.g., for example, IBS, IBD, etc ).
  • the doctor may prescribe a therapeutics system to the patient.
  • the therapeutics system is a prescription digital therapeutics (PDT) system.
  • PDT prescription digital therapeutics
  • a PDT system differs from traditional computer-based wellness systems, in that the PDT system is required to be approved by a government agency before it can be marketed for administration to humans.
  • a PDT system requires FDA approval and rigorous clinical evidence to substantiate intended use and impact on disease state.
  • a PDT system is typically a system for which a medical prescription is required for administration to patients.
  • a patient is provided with a prescription digital therapeutics (PDT) system at operation 204
  • method flow proceeds to operation 206.
  • the PDT system performs a pre-assessment of a patient exhibiting one or more GI and/or inflammatory health condition symptoms to generate patient profile and pre-assessment data.
  • an embodiment of the online system in coordination with the network and a client device, can perform the preassessment of operation 206 contemporaneously with executing an onboarding process with the patient with the online system.
  • Operation 206 functions to retrieve data describing characteristics of the patient, preferences of the patient, goals of the patient and/or any other suitable patient features that can be used to provide adaptive interventions through an intervention regimen associated with administration of guided behavioral therapy to the patient in a customized and personalized manner.
  • operation 206 can include preassessing and onboarding patients to generate patient profile and pre-assessment data, wherein the patient profile and pre-assessment data includes one or more of: demographics (e.g., genders, ages, familial statuses, residential location, ethnicities, nationalities, socioeconomic statuses, sexual orientations, etc.), household situations (e.g., living alone, living with family, living with a caregiver, etc.), dietary characteristics (e.g., omnivorous, vegetarian, pescatarian, vegan, reduced carbohydrate consumption, reduced acid consumption, gluten-free, simple carbohydrate, or other dietary restrictions, etc.), levels of activity, levels of alcohol consumption, levels of drug use, psychological symptom severity, levels of mobility (e.g., in relation to distance traveled in a period of time), biomarker statuses (e.g., fecal calprotectin, cholesterol levels, lipid states, blood biomarker statuses, etc.), weight
  • demographics e.g., genders,
  • patient profile and pre-assessment data generated at operation 206 includes data related to non-behavioral therapies that the patient is receiving and/or has received.
  • patient profile and pre-assessment data may include data such as, but not limited to, data indicating the type of non-behavioral therapy (e.g., pharmaceutical, nutraceutical, etc.), data indicating the class of non-behavioral therapy (e.g., anticholinergic medications, antidiarrheal medications, laxatives, antidepressants, probiotics, prebiotics, synbiotics, etc.), data indicating the specific name of the non-behavioral therapy (e.g., alosetron (e.g., Lotronex®), eluxadoline (e.g., Viberzi®), linaclotide (e.g., Linzess®), lubiprostone (e.g., Amitiza®), plecanatide (e.g.
  • alosetron e.g
  • patient profile and pre-assessment data includes data, such as, but not limited to, physiological data, behavioral data, environmental stress data, emotional data, and cognitive data of the patient.
  • the pre-assessment and/or onboarding process performed in operation 206 can identify mental health statuses of the patient, in relation to comorbid or non-comorbid conditions (e.g., associated with anxiety, associated with depression, associated with social behavior, etc.), where the intervention regimen described in more detail below can be configured to improve mental health states of the patient in a timely and adaptive manner.
  • related data can include psychological and/or disease symptom/clinical profile data that informs selection of high priority therapy components, where examples include data such as, but not limited to: illness-related ruminations being predominant; symptoms triggered by anticipatory anxiety; aspects adapted for types of reinforcement based on level of anhedonia, as assessed from system-provided tools associated with depression assessment (e.g., upon identification of anhedonia characteristics of the patient, promoting behavioral activation content by the system and response chaining, where response chaining involves linking of effortful avoided tasks to those that are neutral or slightly rewarding); sources of motivation; reward sensitivity (e.g., sensitivity associated with drive and reward responsiveness (e.g., using a BIS/BAS assessment tool); and threat sensitivity.
  • data such as, but not limited to: illness-related ruminations being predominant; symptoms triggered by anticipatory anxiety; aspects adapted for types of reinforcement based on level of anhedonia, as assessed from system-provided tools associated with depression assessment (e.g., upon identification of anhedonia
  • the method 200A can include receiving a reward sensitivity dataset characterizing motivation and reinforcement behavior of the patient, and modulating aspects of the treatment upon processing the reward sensitivity dataset with one or more models described herein.
  • Mental health, reward tendencies and sensitivity, and motivational aspect identification can, however, be assessed outside of the pre-assessment of operation 206.
  • the preassessment and/or onboarding process performed in operation 206 can identify user preferences associated with scheduling of content delivery (e.g., in relation to frequencies of content delivery described above) associated with one or more aspects of the intervention regimen, preferred formats (e.g., visual formats, audio formats, haptic formats, etc.) of content delivery, frequency of content delivery, location of user when content is delivered, specific device(s) to which content is delivered, and/or any other suitable user preferences.
  • preferred formats e.g., visual formats, audio formats, haptic formats, etc.
  • the preassessment and/or onboarding process performed in operation 206 can identify user goals for improving health, in relation to the intervention regimen.
  • Such goals can include one or more goals, such as, but not limited to: reduction of anxiety, reduction of negative emotions, reduction of depression symptoms, improvement of sleep behavior, improvement in socialization, improvement of GI and/or inflammatory health condition symptoms, improvement of medication adherence, improvement in GI and/or inflammatory-related quality of life, improvement of other health condition symptoms, and/or any other suitable goals.
  • Goals can be organized at a high level of abstraction (e.g., improve sleep behavior), and/or at lower levels of abstraction (e.g., improve quality of sleep, reduce number of symptom-induced disturbances to sleep, etc.).
  • the patient profile and pre-assessment data can be obtained through various mechanisms, including, but not limited to, from a pre-assessment module of the PDT system, from patient health records accessible by the PDT system, from API access of health monitoring systems through the PDT system, and/or from biometric sensor data obtained by the PDT system from various devices utilized by the patient.
  • patient profile and pre-assessment data can be collected repeatedly throughout performance of the methods described herein, as will be discussed in additional detail below.
  • the online system and/or other system components can implement surveying tools (e.g., to obtain self-report data from the patient) and/or non-survey-based tools for acquisition of data.
  • Survey tools can be delivered through an application associated with the PDT system executing on the client device of the patient and/or through another suitable method, where the survey tools can implement architecture for assessing the patient in relation to mental health, pain, GI and/or inflammatory health symptom severity or disease activity, types of GI and/or inflammatory health condition symptoms, and/or other statuses.
  • the surveying tools can be derived from one or more patient reported outcome instruments, such as, but not limited to: a Functional Bowel Disorder Severity Index (FBDSI) instrument, a Gastrointestinal Symptom Rating Scale - IBS (GSRS- IBS) instrument, an IBS-Adequate Relief (IBS-AR) instrument, an IBS Global Assessment of Improvement Scale (IBS-GAI) instrument, an IBS Symptom Severity Score (IBS-SSS) instrument, an IBS Quality of Life (IBS-QOL) instrument, a Patient Reported Outcome Measurement Information System (PROMIS) instrument (e.g., Abdominal Pain PROMIS scale, Constipation PROMIS scale, Diarrhea PROMIS scale, etc.), a Visual Analogue Scale for Irritable Bowel Syndrome (VAS-IBS), a patient health questionnaire (e.g., PHQ-9), an anxiety disorder questionnaire (e.g., GAD-7, PC-PTSD, SCARED), a work
  • FBDSI Functional Bo
  • survey components can be implemented during preassessment of a patient and/or within modules of the intervention regimen, as described in more detail below.
  • the online system and/or other system components can implement data from devices (e.g., non-survey data).
  • embodiments of the system can perform pre-assessment with implementation of data from devices including one or more devices, such as, but not limited to: electronic health record-associated devices; wearable devices (e.g., wrist-borne wearable devices, head-mounted wearable devices, etc.) for monitoring behavior and activities (e.g., related to physiological/cognitive stress, related to respiration activity, related to sedentary and active states, etc.) of the user; non-invasive torso- coupled devices (e.g., abdominal or stomach sensors configured to detect GI or digestive activity); ingestible smart-pill devices; smart toilet devices and/or other devices for analyzing stool and/or urine samples from the patient; and other devices.
  • devices including one or more devices, such as, but not limited to: electronic health record-associated devices; wearable devices (e.g., wrist-borne wearable devices, head-mounted wearable devices, etc.) for monitoring behavior and activities (e.g., related to physiological/cognitive stress, related to respiration activity, related to sedentary
  • Non-survey-derived data can additionally or alternatively include data derived from API access of social networking platforms, other communication platforms (e.g., for extracting social behavior characteristics associated with text, voice, and other communications of the users), location-determining platforms, and/or other platforms, in order to assess social behaviors of the user.
  • multiple surveying tools may be combined in a single assessment module, or may be provided as distinct, separate, assessment modules.
  • Assessment modules may be based on, and used to solicit input for, a variety of diagnostic questionnaires, depending on a particular GI and/or inflammatory health condition that a patient is to be evaluated for. Additionally or alternatively, assessment modules may be designed to evaluate any other physiological and/or psychological conditions of the patient.
  • data pertaining to patient symptoms, quality of life, and other medical information may be obtained via access to electronic health records (EHRs) and/or electronic medical records (EMRs).
  • EHRs electronic health records
  • EMRs electronic medical records
  • applications in accordance with technologies as described herein may provide for communication with a secure database in order to receive and/or access EHR and/or EMR data for the user.
  • Such data may be used to populate a patient profile, and as a basis for tailoring content, e.g., as described herein.
  • method flow proceeds to operation 208.
  • the PDT system processes the patient pre-assessment data to generate patient condition data, wherein the patient condition data includes an identification of the patient’s condition, condition sub-type, and/or condition severity.
  • processing of the patient pre-assessment data in operation 208 can result in identification of the patient as having GI health condition symptoms associated with GI health, such as, but not limited to, one or more of: irritable bowel syndrome (IBS), inflammatory bowel disease (IBD, such as associated with Crohn’s disease or ulcerative colitis), lactose intolerance, gastroesophageal reflux disease (GERD), ulcers (e.g., peptic ulcer disease, gastric ulcers, etc.), functional dyspepsia, hernias, celiac disease, diverticulitis, malabsorption, short bowel syndrome, intestinal ischemia, pancreatitis, cysts, gastroparesis, gastritis, esophagitis, achalasia, strictures, anal fissures, hemorrhoids, proctitis, prolapse, gall stones, cholecystitis, cholangitis,
  • IBS irritable bowel syndrome
  • IBD inflammatory
  • processing of the patient pre-assessment data in operation 208 can result in identification of the patient as having inflammatory health condition symptoms associated with chronic inflammation, such as, but not limited to, one or more of: diabetes, cardiovascular diseases (e.g., hypertension), liver diseases, arthritis and joint diseases (e.g., rheumatoid arthritis), various allergies, asthma, chronic obstructive pulmonary disease (COPD), and/or any other suitable symptoms.
  • operation 208 can further identify one or more subtypes of a GI and/or inflammatory health condition.
  • IBS irritable bowel syndrome
  • the PDT system can be configured to receive, automatically detect, or automatically extract information regarding the particular subtype(s) of IBS that a patient has, based on a combination of patient health record data, data collected from health monitoring systems, data collected from biometric sensors, and data collected from patient-reported outcome instruments, in order to prioritize relevant content provided to the patient, in the interests of customizing the program.
  • subtypes of IBS may include IBS-C (with predominant constipation), IBS-D (with predominant diarrhea), and IBS-M (with mixed bowel habits). If the processing operation 208 identifies that the patient is predominantly subtype IBS-C, subsequent portions of the intervention regimen can prioritize content associated more highly with IBS-C. In some embodiments, however, subtype identification may be determined outside of the processing of operation 208.
  • operation 208 of method 200A includes a method of determining severity of the GI and/or inflammatory health condition.
  • operation 208 can calculate levels of a GI and/or inflammatory health condition-associated marker (e.g., from a sample from the patient, such as a stool sample or a breath sample, from interactions with the system, etc.) to identify the patient as having a certain state of severity (e.g., expression, phenotype, etc.) of the GI and/or inflammatory health condition.
  • a GI and/or inflammatory health condition-associated marker e.g., from a sample from the patient, such as a stool sample or a breath sample, from interactions with the system, etc.
  • operation 208 can be implemented through the PDT system executing on a mobile device or other device associated with the patient, where a user interface of the PDT system prompts inputs from the patient pertaining to various symptoms (e.g., pain, defecation, abdominal distension, digestive issues, cognitive symptoms, behavioral effects, etc.) and generates a report indicating severity of the GI and/or inflammatory health condition (e.g., IBS, IBD, etc ).
  • symptoms e.g., pain, defecation, abdominal distension, digestive issues, cognitive symptoms, behavioral effects, etc.
  • a report indicating severity of the GI and/or inflammatory health condition (e.g., IBS, IBD, etc ).
  • IBS irritable bowel syndrome
  • a survey tool such as the IBS Symptom Severity Scale (IBS-SSS), in which a patient provides grades for five facets of their IBS symptoms: severity of abdominal pain, frequency of abdominal pain, severity of abdominal distention, dissatisfaction with bowel habits, and interference with quality of life.
  • IBS-SSS IBS Symptom Severity Scale
  • Patient inputs are used to assign a score ranging from 0 to 500, with higher scores indicating more severe symptoms. Based on a patient score, a classification of mild, moderate, or severe IBS may be assigned.
  • the PDT system disclosed herein can include architecture for receiving data derived from the patient (e.g., through sensor components, through survey components, associated with pain characteristics, digestive characteristics, defecation characteristics, and other characteristics), processing the data with one or more models, and returning scores (e.g., measures of symptom severity, etc.). Scores can also be used for tagging user data with symptom severity, in relation to model aspects and model training/refmement described below.
  • method flow proceeds to operation 210.
  • the patient profile and pre-assessment data and the patient condition data are processed to identify one or more complementary non-behavioral therapy components to be administered to the patient in combination with behavioral therapy components.
  • the prescription digital therapeutics (PDT) system disclosed herein may utilize behavioral therapy components in combination with non-behavioral therapy components to provide treatment for various physiological conditions (e.g., conditions with one or more physical symptoms, features, or manifestations), such as those described herein.
  • the PDT system disclosed herein may administer behavioral therapies and associated components in combination with one or more non- behavioral therapies and associated components, such as those described herein.
  • behavioral therapy is administered to subject(s) who are receiving or have received non-behavioral therapy for a relevant disease, disorder, or condition.
  • behavioral therapies and non-behavioral therapies may be approved, and/or administered as a combination product.
  • prescription digital therapeutics (PDT) systems and methods described herein are utilized to administer guided behavioral therapy to a patient undergoing treatment for one or more GI and/or inflammatory health conditions via administration of one or more non-behavioral therapies.
  • GI health conditions those skilled in the art will be familiar with various approved and/or otherwise accepted non-behavioral therapies for GI health conditions, including, for example, pharmaceutical compositions such as, but not limited to: antibiotics, anticholinergic medications, antidiarrheal medications, antidepressants (e.g., tricyclic antidepressants, e.g., selective serotonin reuptake inhibitor (SSRI) antidepressants), antispasmodics, chloride channel activators, Guanylate Cyclase-C agonists, osmotic agents, laxatives, pain medications, selective serotonin (5-HT4) receptor agonists, sodium/hydrogen exchanger 3 (NHE3) inhibitors, and various IBS agents.
  • antibiotics e.g., anticholinergic medications, antidiarrheal medications, antidepressants (e.g., tricyclic antidepressants, e.g., selective serotonin reuptake inhibitor (SSRI) antidepressants
  • particular agents that may be utilized in therapy for GI health conditions may include one or more of: alosetron (e.g., Lotronex®), eluxadoline (e.g., Viberzi®), linaclotide (e.g., Linzess®), lubiprostone (e.g., Amitiza®), plecanatide (e.g., Trulance®), and rifaximin (e.g., Xifaxan®).
  • a patient suffering from a GI health condition may be treated using any combination of the above listed non-behavioral therapies.
  • compositions such as, but not limited to: anti-inflammatory therapies, biologies, corticosteroids, and immunomodulators.
  • pharmaceutical compositions relevant for treatment of chronic inflammation and/or inflammatory health conditions include various antiinflammatories, such as nonsteroidal anti-inflammatory drugs (NSAIDs) [e.g., Aminosalicylates (5-ASAS)].
  • NSAIDs nonsteroidal anti-inflammatory drugs
  • 5-ASAS Aminosalicylates
  • compositions relevant for treatment of chronic inflammation and/or inflammatory health conditions include blood pressure medications such as, angiotensin-converting enzyme (ACE) inhibitors, angiotensin II receptor blockers (ARBs), beta blockers, calcium channel blockers, diuretics, renin inhibitors, as well as alpha blockers, alpha-beta blockers, aldosterone antagonists, central-acting agents, and vasodilators.
  • blood pressure medications such as, angiotensin-converting enzyme (ACE) inhibitors, angiotensin II receptor blockers (ARBs), beta blockers, calcium channel blockers, diuretics, renin inhibitors, as well as alpha blockers, alpha-beta blockers, aldosterone antagonists, central-acting agents, and vasodilators.
  • ACE angiotensin-converting enzyme
  • ARBs angiotensin II receptor blockers
  • beta blockers calcium channel blockers
  • diuretics renin inhibitors
  • renin inhibitors
  • compositions relevant for treatment of chronic inflammation and/or inflammatory health conditions include compositions relevant for treatment of arthritis, such as biological response modifiers, such as tumor necrosis factor (TNF) inhibitors (e.g., etanercept and infliximab), corticosteroids, disease-modifying antirheumatic drugs (DMARDs), such as methotrexate and hydroxychloroquine, painkillers, and NSAIDs.
  • TNF tumor necrosis factor
  • DMARDs disease-modifying antirheumatic drugs
  • a patient suffering from an inflammatory health condition may be treated using any combination of the above listed non-behavioral therapies.
  • one or more non-behavioral therapies utilized for treatment of GI and/or inflammatory health conditions may include nutraceutical compositions such as supplements, probiotics, prebiotics, synbiotics, natural products, herbal therapies, and peppermint oil.
  • nutraceutical compositions such as supplements, probiotics, prebiotics, synbiotics, natural products, herbal therapies, and peppermint oil.
  • One or more non-behavioral therapies may further include nutritional therapies (e.g., enteral nutrition), acupuncture, mind-body interventions (e.g., relaxation, meditation, yoga), whole system medicine (e.g., Eastern Medicine, Ayurveda), and physical exercises.
  • One or more non-behavioral therapies may further include therapies utilizing a variety of medical devices, such as, but not limited to, wearable devices, ingestible devices, implanted devices, and/or biofeedback devices (e.g., for control of the autonomic nervous system, for control of the cardiovascular system, to facilitate digestion and bowel movement, for treating abdominal pain and other symptoms).
  • a patient suffering from a GI and/or inflammatory health condition may be treated using any combination of the above listed non- behavioral therapies.
  • the prescription digital therapeutics (PDT) systems and methods disclosed herein collect patient medication information, for example in the preassessment operation discussed above, via interactive lesson modules such as a pre-assessment module, via modules specifically related to medication, etc., and/or via user entry into a user profile.
  • the prescription digital therapeutics (PDT) systems and methods described herein may collect and offer recommendations regarding an amount and/or timing of dosage of particular medications. Such recommendations regarding amount and/or timing may be absolute and/or relative to other events and/or activities. For example, recommendations may comprise a particular schedule of dosage, e.g., a particular rate, timing (e.g., in a morning, afternoon, or evening), etc.
  • Timing may including timings and/or amounts relative to other activities, such as meal consumption, physical exercises, seasons, social gatherings, travel, work, etc. Such recommendations may be based on data provided by the patient, for example in daily symptom diary entries, via assessment modules, personal model creation modules, etc., such as those described in more detail below.
  • such recommendations are generated via use of one or more machine learning modules that receive, as input, data corresponding to patient symptom and/or habits, as tracked by various modules such as those described herein. In some embodiments, this information is used as feedback, to refine and dynamically update parameters of machine learning modules. In some embodiments, dosage recommendations provided via the approaches described herein are restricted to fall within a pre-defined range, for example as specified by a physician.
  • dosage recommendations provided by technologies (e.g., systems and methods) described herein comprise an identification of one or more specific symptoms, so as to provide recommendation to discuss particular symptoms with a medical professional, such as a physician and/or therapist (e.g., to discuss particular changes to medication regimens and/or types of medication, so as to best manage particular symptoms).
  • a medical professional such as a physician and/or therapist (e.g., to discuss particular changes to medication regimens and/or types of medication, so as to best manage particular symptoms).
  • the non-behavioral therapy components are related to therapies that have previously been administered to the patient.
  • the non- behavioral therapy components are related to therapies that are currently being administered to the patient.
  • the non-behavioral therapy components are related to therapies that will be and/or are recommended to be administered to the patient.
  • method flow proceeds to operation 212.
  • the patient profile and pre-assessment data and the patient condition data are processed to generate a personalized intervention regimen for the patient, wherein the personalized intervention regimen defines both behavioral therapy components and non-behavioral therapy components to be administered to the patient.
  • the personalized intervention regimen provides, through client devices, an array of empirically- supported intervention options or actions delivered via a modular and flexible approach, whereby modules of the regimen (a set of overarching principles and evidence-based interventions) can be adaptively provided based on patient states assessed in real-time or near real-time. This allows for individualized treatment planning.
  • guided behavioral therapy technologies as provided herein provide a user with a sequence of interactive lesson modules that the user accesses and interacts with via a graphical user interface (GUI) of a PDT system, which may include a web-based application accessible via a web-browser of a user personal computer (e.g., desktop, laptop, etc.), and/or a mobile application, running, at least in part, on and/or accessible via a user mobile computing device.
  • GUI graphical user interface
  • Each interactive lesson module may represent a guided lesson in a particular behavioral therapy skill and includes specific graphical content and/or graphical widgets designed to introduce a user to a particular behavioral therapy skill, such as keeping a symptom diary, managing symptoms, setting goals, identifying and understanding thoughts e.g., unhelpful and/or irrational thoughts), and the like.
  • a user completes various interactive lesson modules, they are introduced to, and learn to practice, a specific behavioral therapy skill.
  • interactive lesson modules are arranged in a particular sequence.
  • a PDT system in accordance with approaches described herein may include controls that encourage and/or require a user to progress through a particular sequence of lesson modules in a prescribed order.
  • the PDT system may restrict access by the user to certain lesson modules, occurring later in the sequence, until others have been completed first.
  • the order of modules of the intervention regimen provided can vary from patient to patient and/or vary based on other factors (e.g., due to refinement and training of models, as described in further detail below); however, in some embodiments, all patients will have access to and be offered all of the skill modules through PDT systems executing on their respective client devices.
  • the skills-based interventions rely on skill acquisition (initial phase of learning the new skill), then skill practice before proceeding to learn the subsequent new skill (e.g., in one’s natural home/social environment). Monitoring of task performance and practicing skills is described in further detail below.
  • the modules can allow users to develop and train core skills (e.g., 8 core skills, another suitable number of core skills, etc.) associated with understanding their disease, disorder, and/or condition, therapies available, brain-gut connections; relaxation skills; behavioral change, avoidance, and activation; problem solving and coping; pain management; cognitive flexibility; social problem solving and communication; and relapse prevention and skills maintenance.
  • core skills e.g., 8 core skills, another suitable number of core skills, etc.
  • sizes of lesson modules - for example, a number of screens a user cycles through, a number of graphical widgets they interact with, an estimated approximate time they are expected to spend with various lesson module(s), etc. - may be tailored to remain relatively small, so as to provide a user ‘bite-sized’ lessons that can and/or are designed to facilitate retention.
  • lesson modules may be designed such that they may be completed with no more than about twenty minutes of continuous user interaction.
  • lesson modules may be designed such that they may be completed with no more than about fifteen minutes of continuous user interaction.
  • lesson modules may be designed such that they may be completed with no more than about ten minutes of continuous user interaction.
  • Disease, condition, and/or syndrome-specific components include content addressing one or more of: an illness narrative, symptom management for pain and other symptoms, disease-specific psychoeducation, social skills training, and emphasis on GI and/or inflammatory health condition (e.g., IBS-related, IBD-related) cognitions, beliefs, and behaviors.
  • Intervention modules can further include general cognitive behavioral components shared across psychological conditions/disorders such as behavioral activation, attentional processes, relaxation, problem solving, cognitive reframing, and other areas.
  • generating a personalized intervention regimen can include defining a type, amount, and/or dosing schedule of a non-behavioral therapy to be administered to the patient in combination with the behavioral therapy components.
  • a dosing schedule for administration of a non-behavioral therapy may be defined relative to a schedule for administration of the behavioral therapy.
  • generating a personalized intervention regimen can include adjusting (e.g., decreasing, increasing, maintaining) an amount of the non-behavioral therapy treatment administered to the patient, for example, based upon the state of the patient’s health condition symptom severity, and/or correspondingly adjusting (e.g., decreasing, increasing, maintaining) an amount of a behavioral therapy treatment provided to the patient, thereby titrating relative treatment types provided to the patient based upon returned outputs of models associated with the methods described.
  • a treatment cocktail can include prescription digital therapeutic aspects (e.g. behavioral therapy components) as well as non-prescription digital therapeutic aspects (e.g. non-behavioral therapy components).
  • FIG. 3 A depicts a schematic of architecture 300 implemented for delivery of behavioral therapy intervention regimen components and/or modules, according to one or more embodiments.
  • architecture 300 includes introduction and education module 301, which in some embodiments, also includes symptom assessment module 302.
  • introduction and education module 301 is utilized to generate patient profile and pre-assessment data.
  • the patient profile and pre-assessment data is generated and/or obtained outside of the functioning of the introduction and education module 301.
  • architecture 300 further includes physical illness narrative module 304, which is utilized to generate patient illness narrative data, which in turn, may be utilized for personalization of an intervention regimen, as well as for constructing personal model 303.
  • the patient profile and pre-assessment data generated by introduction and education module 301, and the patient illness narrative data generated by physical illness narrative module 304 are processed through the PDT system to generate a personalized and adaptive intervention regimen for the patient, as will be discussed in additional detail below.
  • the personalized intervention regimen includes one or more additional interactive therapy modules, such as, but not limited to, relaxation module 306, behavioral change and avoidance module 308, problem solving and coping module 310, pain management module 312, cognitive restructuring and flexibility module 314, social problemsolving and communication module 316, relapse prevention and skills maintenance module 318, and adherence module 320.
  • additional interactive therapy modules such as, but not limited to, relaxation module 306, behavioral change and avoidance module 308, problem solving and coping module 310, pain management module 312, cognitive restructuring and flexibility module 314, social problemsolving and communication module 316, relapse prevention and skills maintenance module 318, and adherence module 320.
  • a symptom diary and meal tracking module 321, and a medication adherence module 323 are also provided.
  • method flow proceeds to operation 214.
  • the one or more behavioral therapy components are administered to the patient through the user interface of the prescription digital therapeutics (PDT) system according to the personalized intervention regimen generated for the patient.
  • PDT prescription digital therapeutics
  • modules are described in a particular order, it should be noted that the modules can be performed in any other suitable sequence, omit operations, and/or include additional operations (e.g., based on refinement and training of models described below, and/or based on other factors). Furthermore, aspects of the modules can overlap with each other in any suitable manner.
  • introduction and education module 301 focuses on education about the patient’s disease and symptoms (e.g., more common symptoms, less common symptoms, etc.).
  • an introduction and education module tailored for GI health conditions may provide information regarding methods of diagnosis, promote understanding of functional implications of symptoms in the context of brain-gut axis education (e.g., with effect to the brain’s role in gut motility, secretion, nutrient delivery, and microbial balance, and the gut’s role in neurotransmitter dynamics, stress and anxiety, mood, and behavior).
  • the introduction and education module is designed to create awareness about what matters to the patient (their reason for trying the program), introduce therapy concepts (e.g., related to CBT, related to other therapies), introduces skills that the user will build by interacting with the system, and assesses user’s level of commitment for change.
  • introduce therapy concepts e.g., related to CBT, related to other therapies
  • introduces skills that the user will build by interacting with the system and assesses user’s level of commitment for change.
  • an overview of this program links to the patient’ s specific psychological/disease management challenges.
  • the following points are emphasized: (1) the treatment is modular/flexible in nature and tailored for patient’s needs (2) the patient will learn skills, that if practiced, will help them manage their symptoms (e.g., with highlighting of red flag symptoms), improve their quality of life, and lessen the toll that the patient’s health conditions take on the patient.
  • Introduction and education module 301 thus can guide the patient to explore the influence that moods, attitudes, beliefs and behavior exert on health and the impact of illness.
  • Introduction and education module 301 can further function to provide tools for education, persuasion (e.g., regarding effectiveness of program completion), personalization, motivation enhancement, setting expectations, eliciting commitment by users, and establishing a relationship between users and the system (e.g., in lieu of a human coach, with supplementation of therapy by a human coach, etc.).
  • Delivery methods for introduction and education module 301 can include one or more of: graphics/animations, metaphorical digital content, interactive exercises provided in a PDT system environment, and a clinical vignette simulating patientprovider interactions.
  • introduction and education module 301 may include a variety of individual sections designed to lay a foundation for progression through later modules. While the sections described below are described in a particular order for illustrative purposes, variations of introduction and education module 301 can additionally or alternatively be arranged in another suitable order, omit sections as desired, and/or include additional sections as desired.
  • FIG. 3B depicts examples of individual sections that may make up an introduction and education module 301 of an intervention regimen, according to one or more embodiments.
  • introduction and education module 301 includes a First Section 322 configured to welcome the patient and introduce the patient to goals of the intervention regimen delivered through the online system and client device.
  • the First Section 322 is delivered by the system in an interactive format (e.g., with video and text content) that creates a feedback loop with users and processes user responses to tailor subsequent module delivery and content, in order to increase engagement.
  • goals can be set in coordination with user desires, with establishment of collaborative empirence. Goals can be specific, in terms of detailed planning of what users will do, including frequency, intensity, duration, and context (e.g., where, when, how, with whom, etc.) of the goal(s).
  • introduction and education module 301 can determine topics having greater relevance to the user’s current issues (e.g., in relation to comorbid conditions, such as anxiety and depression, in relation to health condition subtypes, such as subtypes of IBS, etc.).
  • the First Section 322 can include a description of how the program will involve regular practice (e.g., daily, every two days, every 3 days, etc.) of skills (e.g., core skills described above and below), with a guideline for program length (e.g., 8 weeks, less than 8 weeks, more than 8 weeks), and methods of identifying personal progress (e.g., feeling better with mastery of a subset of skills).
  • introduction and education module 301 includes a Second Section 324 configured to allow the patient to submit information, through a user interface of the PDT system, regarding personal aspects of his/her health condition as an initial physical illness narrative, along with video content to which the patient can compare his/her experiences.
  • Second Section 324 has goals of facilitating emotional awareness, establishing a physical illness narrative that can be revisited as the user gains mastery of skills, and helping the user to articulate and track his/her experiences.
  • introduction and education module 301 includes a Third Section 326 configured for personalization of subsequent portions of the intervention regimen to the patient, by allowing the patient to indicate, through a user interface of the PDT system, which symptoms (e.g., fatigue, pain, nausea, vomiting, lack of appetite, weight loss, skin problems, eye problems, joint problems, diarrhea, bowel movement issues, cramping pains, bloody stool, medication side effects, other symptoms, etc.) are most bothersome.
  • Third Section 326 can also include architecture for mapping the user’s symptoms and health condition-induced factors to various impacts associated with the user’s values.
  • one or more of the mappings can be created, such as, but not limited to: symptoms associated with diarrhea, abdominal pain, urgency, tenesmus, nocturnal bowel movements, rectal bleeding, physical fatigue, and other physical symptoms with mappings to aspects of life (e.g., relationships, work, school, hobbies, daily activities, etc.) that have been affected by such symptoms and the reason such aspects have been affected; medication side effects with mappings to aspects of life (e.g., relationships, work, school, hobbies, daily activities, etc.) that have been affected by such symptoms and the reason such aspects have been affected; social/relationship issues (e.g., stress on loved ones, impacts on friendships, etc.) with mappings to behaviors (e.g., relationships, work, school, hobbies, daily activities, etc.) that have been affected by such symptoms and the reason such aspects have been affected; and behavioral, mental, and emotional factors (e.g., exhaustion, lack of control, inability to perform activities, additional help needed for tasks, limitations in diet, limitations in travel
  • Third Section 326 has goals for providing education about health condition symptoms and psychological consequences (e.g., behavioral psychological consequences), as well as generating data for future personalization of the intervention regimen.
  • introduction and education module 301 includes a Fourth Section 328 configured for personalization and values identification, with tools for allowing the user to provide data related to positive and negative changes in his/her life that are attributed to having the health condition, in relation to changes in relationships, levels of embarrassment, curiosity, being understood, stress to self and loved ones, confidence, energy levels, senses of lack of control, worry (e.g., about health issues experienced outside of a comfortable environment, about disease progression, and symptoms, about medication effects, about ability to conduct daily activities, about dietary constraints, about travel, etc.), and other aspects.
  • worry e.g., about health issues experienced outside of a comfortable environment, about disease progression, and symptoms, about medication effects, about ability to conduct daily activities, about dietary constraints, about travel, etc.
  • Fourth Section 328 can also revisit aspects of the user’s initial physical illness narrative, with ranking of: symptoms (e.g., physical fatigue, abdominal pain, diarrhea, urgency, tenesmus, bowel movements at night, rectal bleeding, medication side effects, etc.); social/interpersonal factors (e.g., changes to relationships, embarrassment, stress to loved ones, dealing with constant questions about illness, not being understood, etc.); emotional factors (e.g., lack of confidence, mental exhaustion, lack of control, etc.); cognitive factors (e.g., worry about health issues outside of places of comfort, worry about disease progression, catastrophizing, depression, anxiety, other comorbid conditions, etc.); and behavioral factors (e.g., not being able to conduct daily activities, needing to prepare for accidents, dietary restrictions, travel restrictions, etc.).
  • symptoms e.g., physical fatigue, abdominal pain, diarrhea, urgency, tenesmus, bowel movements at night, rectal bleeding, medication side effects, etc.
  • social/interpersonal factors e
  • introduction and education module 301 includes a Fifth Section 330 configured for allowing further customization, by providing the patient with interactive elements that allow the patient to prioritize the order in which content associated with interventions is received.
  • introduction and education module 301 also includes a Sixth Section 332 configured for introducing subsequent portions/modules of the intervention according to user preferences indicated from outputs of the Fifth Section 330, where the goals of Sixth Section 332 include promotion of treatment credibility (e.g., through presentation of video content by patients having experiences similar to those of the user(s)).
  • introduction and education module 301 includes a Seventh Section 334 configured for delivery of content for educating the patient about their condition, where the content includes an animated element and audio format content configured to actively interact with the user.
  • the interactive elements function to gauge how well the patient understands the content provided, and to provide additional content to engage and inform the patient depending upon responses of the patient.
  • the Seventh Section 334 has goals of shaping knowledge of symptoms and treatment components of the intervention regimen and enhancing motivation.
  • Seventh Section 334 can teach users of the system regarding the brain’s role in proper gut functioning, and the connection between the mind and the gut. As such, the user can be primed to gain skills related to affecting gut functioning and regulation by changing behaviors, attentional biases, and automatic thought patterns. Seventh Section 334 can further gage internalization and understanding of the user, with provision of further content in this section and/or the eighth section to promote further understanding.
  • introduction and education module 301 includes an Eighth Section 336 configured for delivery of content for educating the patient in a manner personalized to the patient, where the content includes video and audio format content configured to actively interact with the user, in order to aid the user in understanding influences on the perception of symptoms, based on symptom severity (e.g., related to a threshold level of severity of symptoms, related to fight-or-flight responses, etc.).
  • Eighth Section 336 also provides interactive exercises for learning about physiological-cognitive pathways for perceiving and responding to experienced symptoms and implements architecture for assessing stress and other disease aspects, with implementation of therapeutic techniques for changing reactivity of the brain, thereby decreasing symptom severity.
  • introduction and education module 301 includes a Ninth Section 338 configured for eliciting commitment from the patient, in relation to different set goals of the patient.
  • the digital content of Ninth Section 338 includes interactive elements for creating a reminder system (according to personalized user preferences and formats for receiving reminders), and interactive elements for setting goals to improve one or more aspects of dealing with the patient’s health condition (e.g., with a menu of choices as well as a field for custom user inputs and a field for prompting the user to confirm chosen goals, where example choices can include repeating of tasks, reviewing content, reflecting, identifying entities for social accountability, relocation of application icons on a home screen of a device in a manner that promotes regular use, identifying factors that may obstruct progress, etc.), where the interactive elements allow the patient to confirm when (e.g., specific times), how often, and where the patient will perform activities to meet such goals.
  • Ninth Section 338 includes a brief introduction to subsequent modules of the intervention regimen that are customized to the patient.
  • Ninth Section 338 has goals including setting of expectations, promoting therapeutic persuasiveness, eliciting commitment, increasing user engagement, providing reminders, providing instruction for performing behaviors (e.g., SMART goals).
  • introduction and education module 301 can additionally or alternatively be arranged in another suitable order, omit sections as desired, and/or include additional sections as desired.
  • the term “physical illness narrative,” “personal illness narrative,” and/or “patient illness narrative” may include a narrative expressed by a patient regarding the patient’s personal experiences with a disease, disorder, and/or condition.
  • An illness narrative is typically a narrative solicited from a patient, which enables a healthcare practitioner to build a more complete picture of the patient’s past and present health state in the context of the patient’s life, while providing the patient with an opportunity for selfreflection and validation.
  • physical illness narrative module 304 provides a form of validation (being heard), highlights cognitive distortions/attentional biases and other clinically relevant processes to address, as well as begins the work of emotional exposure. It also provides a point of reference for reflection throughout and at the end of the program. Physical illness narrative module 304 promotes formation of a “personal disease model,” or “personal model” for users, such that they can identify patterns and/or cycles in their disease expression and/or progression, in relation to biology, behaviors, environment, stressors, emotions, and thoughts.
  • the term “personal model,” and/or “personal disease model” may include a construction built based on patient input, which enables the patient to identify stressors, counter-productive behaviors, unhelpful thoughts, and negative emotions as associated with the patient’s disease, disorder, and/or condition.
  • a personal model may be utilized to help a patient identify such links, and to consider possible changes in their behavior that could be implemented to address their symptoms.
  • second patient response data representing the patient’s responses to content provided to the patient through the second interactive therapy module is obtained, for example, through the user interface of the PDT system, or from a variety of patient devices, such as, but not limited to, sensors and/or biometric devices.
  • the PDT system then processes the second patient response data to generate physical illness narrative data, which can then be used for a variety of purposes.
  • the patient illness narrative data can be utilized to personalize an intervention regimen for the patient, as will be discussed in additional detail below.
  • the patient illness narrative data generated by physical illness narrative module 304 can also be utilized as the basis for formation of a personal model, such as personal model 303 of FIG. 3 A, which can then be graphically represented to the user to aid in progression through the intervention regimen.
  • key functions of physical illness narrative module 304 can include creation of a patient’s personal model 303, validation of a patient’s experience, enhancement of self-understanding and illness comprehension, setting the stage for application of behavioral therapy skills to accept uncontrollable elements of physical illness and/or or increase proactivity to address controllable elements of physical illness, and generation of interest for patient engagement.
  • physical illness narrative module 304 introduces a patient to a process for creating a personal model 303, for example so as to orient them and provide content designed to offer helpful motivation.
  • graphical content representing educational material is displayed to a patient, for example to introduce them to concept of vicious cycles, and explain how symptoms, stress, and pain can create a feedback loop.
  • graphical content corresponding to shared patient experiences and/or testimonials is displayed.
  • viewing shared experiences from other patients may help prime a patient to be receptive to therapy, provide motivation, and foster a particular sense of therapy.
  • such content can serve to reinforce skills that lesson modules present to a patient, by allowing the patient to hear benefits of various lessons and/or skill practice from real patients.
  • testimonial content can comprise stories from patients describing their experiences living with a particular health condition and which behavioral therapy skills and/or lesson they found particularly helpful.
  • patients providing videos may be loosely coached, e.g., to structure, direct, etc. their stories in a particular way, while still allowing them to provide authentic, ‘from the heart’ descriptions of their experiences. Additionally or alternatively, among other things, viewing relatable experiences from real patients (e.g., and not actors) can provide a patient with a helpful sense of not being alone in their experiences.
  • a patient may be prompted to read about another patient’s experiences with their condition and guided behavioral therapy approaches such as those described herein.
  • a patient may view exemplary personal models created by and shared by others.
  • screens comprising graphical content providing helpful encouragement are displayed within a GUI of the PDT system.
  • Other lesson modules for example any lesson modules described herein and/or additional lesson modules, providing for development of other behavioral therapy skills provided via the technologies described herein may also include content comprising patient experiences and/or testimonials.
  • FIG. 4 depicts an example of formation of a personal disease model, according to one or more embodiments.
  • physical illness narrative module 304 can receive patient report data (or other data) regarding the patient’s illness history (e.g., painful experiences in a clinical setting, such as with a clinician or hospital environment), thoughts (e.g., thoughts of guilt or responsibility for condition and behaviors, etc.), emotions (e.g., in relation to helplessness, feeling worthless, in relation to embarrassment, etc.), in order to address cognitive distortions for emotional exposure throughout subsequent interactions with the system.
  • patient report data or other data regarding the patient’s illness history (e.g., painful experiences in a clinical setting, such as with a clinician or hospital environment), thoughts (e.g., thoughts of guilt or responsibility for condition and behaviors, etc.), emotions (e.g., in relation to helplessness, feeling worthless, in relation to embarrassment, etc.), in order to address cognitive distortions for emotional exposure throughout subsequent interactions with the system.
  • physical illness narrative module 304 is used to implement, via a GUI of the PDT system, a structured process for conveniently soliciting patient input of specific counter-productive behaviors, unhelpful thoughts, and negative emotions that they identify, e.g., in their life and/or as associated with their particular condition for use in creating a patient’s own personal model 303.
  • physical illness narrative module 304 and/or other related modules can include architecture for prompting the patient to provide data and/or automatically receiving data (e.g., through API access of health monitoring systems, through receiving of sensor signals of devices of the patient, etc.) pertaining to one or more of: biological aspects (e.g., physiological symptoms); behavioral aspects (e.g., in relation to skipping meals, in relation to exercise avoidance, in relation to social event behavior, in relation to locating restrooms, in relation to straining, in relation to checking stools, in relation to other aspects); environmental aspects (e.g., in relation to stress, in relation to temperatures, in relation to diet, etc.); emotional aspects; and thoughts linked to behaviors (e.g., regarding anxiety around diet, regarding to anxiety around performing various activities, etc.),
  • biological aspects e.g., physiological symptoms
  • behavioral aspects e.g., in relation to skipping meals, in relation to exercise avoidance, in relation to social event behavior, in relation to locating restrooms, in relation to straining, in relation to checking stools, in relation
  • physical illness narrative module 304 can include architecture for prompting the patient to provide data and/or automatically receiving data (e.g., through API access of health monitoring systems, through receiving of sensor signals of devices of the patient, etc.) pertaining to one or more aspects such as, but not limited to: pain symptoms, stress symptoms, diarrhea and stool aspects, accidents incurred, constipation and stool aspects, amount of time straining, meals eaten/skipped and times of meals, behaviors and behavioral changes, and other aspects.
  • physical illness narrative module 304 may automatically return an analysis summarizing the personal model 303 of the patient (e.g., in a visual format, etc.). Such personalization thus promotes interruption of vicious cycles for patients.
  • the method 200A can include returning a mapping with a network of flows between a set of behaviors specific to the patient, a set of thought patterns specific to the patient, a set of physiological symptoms specific to the patient, a set of emotions specific to the patient, and environmental triggers specific to the patient, where returned outputs of models described can be configured to disrupt flows of the network contributing to deterioration of symptoms of the patient.
  • a personal model is constructed as a graphical representation, which comprises text corresponding to patient-selected counter-productive behavior(s), unhelpful thought(s), and negative emotion(s), superimposed on a flow diagram illustrating links between each other.
  • a personal model graphical representation comprises text corresponding to causes and/or stressors of symptoms. Examples of personal model graphical representations will be provided below in the discussion of the PDT user interface.
  • generation of a visual or graphical representation of a personal model 303 may include, retrieving, by the illness narrative module 304, stored information previously input by a patient.
  • a patient may have previously provided input identifying causes and/or stressors that impact their particular condition.
  • a patient provides input corresponding to causes and/or stressors associated with their particular condition via the physical illness narrative module 304.
  • a graphical representation of a partially completed personal model 303 is rendered, showing the patient identified causes and stressors superimposed on a flow diagram, with portions allocated for graphical representations of additional information such as counterproductive behaviors, unhelpful thoughts, and negative emotions, to be displayed.
  • the physical illness narrative module 304 includes graphical content prompting a patient to review their personal model 303.
  • a series of questions e.g., from a predefined list of questions, e.g., based on a therapeutic protocol
  • graphical content including passages of rendered text, mimicking conversation with a therapist can be displayed.
  • encouraging graphical content is displayed, and the patient is returned to a home screen.
  • delivery methods for the physical illness narrative module 304 can include audio format content and/or textual content for guiding exercises.
  • physical illness narrative module 304 may be a subcomponent of multiple modules, such that its content can be revisited. For instance, upon development of core skills associated with the modules, the system can trigger revisitation of aspects of physical illness narrative module 304 within the PDT system, such that patients can solidify new skills, reflect on their initial versions of their physical illness narrative and what has changed, generalize skills, maintain skills, and implement cognitive flexibility.
  • a relaxation module 306 provides a patient with understanding of what physiological stress feels like (e.g., with education on fight or flight responses) and recognition of the importance of actively optimizing their stress response, particularly because of the connection between stress reactivity, stress hormones and autonomic arousal, and flares in symptoms.
  • Relaxation module 306 informs the patient that (1) stress is a natural reaction and it causes its own physical symptoms (2) the brain does not differentiate between an event that is actually happening to us and an event that we only think is happening, and (3) the connection between stress and flares and symptoms.
  • relaxation module 306 provides the patient with a rationale for each type of relaxation and how it is tailored for their specific stress symptoms, and provides guided relaxation exercises (e.g., through an application associated with the PDT system executing at the client device).
  • Relaxation module 306 promotes mastery of at least one relaxation technique.
  • Key functions of relaxation module 306 can include decreasing physiological reactivity associated with stress, worry, anxiety, and pain, activation (for depression symptoms), and stress management.
  • Delivery methods for relaxation module 306 can include audio format and/or visual content for guiding exercises associated with targeted muscle groups for progressive muscle relaxation, video-guided demonstration of diaphragmatic breathing, and haptic feedback for exercise guidance.
  • relaxation module 306 can include video format content that introduces the general concept of relaxation; educates the patient on the applicability of stress-reduction exercises to specific health conditions, with active text boxes that promote user engagement and personalization of the module to the patient’s specific symptoms and contexts; addresses common doubts or concerns about relaxation; promotes a guided breathing exercise with a diaphragmatic breathing demonstration and corresponding animated graphic; promotes guided exercises for muscle relaxation using progressive muscle relaxation (PMR) techniques using graphical animations (e.g., of targeted muscle groups); provides information on how relaxation practices can be used (e.g., for abdominal pain, for anxiety, for other stressors, etc.), and encourages practice of exercises by including active interactive elements that the patient can use for scheduling and/or accountability in practicing exercises.
  • behavior change and avoidance module 308 provides content covering the importance of activation and approaching avoided situations/experiences in breaking the cycle of persistent pain symptoms and depressive and/or anxious mood.
  • Specific action plans are developed for decreasing avoidance behavior.
  • Key functions of this module can include linking behaviors and mood, mood monitoring (e.g. selfmonitoring), activity scheduling, identifying and counteracting avoidance behavior, action planning, activity scheduling, creating anxiety hierarchies, self-monitoring, behavioral experiments, exposure (e.g., imaginal exposure, actual exposure to counteract anxiety) and systematic desensitization for anxiety, coping performance, confidence building, and routine building.
  • Delivery methods for behavior change and avoidance module 308 can include use of automated tailoring for choosing topics that have greater relevance to a patient's current problems (e.g., if a patient reports anxiety, information about physiological responses of anxiety and their relationship with thoughts and behaviors would be more appropriate than information about the physiological symptoms of depression or generic stress).
  • problem solving and coping module 310 provides content covering how to differentiate controllable vs. uncontrollable stressors, problem-focused coping (e.g., with problem identification, solution brainstorming, evaluation of solution options, etc.) vs. emotion-focused coping (e.g., with grounding exercises), as well as types of adaptive and maladaptive coping. Mood/anxiety/stress may be managed/ameliorated by using externally-focused coping to distressing and modifiable conditions and internally-focused coping to adjust one’s expectations and interpretations for unmodifiable conditions.
  • problem solving and coping module 310 can include architecture and instructions for promoting practicing of problem solving and coping methods by the patient, such that the patient is better able to handle stronger symptoms (and milder symptoms).
  • Delivery methods for problem solving and coping module 310 can include digital content with explanations and testimonials of other patients and their uses of problem solving skills, peer support groups facilitated by the PDT system, and other delivery methods. Pain Management Module 312
  • pain management module 312 focuses on awareness of the pain experience, discusses how pain influences mood and vice versa, promotes recognition of certain behaviors (e.g., overactivity, avoidance) and automatic thoughts that may influence pain as well as how to feel more in control of pain by also improving physical and role functioning though increasing adaptive behaviors/coping (attention) and decreasing avoidance/maladaptive behaviors.
  • Key functions of pain management module 312 can include behavioral experimentation, behavior substitution, acceptance of pain, and selfmonitoring, with one or more disease-or-syndrome-specific targets.
  • pain management module 312 can include architecture and content for educating patients regarding re-directing attention away from pain symptoms by focusing on parts of the body that are not in pain, and other methods.
  • the system can include a processor with instructions stored in non-transitory media that when executed, perform operations for identifying when a patient is in a state of pain, and triggering a response (e.g., verbal cues and instructions to modify attention and/or engage in various pain observation exercises, a change in the environment of the patient, by playing music, by activating a display and providing video or image content, by providing haptic stimulation to the patient, etc.).
  • a processor with instructions stored in non-transitory media that when executed, perform operations for identifying when a patient is in a state of pain, and triggering a response (e.g., verbal cues and instructions to modify attention and/or engage in various pain observation exercises, a change in the environment of the patient, by playing music, by activating a display and providing video or image content, by providing haptic stimulation to the patient, etc.).
  • a response e.g., verbal cues and instructions to modify attention and/or engage in various pain observation exercises, a change in the
  • delivery methods for pain management module 312 can include audio format content and/or textual content for managing pain (e.g., with music, exercise, etc.) and/or for promoting attention restructuring.
  • FIG. 3C depicts examples of individual sections that may make up a pain management module of an intervention regimen, according to one or more embodiments.
  • pain management module 312 can include a First Section 340 that includes content focused on common types of pain (e.g., abdominal pain) associated with the patient’s health condition.
  • pain management module 312 can include a Second Section 342 focusing on facts about chronic pain associated with the patient’s health condition, in relation to constant pain, flare ups of pain, pain signals for people with health conditions vs. without health conditions, factors affecting pain strength, and other factors. Second Section 342 can also include image and video content (e.g., including testimonials of patients similar to the user) and other interactive exercises. [ 0237 ] In one embodiment, pain management module 312 can include a Third Section 344 describing differences between acute pain and chronic pain associated with health conditions, and therapies associated with each type of pain.
  • pain management module 312 can include a Fourth Section 346 focused on pain volume attributed to specific nerves of the brain, with interactive exercises and content for re-training the brain to adjust pain volume (i.e., pain modulation).
  • pain management module 312 can include a Fifth Section 348 focusing on factors that affect pain intensity/perceived pain intensity (e.g., loss of sleep, tense muscles, anxiety, worry, etc.) and methods for modulating pain intensity and duration (e.g., relaxation, distraction, positivity, exercise, medicine, etc.).
  • factors that affect pain intensity/perceived pain intensity e.g., loss of sleep, tense muscles, anxiety, worry, etc.
  • methods for modulating pain intensity and duration e.g., relaxation, distraction, positivity, exercise, medicine, etc.
  • pain management module 312 can include a Sixth Section 350 describing the importance of relaxation in modulating pain volume and creation of a pain management plan.
  • pain management module 312 can include a Seventh Section 352 focused on the effects of pain on negative emotions, with architecture for including customized content from the patient’s illness narrative (associated with other modules), in a textual, audio, and/or visual format, and allowing the patient to update his/her illness narrative.
  • pain management module 312 can include an Eighth Section 354 focused on development of automatic habitual thinking patterns to interrupt and break these negative cycles.
  • pain management module 312 can include a Ninth Section 356 with architecture for presenting a patient testimonial regarding a personal experience of catastrophizing thoughts and the effects on worsening mood, pain, and perpetuation of biased attentional processing.
  • pain management module 312 can include a Tenth Section 358 focused on promoting a healthy lifestyle to protect the body against stress, pain flares, and other health condition symptoms.
  • pain management module 312 can include an Eleventh Section 360, which provides architecture for helping the patient establish goals in various activities in his/her daily life (e.g., school, friendship, sports, etc.), as they relate to pain management.
  • pain management module 312 can include a Twelfth Section 362 focused on activity pacing to prevent increases in pain, with interactive content (e.g., derived from patient testimonials, etc.).
  • pain management module 312 can include a Thirteenth Section 364 focused on providing examples of activity pacing (e.g., taking breaks during physical exercise, setting limits in relation to pain thresholds, etc.), with interactive modules for setting goals specific to activities that the patient values and/or enjoys.
  • activity pacing e.g., taking breaks during physical exercise, setting limits in relation to pain thresholds, etc.
  • pain management module 312 can also include a Fourteenth Section 366 focused on helping the patient to generate a pain management plan with respect to relaxation skills gained (e.g., diaphragmatic breathing, progressive muscle relaxation, etc.), cognitive flexibility skills (e.g., catastrophizing avoidance, etc.), eating and drinking habits (e.g., with respect to regular meals with respect to caffeine limitation, etc.), with respect to activity performing, and with respect to activity pacing.
  • relaxation skills gained e.g., diaphragmatic breathing, progressive muscle relaxation, etc.
  • cognitive flexibility skills e.g., catastrophizing avoidance, etc.
  • eating and drinking habits e.g., with respect to regular meals with respect to caffeine limitation, etc.
  • cognitive restructuring and flexibility module 314 targets one’s interpretations of events/experiences (e.g., how core thoughts influence our feelings and behavior).
  • Cognitive restructuring and flexibility module 314 emphasizes connections between thoughts and physical sensations due to a variety of symptoms.
  • the aim of cognitive restructuring and flexibility module 314 is to teach patients how to identify unhelpful automatic thinking patterns and develop a new pattern of realistic, balanced, and flexible thinking.
  • a health behavior change is targeted in the area of sleep and worry by providing education about worry and how it might interfere with sleep.
  • Strategies to manage worry before bedtime e.g., use a relaxation practice are provided as well as basic sleep hygiene.
  • Cognitive restructuring and flexibility module 314 can include resetting of cognitive distortions (e.g., about self, others, and the world), identification of unhelpful thoughts, challenging of automatic thoughts, creating more balanced thoughts, reattribution, appraisals of moods, and improving cognitive flexibility.
  • Delivery methods for cognitive restructuring and flexibility module 314 can include a tool providing digital content for reassembling a traditional thought record in which patients enter an unhelpful automatic thought and select from a list of negative thoughts that best matched. After selecting from a list of most common automatic thoughts, the tool can generate a list of possible challenge/altemative thoughts. The patient can then input their own personalized challenge/altemative thought.
  • social problem solving and communication module 316 provides content promoting effective social behaviors in the context of a variety of health conditions.
  • Social problem solving and communication module 316 can provide tools for one or more of: action planning, social skills training, social support, exposure, and activation, with identification of oneself as a role model, and presentation of information regarding vicarious consequences.
  • social problem solving and communication module 316 is intended to assist interactions between patients and their social environment in the context of their health condition(s), and how to communicate effectively about the medical condition/disease.
  • Some examples include requesting support in college (disability services office) or at work; informing a patient that his/her behavior may be an example to others; coping with sense of urgency to use bathroom; and problem solving about bathroom/bowel related challenges and worries.
  • Key functions of social problem solving and communication module 316 can include activation and action planning, problem solving by analysis of factors influencing the behavior and generating strategies to overcome barriers, demonstrating one’s ability to cope, decreasing avoidance behaviors, ensuring practice of new coping skills, when symptoms are more severe (e.g., with behavioral rehearsal, etc.).
  • Delivery methods for social problem solving and communication module 316 can include digital content with testimonials of other patients and their uses of problem solving, peer support groups facilitated by the PDT system, and other delivery methods.
  • social problem solving and communication module 316 can include architecture for triggering actions based on detected changes in symptoms. For instance, in one example, social problem solving and communication module 316 can process data generated by interactions between the user and the system (e.g., with sensor-based monitoring of symptom progression, with user input-based monitoring of symptom progression, etc.), and based upon the data, generate control instructions for recommended actions that would improve social problem solving ability.
  • Examples of recommended actions can include one or more of: guidance for conducting a conversation regarding symptoms (e.g., example language for communicating pain, defecation, or other-related symptoms to an entity, so that the user can experience relief, etc.); triggering automatic communications between the patient and an entity (e.g., automatically sending a private message to a teacher so that the teacher can excuse the patient to manage pain-related, defecation-related, and/or other symptoms); and performing other suitable actions.
  • symptoms e.g., example language for communicating pain, defecation, or other-related symptoms to an entity, so that the user can experience relief, etc.
  • triggering automatic communications between the patient and an entity e.g., automatically sending a private message to a teacher so that the teacher can excuse the patient to manage pain-related, defecation-related, and/or other symptoms
  • performing other suitable actions e.g., guidance for conducting a conversation regarding symptoms (e.g., example language for communicating pain, defecation, or other-related
  • relapse prevention and skills maintenance module 318 encourages maintenance/continuation of treatment gains, and reinforces positive changes in thoughts and behavior that were accomplished during the active treatment time.
  • Key functions of relapse prevention and skills maintenance module 318 can include skills generalization, skills maintenance, and adaptive monitoring to refresh skills learned. Additionally, relapse prevention and skills maintenance module 318 can perform one or more of: informing patients of signs of relapse into old patterns, development of specific proactive coping tools for future challenges, encouragement of proactive coping for mood regulation, explaining perseverance, education regarding sequential coping strategies, and identification of skill s/techniques that were most effective for the user, based on analysis of user outcomes. Delivery methods for relapse prevention and skills maintenance module 318 can include digital content and/or notifications related to monitored states of the patient (e.g., related to relapse) as described in further detail below.
  • an intervention regimen may include a symptom diary module that introduces and familiarizes a patient with techniques for tracking their GI and/or inflammatory health condition symptoms.
  • technologies described herein provide a convenient interface that facilitates patient tracking and/or monitoring of their GI and/or inflammatory health condition symptoms on a regular basis.
  • a patient may use utilize the PDT system disclosed herein to rate pain and stress on a scale, provide ratings characterizing constipation and diarrhea, and provide information characterizing their daily meals and activity routines.
  • symptom diary and meal tracking module 321 may include features providing options for setting goals, for example, goals pertaining to a regular timing and/or type of food (e.g., regular consumption of meals, e.g., of a particular and/or consistent size and/or at a particular and/or consistent time) and/or activity (e.g., physical exercise, meditation, breathing and/or relaxation exercises, reflection exercise, e.g., including skills introduced via lesson modules and/or practicable via interaction with one or more other practice modules, such as keeping a regular symptom diary, etc.).
  • goals pertaining to a regular timing and/or type of food e.g., regular consumption of meals, e.g., of a particular and/or consistent size and/or at a particular and/or consistent time
  • activity e.g., physical exercise, meditation, breathing and/or relaxation exercises, reflection exercise, e.g., including skills introduced via lesson modules and/or practicable via interaction with one or more other practice modules, such as keeping a regular symptom diary,
  • daily meals may be characterized via use of a streamlined meal-tracking interface.
  • conventional meal tracking tools typically allow users to input a wide array of information about their particular meals, including detailed information characterizing types of food and/or food content.
  • approaches described herein provide a streamlined meal tracking interface that expressly limits a range of user input and avoids allowing a user to input detailed information regarding meal content.
  • information may be relevant to, for example, identifying allergies, certain food triggers, and ensuring adherence to specific diets, in some embodiments it may not necessarily be of utmost importance for GI and/or inflammatory health condition symptom tracking.
  • less finely grained information such as a broad categorization of meal size (e.g., small, medium, large, as well as an option for whether or not a particular meal was consumed at all), and a particular time at which the meal was consumed can provide sufficient information for tracking meal habits and/or evaluating GI and/or inflammatory health condition symptoms, flare ups, etc. in context of meal habits and/or identifying patterns.
  • this approach may facilitate user input of meal information, and can improve adherence to meal-tracking.
  • this approach encompasses recognition that patients suffering from certain GI and/or inflammatory health conditions and associated mental health conditions, such anxiety and/or depression, can suffer from unhelpful thoughts and compulsive behavior, which conventional, overly complex meal-trackers may exacerbate. Accordingly, among other things, by providing, in some embodiments, a streamlined meal tracking approach, technologies described herein can address unique challenges associated with a particular patient population.
  • a meal tracking process may provide for display of a streamlined meal tracking interface, that allows for limited user input for each of a limited set of daily meals, such as breakfast, lunch, and dinner.
  • a user may be provided with options for input including, for example, an identification of a meal size on a meal size scale, and a meal time.
  • a meal size scale includes an option for indicating that a particular meal was not consumed at all.
  • a meal size scale includes four or fewer values - for example, values indicating small, medium, large, along with a value indicating that a meal was not consumed at all.
  • a streamlined meal tracking interface can be used to solicit and receive user input corresponding to an indication of a meal size and user input corresponding to a meal time.
  • a streamlined GUI does not provide options for user input of food type, content, or other identification of food.
  • no other meal-related input is solicited.
  • once meal tracking data is received it may be stored and/or provided for display and/or further processing. For example, user inputs may be stored, along with other data, in a daily symptom record populated via a symptom diary.
  • the present disclosure provides methods for facilitating meal tracking by a subject suffering from a GI and/or inflammatory health condition, for example including steps of: causing, by a processor of a computing device, display of a streamlined meal-tracking user interface comprising one or more meal tracking features, wherein, for each of one or more particular daily meals, the meal tracking features provide for user input of meal data, including one or more of: binary user input indicating consumption of the particular meal of a day, a size of the particular meal [e.g., via selection of a value on a scale comprising a finite, ordered list of members (e.g., small, medium, and large)], and a time at which the particular meal was consumed.
  • the meal data input by the user via the meal tracking features is received by the processor stored for display and/or further processing, by the processor, the meal input data.
  • the prescription digital therapeutics (PDT) system described herein can include mechanisms to facilitate a patient’s adherence to one or more particular non-behavioral therapies, such as dosing regimens of pharmaceutical compositions, nutraceutical compositions, and/or therapies involving use of medical devices.
  • various lesson modules and/or practice modules, as described herein may include features that allow a patient to track their adherence to medication.
  • medication adherence module 323 may include features that provide for patient input e.g., via one or more graphical widgets) of when and what medication the patient took. Tracking features such as these may serve as a helpful reminder to the patient to actually take their medication.
  • medication adherence module 323 may provide features for setting goals pertaining to adherence to medication.
  • goals pertaining to medication adherence may include goals relating to a timing and/or particular type of medication, such as adherence to a regular schedule and/or timing of a particular medication.
  • medication adherence goals may include timing of a particular medication in relation to symptoms (e.g, of a user physiological condition) and/or other events, such as relative to meal consumption, physical exercises, seasons, social gatherings, travel, work, etc.
  • guided behavioral therapy technologies described herein may provide alerts, such as in-app pop up messages, push notifications, digital calendar integration, email/text message reminders, and the like, that facilitate medication adherence. Such notifications may include, for example, reminders to take particular medications.
  • the PDT systems and methods as described herein may provide for communication between a patient and one or more external medication tracking devices, as will be discussed in additional detail below.
  • guided behavioral therapy technologies described herein may also provide content (e.g, graphical content, e.g., presented within a GUI, such as those described herein) that explains and/or educates a user about one or more particular medications that they are taking.
  • medication adherence module 323 may be a standalone module, or may be included in the PDT system as part of another module, such a daily symptom diary and meal tracking module 321 discussed above.
  • exercises associated with the intervention regimen can include one or more of: a card sorting task to identify a patient’s reinforcers/motivators (e.g., in relation to social reinforcers, reminders, accountability, gaming/competition, responsiveness to quantitative summary feedback, monetary incentives, altruism, learning, elimination of symptoms, etc.); computerized performance tasks (e.g., delayed discounting) to measure/identify salient reinforcers and/or learning style; and performance tasks (e.g., validated distress tolerance computer tasks, tasks associated with mimicked social interactions, etc.) to measure emotional awareness and ability to tolerate various types of distress (psychological, physical, etc.).
  • a card sorting task to identify a patient’s reinforcers/motivators (e.g., in relation to social reinforcers, reminders, accountability, gaming/competition, responsiveness to quantitative summary feedback, monetary incentives, altruism, learning, elimination of symptoms, etc.); computerized performance tasks (e.g., delayed discounting) to measure/identify salient reinforcer
  • modules are described in a particular order, it should be noted that the modules can be performed in any other suitable sequence, omit operations, and/or include additional operations (e.g., based on refinement and training of models described below, and/or based on other factors). Furthermore, aspects of the modules can overlap with each other in any suitable manner.
  • method flow proceeds to operation 215.
  • the one or more non-behavioral therapy components are administered to the patient in combination with the one or more behavioral therapy components according to the personalized intervention regimen generated for the patient.
  • administering therapies according to an intervention regimen can further include administration of other types of interventions, such as those including non-behavioral therapy components, in combination with interventions that include behavioral therapy components, by way of the online system in coordination with other devices, where monitoring of performance of activities with such interventions is described below.
  • non-behavioral therapy components can include one or more of pharmaceutical compositions, nutraceutical compositions, nutritional therapies, whole system medicine, mind-body interventions, physical exercise, and biofeedback.
  • some therapies can be administered via a variety of routes, such as, but not limited to, ocular, oral, parenteral, topical, bronchial (e.g., by bronchial instillation), buccal, dermal (which may be or comprise, for example, one or more of topical to the dermis, intradermal, interdermal, transdermal, etc.), enteral, intra-arterial, intradermal, intragastric, intramedullary, intramuscular, intranasal, intraperitoneal, intrathecal, intravenous, intraventricular, within a specific organ (e.g., intrahepatic), mucosal, nasal, oral, rectal, subcutaneous, sublingual, topical, tracheal (e.g., by intratracheal instillation), vaginal, and vitreal.
  • routes such as, but not limited to, ocular, oral, parenteral, topical, bronchial (e.g., by bronchial instillation), buccal,
  • administration may be performed via a medical device such as, for example, a wearable device, an implanted device, and/or an ingestible device.
  • wearable devices may be designed and/or demonstrated to stimulate peristalsis.
  • ingestible devices can be designed and/or demonstrated to aid to trigger contractions in a colon of the patient.
  • therapies can be self-administered by patients, for example, in the case of therapies involving physical exercise or mind-body interventions.
  • method flow proceeds to operation 216.
  • the patient at operation 216, the patient’s interactions with the one or more behavioral therapy components and the one or more non-behavioral therapy components are monitored remotely in near realtime to generate patient interaction data.
  • an embodiment of the online system in coordination with the network and a client device, can monitor the patient’s interactions with the behavioral and non-behavioral therapy components contemporaneously with administration of the intervention regimen.
  • Monitoring patient interactions functions to provide intimate understanding of progress of the patient in achieving health goals, and to provide further personalization of and administration of intervention content at appropriate times, in order to maintain or improve progress of the patient.
  • Monitoring is preferably performed in near-real time or real time, such that actions can be taken to adjust interventions to patient states according to just-in-time adaptive intervention (JIT Al) protocols.
  • JIT Al just-in-time adaptive intervention
  • monitoring can be performed with any suitable delay (e.g., in relation to achieving better accuracy of assessed states of the patient).
  • monitoring can be performed using survey components, such as the patient reported outcome instruments described above, which may be delivered with interactive interventions of the intervention regimen, where the patient is prompted and provided with interactive elements that allow the patient to provide self-report data indicating progress statuses.
  • Monitoring can additionally or alternatively be performed with processing of other nonsurvey data streams, where the non-survey data streams are associated with system or device usage metrics, social networking behavior extracted from usage of social networking platforms and communication platforms, sensor-derived data, and/or other data. Monitoring can thus occur with any frequency and/or level of intrusiveness.
  • operation 216 can process monitoring data (e.g., real time data, non-real time data, dynamic data, static data) with a predictive model that outputs indications of one or more of symptom severity predictions, predictions of patient states, indications of predicted success of the patient in achieving goals, and/or other predictions, where training of the predictive model with training sets of data is described in additional detail below.
  • monitoring data e.g., real time data, non-real time data, dynamic data, static data
  • a predictive model that outputs indications of one or more of symptom severity predictions, predictions of patient states, indications of predicted success of the patient in achieving goals, and/or other predictions, where training of the predictive model with training sets of data is described in additional detail below.
  • ecological momentary assessments of the patient can be used for monitoring.
  • client device usage parameters can be used for monitoring.
  • client device usage parameters can include frequency of application switching, duration of time spent in association with each application login, screen time parameters, data usage associated with different applications and/or types of applications (e.g., social networking, creative, utility, travel, activity-related, etc.) executing on the client device of the patient, time of day of application usage, location of device usage, and other client device usage parameters.
  • applications e.g., social networking, creative, utility, travel, activity-related, etc.
  • the system can process voice data and/or text communication data of the patient for monitoring and modifying interventions and program aspects.
  • voice data can include voice sampling data from which emotional states can be extracted using voice processing models.
  • natural language processing of textual data e.g., from communication platforms, from social networking platforms
  • the client device can be used to provide context for behaviors of the patient and/or assess emotional or cognitive states of the patient.
  • electronic health record data can be used for monitoring.
  • the online system can be configured to receive a notification providing information regarding the type of care the patient has received, and to use this data for monitoring statuses of the patient.
  • the system can include architecture for processing data from other sensors of the client device, devices in the environment of the patient, and/or wearable computing devices can be used for monitoring.
  • device data can include activity data, location data, motion data, biometric data, and/or other data configured to provide context to behaviors associated with the health condition of the patient.
  • motion data from motion of sensors of the client device can indicate that the user is sedentary, and may be experiencing symptoms that can be addressed with components of the intervention regimen.
  • device usage data can indicate that the patient has been using a particular device (e.g., a tablet device in proximity to the patient, where use does not require extensive motion of the patient), in a fixed location (e.g., from GPS data), and in a prone position (e.g., from motion chip data), and may be experiencing health condition symptoms that can be addressed with components of the intervention regimen.
  • a particular device e.g., a tablet device in proximity to the patient, where use does not require extensive motion of the patient
  • a fixed location e.g., from GPS data
  • a prone position e.g., from motion chip data
  • the PDT systems and methods as described herein may provide for communication between a patient and one or more external medication tracking devices, such as a smart pill packet, smart pill bottle, etc.
  • external medication tracking devices such as a smart pill packet or smart pill bottle may communication with and provide data to a cloud-based system to indicate, for example, if/when/how often a patient takes their medication.
  • technologies described herein may receive updates from the cloud-based system to track the patient’s taking of their medication.
  • An application may, for example, use received updates to check that a patient is adhering to their medication schedule, goals, etc., and present reminders accordingly.
  • technologies described herein may provide for other approaches of communication, e.g., directly, with external medication devices, for example wirelessly, e.g., over a wireless network, via Bluetooth®, and the like.
  • monitoring the patient’ s interactions with the behavioral and non-behavioral therapy components includes obtaining one or more of: patient physiological health data; patient psychological health data; patient condition data; patient symptoms data; patient medications data; patient medication adherence data; patient progress report data; patient system usage data; patient device usage data; patient social networking behavior data; patient voice data; patient textual data; patient activity data; patient location data; patient motion data; and patient biometric data.
  • active monitoring of patient states can be used to adjust administration of intervention regimen modules in order to appropriately meet the needs of the patient.
  • Other data and combinations of data can, however, be used for monitoring.
  • the patient interaction data is processed by the PDT system to generate intervention modification data representing recommended modifications to the patient’s personalized intervention regimen.
  • the recommended modifications to the patient’s personalized intervention regimen include recommended modifications to aspects of the behavioral therapy components of the regimen, based on processing of patient interaction data representing patient interactions with the behavioral therapy components of the regimen, wherein the patient interaction data is generated by the monitoring operation 216, as discussed above.
  • operation 218 functions to generate recommendations for further customization of the behavioral therapy components of the intervention regimen, in order to improve personalization of delivered content to meet the needs of the patient, in an adaptive manner.
  • Operation 218 can also function to generate recommendations for increasing engagement between the patient and the intervention regimen, in order to improve effectiveness of provided treatments and increase the chances of success of the patient in achieving their goals.
  • behavioral therapy components of the intervention regimen may include a plurality of interactive therapy modules.
  • recommendations for modifying aspects of the behavioral therapy components of the patient’s personalized intervention regimen can include one or more recommendations, such as, but not limited to: adjusting the order of administration of the behavioral therapy components; adjusting the frequency of administration of the behavioral therapy components; adjusting the mode of administration of the behavioral therapy components; adjusting the content of the behavioral therapy components; adjusting the content size of the behavioral therapy components; adjusting the presentation of the behavioral therapy components; adjusting the layout of the behavioral therapy components; updating the patient’s electronic health records (EHRs); updating the patient’s personal health records (PHRs); updating the patient’s open medical records, for instance by writing to or modifying records whenever new information is generated regarding the user/patient.
  • EHRs electronic health records
  • PHRs personal health records
  • recommendations for modifying aspects of the behavioral therapy components of the patient’s personalized intervention regimen can include recommendations for providing features for increasing engagement and optimal learning.
  • specific descriptions self-reported by the patient can be used in subsequent portions of the intervention regimen to increase personalization of the intervention to drive engagement.
  • features for increasing engagement and optimal learning can include features that mimic therapist/healthcare provider, or social group interactions (e.g., patient testimonials, clinician video content, etc.).
  • features for increasing engagement and optimal learning can include features that link the patient’s specific current problems and/or challenges faced by the patient as a trigger to notify the patient to interact with content of the intervention regimen and recommend appropriate skill for improving health states.
  • the recommended modifications to the patient’s personalized intervention regimen include recommended modifications to aspects of the non- behavioral therapy components of the regimen, based on processing of patient interaction data representing patient interactions with the non-behavioral therapy components of the regimen, wherein the patient interaction data is generated by the monitoring operation 216, as discussed above.
  • recommendations for modifying aspects of the non- behavioral therapy components of the patient’s personalized intervention regimen can include one or more recommendations, such as, but not limited to: adjusting the order of administration of the non-behavioral therapy components; adjusting the frequency of administration of the non- behavioral therapy components; adjusting the mode of administration of the non-behavioral therapy components; adjusting the content of the non-behavioral therapy components; adjusting the dosage amount of the non-behavioral therapy components; and adjusting the dosage schedule of the non-behavioral therapy components .
  • a dosage amount of the non-behavioral therapy treatment may be based upon the state of the patient’s health condition symptom severity.
  • a dosing schedule for administration of a non-behavioral therapy may be relative to a schedule for administration of the behavioral therapy.
  • Such recommendations regarding amount and/or dosing may be absolute and/or relative to other events and/or activities.
  • recommendations may comprise a particular schedule of dosage, e.g., a particular rate, timing (e.g., in a morning, afternoon, or evening), etc.
  • Recommendations regarding timing may include timings and/or amounts relative to other activities, such as meal consumption, physical exercises, seasons, social gatherings, travel, work, etc.
  • adjusting an amount of the non-behavioral therapy can include correspondingly adjusting an amount of a behavioral therapy treatment provided to the patient, thereby titrating relative treatment types provided to the patient based upon returned outputs of models associated with the methods described.
  • dosage recommendations provided via the approaches described herein are restricted to fall within a pre-defined range, for example as specified by a physician.
  • dosage recommendations provided by technologies (e.g., systems and methods) described herein comprise an identification of one or more specific symptoms, so as to provide recommendation to discuss particular symptoms with a medical professional, such as a physician and/or therapist (e.g., to discuss particular changes to medication regimens and/or types of medication, so as to best manage particular symptoms).
  • a medical professional such as a physician and/or therapist
  • recommendations may be generated via use of one or more machine learning modules that receive, as input, data corresponding to patient symptom and/or habits, as tracked by various modules such as those described herein. In some embodiments, this information is used as feedback, to refine and dynamically update parameters of machine learning modules.
  • one or more notifications are issued to a computing device accessible to one or more health practitioners associated with the patient (e.g., nurses, physicians, dieticians, therapists, etc., who may be registered to view patient updates with a secure hub).
  • one or more notifications are issued to a patient computing device, for example, through the PDT system disclosed herein, and/or via an out-of-app notification, such as text message, push notification, email, calendar reminder, etc.
  • the one or more notifications include options and/or recommendations for modifications to the patient’s personalized intervention regimen, for the patient to discuss with their healthcare practitioner
  • the one or more notifications include identification of activities, behaviors, and/or symptoms of the patient.
  • the one or more notifications include options and/or recommendations for new therapies and/or potential adjustments to current therapies being administered to the patient.
  • the options and/or recommendations are based on potential compatibility of new and/or modified therapies with the identified activities, behaviors, and/or symptoms of the patient.
  • options and/or recommendations may include adjusting aspects of the patient’s intervention regimen, such that it is compatible with the patient’s physical exercise, travel, work, etc.
  • the one or more notifications include options and/or recommendations for one or more tests for the patient to complete (e.g., blood test, breath test for bacterial overgrowth, colonoscopy, computed tomography (CT) scan, flexible sigmoidoscopy, lactose intolerance test, saliva test, stool tests, upper endoscopy, x-ray, etc.)
  • the one or more notifications include alerts and/or reminders to the patient to self-administer at least a portion of a therapy.
  • a notification may be a reminder to take a particular pharmaceutical composition and/or a particular nutraceutical composition and/or a notification may be a reminder to use a wearable device for a prescribed period of time according to a particular therapeutic regimen.
  • method flow proceeds to operation 220.
  • aspects of the behavioral therapy and/or the non-behavioral therapy components defined by the patient’s personalized intervention regimen may be modified based on the intervention modification data.
  • an embodiment of the online system in coordination with the network and a client device can, based on the intervention modification data, perform one or more actions to dynamically modify aspects of the behavioral therapy and/or the non-behavioral therapy components defined by patient’s personalized intervention regimen.
  • dynamically modifying aspects of the behavioral and non-behavioral therapy components of the patient’s personalized intervention regimen includes one or more of: adjusting the order of administration of the behavioral therapy components; adjusting the order of administration of the non-behavioral therapy components; adjusting the frequency of administration of the behavioral therapy components; adjusting the frequency of administration of the non-behavioral therapy components; adjusting the mode of administration of the behavioral therapy components; adjusting the mode of administration of the non- behavioral therapy components; adjusting the content of the behavioral therapy components; adjusting the content of the non-behavioral therapy components; adjusting the content size of the behavioral therapy components; adjusting the dosage amount of the non-behavioral therapy components; adjusting the dosage schedule of the non-behavioral therapy components; adjusting the presentation of the behavioral therapy components; adjusting the layout of the behavioral therapy components; updating the patient’s electronic health records; updating the patient’s personal health records; updating the patient’s open medical records; and increasing personalization of the intervention regimen.
  • dynamically modifying aspects of the patient’s personalized intervention regimen to promote patient engagement can be done using one or more of: artificial reality tools (e.g., augmented reality platforms, virtual reality platforms) for reducing depression, anxiety, pain, and/or other symptoms; artificial intelligence-based coaching elements for driving interactions with the patient; smart assistants (e.g., AlexaTM, SiriTM, GoogleTM Assistant, etc.) for assisting the patient in relation to task management, gamification elements within intervention regimen-associated applications executing on the client device; gamification elements of other devices (e.g., smart toilet devices having interactive elements, such as buttons that control flushing and other subsystems, for promoting triggering of stool sample tracking in relation to various symptoms); smart pill devices and/or medication-dispensing devices that provide insights in an engaging manner in coordination with intervention regimen modules; adjustment of reinforcement schedules (e.g., in relation to reward sensitivity, positive reinforcement, negative reinforcement, etc.) for providing intervention regimen content to the patient; and other elements for increasing engagement
  • artificial reality tools e.g., augmented reality
  • features for modifying, updating, and/or personalizing the intervention regimen, as well as for promoting engagement with the intervention regimen can be delivered within modules of the intervention regimen before, during and/or after monitoring of the patient at operation 216.
  • the patient’s personalized intervention regimen is modified dynamically, in near-real time, based on the intervention modification data generated at operation 218.
  • method flow may return to operation 214 to continue administering the intervention according to the modified personalized intervention regimen.
  • method flow proceeds to END operation 222, and the method 200A for treating gastrointestinal and inflammatory health conditions using prescription digital therapeutics in combination with other therapies is exited to await new instructions.
  • FIG. 2B depicts a flowchart of a method 200B for providing adaptive interventions for gastrointestinal and inflammatory health conditions, according to one or more embodiments.
  • method 200B begins at BEGIN 224, and method flow proceeds to operation 226.
  • operation 226 a preassessment of a patient exhibiting one or more GI and/or inflammatory health condition symptoms is performed.
  • an embodiment of the online system in coordination with the network and a client device, can perform operation 226, performing a pre-assessment of a patient exhibiting one or more GI and/or inflammatory health condition symptoms, contemporaneously with executing an onboarding process with the patient with the online system.
  • Operation 226 functions to retrieve data describing characteristics of the patient, preferences of the patient, goals of the patient and/or any other suitable patient features that can be used to provide adaptive interventions in a customized and personalized manner, in order to promote user engagement with the intervention regimen(s) described in subsequent operations of the method 200B.
  • operation 226 can include preassessing and onboarding patients and assessing characteristics including one or more of: demographics (e.g., genders, ages, familial statuses, residential location, ethnicities, nationalities, socioeconomic statuses, sexual orientations, etc.), household situations (e.g., living alone, living with family, living with a caregiver, etc.), dietary characteristics (e.g., omnivorous, vegetarian, pescatarian, vegan, reduced carbohydrate consumption, reduced acid consumption, gluten-free, simple carbohydrate, or other dietary restrictions, etc.), levels of activity, levels of alcohol consumption, levels of drug use, psychological symptom severity, levels of mobility (e.g., in relation to distance traveled in a period of time), biomarker statuses (e.g., fecal calprotectin, cholesterol levels, lipid states, blood biomarker statuses, etc.), weight, height, body mass index, genotypic factors, durations of mindfulness (e.g.
  • the pre-assessment and/or onboarding process performed in operation 226 can identify the patient as having GI health condition symptoms associated with GI health, such as, but not limited to, one or more of: irritable bowel syndrome (IBS), inflammatory bowel disease (IBD, such as associated with Crohn’s disease or ulcerative colitis), lactose intolerance, gastroesophageal reflux disease (GERD), ulcers (e.g., peptic ulcer disease, gastric ulcers, etc.), functional dyspepsia, hernias, celiac disease, diverticulitis, malabsorption, short bowel syndrome, intestinal ischemia, pancreatitis, cysts, gastroparesis, gastritis, esophagitis, achalasia, strictures, anal fissures, hemorrhoids, proctitis, prolapse, gall stones, cholecystitis, cholangitis, G
  • IBS irritable bowel syndrome
  • IBD inflammatory
  • the preassessment and/or onboarding process performed in operation 226 can identify the patient as having inflammatory health condition symptoms associated with chronic inflammation, such as, but not limited to, one or more of: diabetes, cardiovascular diseases (e.g., hypertension), liver diseases, arthritis and joint diseases (e.g., rheumatoid arthritis), various allergies and asthma, and chronic obstructive pulmonary disease (COPD), and/or any other suitable symptoms.
  • inflammatory health condition symptoms associated with chronic inflammation such as, but not limited to, one or more of: diabetes, cardiovascular diseases (e.g., hypertension), liver diseases, arthritis and joint diseases (e.g., rheumatoid arthritis), various allergies and asthma, and chronic obstructive pulmonary disease (COPD), and/or any other suitable symptoms.
  • diabetes e.g., hypertension
  • liver diseases e.g., arthritis and joint diseases (e.g., rheumatoid arthritis)
  • COPD chronic obstructive pulmonary disease
  • a set of signals can encode physiological data, behavioral data, environmental stress data, emotional data, and cognitive data of the user, from the preassessment, health record access, API access of health monitoring systems, and/or biometric sensors. Furthermore, such signals can be collected repeatedly throughout performance of the methods described, as will be discussed in additional detail below.
  • the pre-assessment can be configured to receive information regarding (or automatically detect, or automatically extract, based upon symptoms, etc.) the subtype(s) of IBS (e.g., IBS-C with predominant constipation, IBS-D with predominant diarrhea, IBS-M with mixed bowel habits) a patient has, in order to prioritize relevant content provided to the patient, in the interests of customizing the program. For instance, if the pre-assessment operation 226 identifies that the patient is predominantly subtype IBS-C, subsequent portions of the method 200B can prioritize content associated more highly with IBS-C. Subtype identification can, however, be assessed outside of the pre-assessment of operation 226.
  • the subtype(s) of IBS e.g., IBS-C with predominant constipation, IBS-D with predominant diarrhea, IBS-M with mixed bowel habits
  • prescription digital therapeutics provided by the method 200B and system 100AA can be provided as monotherapies, or as complementary therapies.
  • complementary therapies for IBS-C can include one or more therapies, such as, but not limited to: antibiotics, antidepressants, antispasmodics, 5 -hydroxytryptamine 4 agonists, over-the-counter laxatives, probiotics, selective C-2 chloride channel activators, and other therapies.
  • complementary therapies for IBS-D can include one or more therapies, such as, but not limited to: antibiotics, antidepressants, anti-diarrheal medications, antispasmodics, 5 -hydroxytryptamine 4 agonists, probiotics, and other therapies.
  • complementary therapies for IBS-M can include one or more of: antibiotics, antidepressants, antispasmodics, probiotics, and other therapies.
  • Complementary therapies can further include one or more of: psychological treatments, hypnotherapy, acupuncture, herbal therapies, oils, and other therapies.
  • operation 226 of method 200B includes a method of determining severity of a gastrointestinal (GI) and/or inflammatory health condition.
  • FIG. 5 A depicts a flowchart of a process for determining severity of a gastrointestinal and/or inflammatory health condition, according to one or more embodiments.
  • FIG. 5B depicts examples of a process for determining severity of a gastrointestinal and/or inflammatory health condition, according to one or more embodiments.
  • [ 0308 ] Referring to FIG. 5 A and FIG. 5B together, in embodiments related to monotherapies and complementary therapies, the process 500, as shown in FIG.
  • operation 501 can include operation 501 for calculating levels of a GI and/or inflammatory health condition-associated marker (e.g., from a sample from the user, such as a stool sample or a breath sample, from interactions with the system, etc.) to identify the user (e.g. the patient), as having a certain state of severity (e.g., expression, phenotype, etc.) of the GI and/or inflammatory health condition.
  • a GI and/or inflammatory health condition-associated marker e.g., from a sample from the user, such as a stool sample or a breath sample, from interactions with the system, etc.
  • a certain state of severity e.g., expression, phenotype, etc.
  • 5 A can be implemented through a PDT system executing on a mobile device or other device associated with the user, where a user interface of the PDT system prompts inputs from the user pertaining to various symptoms (e.g., pain, defecation, abdominal distension, digestive issues, cognitive symptoms, behavioral effects, etc.) and generates a report indicating severity of the GI and/or inflammatory health condition (e.g., IBS, IBD, etc ), as shown in FIG. 5B.
  • various symptoms e.g., pain, defecation, abdominal distension, digestive issues, cognitive symptoms, behavioral effects, etc.
  • a report indicating severity of the GI and/or inflammatory health condition (e.g., IBS, IBD, etc ), as shown in FIG. 5B.
  • the process 500 shown in FIG. 5 A can then include operation 502, administering a treatment (e.g., monotherapy, complementary therapy) to the user having the state of severity, where the treatment comprises one or more of the therapies described.
  • a treatment e.g., monotherapy, complementary therapy
  • the process 200B can include adjusting (e.g., decreasing, increasing, maintaining) an amount of a non-behavioral therapy treatment provided to the user based upon the state of severity, and/or correspondingly adjusting (e.g., decreasing, increasing, maintaining) an amount of a behavioral therapy treatment provided to the user, thereby titrating relative treatment types provided to the user based upon returned outputs of models associated with the methods described.
  • a treatment cocktail can include prescription digital therapeutic aspects and non-prescription digital therapeutic aspects.
  • the pre-assessment and/or onboarding process performed in operation 226 can identify mental health statuses of the patient, in relation to comorbid or non-comorbid conditions (e.g., associated with anxiety, associated with depression, associated with social behavior, etc.), where the intervention regimen described in more detail above can be configured to improve mental health states of the patient in a timely and adaptive manner.
  • comorbid or non-comorbid conditions e.g., associated with anxiety, associated with depression, associated with social behavior, etc.
  • related data can include psychological and/or disease symptom/clinical profile data that informs selection of high priority therapy components, where examples include data such as, but not limited to: illness-related ruminations being predominant; symptoms triggered by anticipatory anxiety; aspects adapted for types of reinforcement based on level of anhedonia, as assessed from system-provided tools associated with depression assessment (e.g., upon identification of anhedonia characteristics of the patient, promoting behavioral activation content by the system and response chaining, where response chaining involves linking of effortful avoided tasks to those that are neutral or slightly rewarding); sources of motivation; reward sensitivity (e.g., sensitivity associated with drive and reward responsiveness (e.g., using a BIS/BAS assessment tool); and threat sensitivity.
  • data such as, but not limited to: illness-related ruminations being predominant; symptoms triggered by anticipatory anxiety; aspects adapted for types of reinforcement based on level of anhedonia, as assessed from system-provided tools associated with depression assessment (e.g., upon identification of anhedonia
  • the method 200B can include receiving a reward sensitivity dataset characterizing motivation and reinforcement behavior of the user, and modulating aspects of the treatment upon processing the reward sensitivity dataset with one or more models described.
  • Mental health, reward tendencies and sensitivity, and motivational aspect identification can, however, be assessed outside of the pre-assessment of operation 226.
  • the pre-assessment and/or onboarding process performed in operation 226 can identify user preferences associated with scheduling of content delivery (e.g., in relation to frequencies of content delivery described above) associated with one or more aspects of the intervention regimen, preferred formats (e.g., visual formats, audio formats, haptic formats, etc.) of content delivery, frequency of content delivery, location of user when content is delivered, specific device(s) to which content is delivered, and/or any other suitable user preferences.
  • preferred formats e.g., visual formats, audio formats, haptic formats, etc.
  • the preassessment and/or onboarding process performed in operation 226 can identify user goals for improving health, in relation to the intervention regimen.
  • Such goals can include one or more goals, such as, but not limited to: reduction of anxiety, reduction of negative emotions, reduction of depression symptoms, improvement of sleep behavior, improvement in socialization, improvement of GI and/or inflammatory health condition symptoms, improvement of medication adherence, improvement in GI and/or inflammatory-related quality of life, improvement of other health condition symptoms, and/or any other suitable goals.
  • Goals can be organized at a high level of abstraction (e.g., improve sleep behavior), and/or at lower levels of abstraction (e.g., improve quality of sleep, reduce number of symptom-induced disturbances to sleep, etc.).
  • the online system and/or other system components can implement surveying tools (e.g., for self-report of data from the patient) and/or non-survey-based tools for acquisition of data.
  • Survey tools can be delivered through an application associated with the PDT system executing on the client device of the patient and/or through another suitable method, where the survey tools can implement architecture for assessing the patient in relation to mental health, pain, GI and/or inflammatory health symptom severity or disease activity (e.g. IBS-symptom severity scale), types of GI and/or inflammatory health condition symptoms, and/or other statuses.
  • the surveying tools can be derived from one or more tools such as, but not limited to: a patient health questionnaire (e.g., PHQ-9), an anxiety disorder questionnaire (e.g., GAD-7, PC-PTSD, SCARED), a work and social adjustment scale (WSAS)- derived tool, a pain assessment questionnaire (e.g., numerical rating scale, Wong-Baker faces scale, FLACC scale, CRIES scale, COMFORT scale, McGill scale, Color Analog scale, etc.), a clinical disease activity measurement (e.g., CD Al, PUCAI, Mayo Score) and any other tool or instrument.
  • Survey components can be implemented during pre-assessment of a patient and/or within modules of the intervention regimen, as described in more detail above.
  • the system can include architecture for receiving data derived from the patient (e.g., through sensor components, through survey components, associated with pain characteristics, digestive characteristics, defecation characteristics, and other characteristics), processing the data with one or more models, and returning scores (e.g., measures of symptom severity, etc.). Scores can also be used for tagging user data with symptom severity, in relation to model aspects and model training/refinement described below. [ 0316 ] In relation to performing the pre-assessment and/or onboarding process at operation 226, in various embodiments, the online system and/or other system components can implement data from devices (e.g., non-survey data).
  • devices e.g., non-survey data
  • embodiments of the system can perform pre-assessment with implementation of data from devices including one or more devices, such as, but not limited to: electronic health record-associated devices; wearable devices (e.g., wrist-borne wearable devices, head-mounted wearable devices, etc.) for monitoring behavior and activities (e.g., related to physiological/cognitive stress, related to respiration activity, related to sedentary and active states, etc.) of the user; non-invasive torso- coupled devices (e.g., abdominal or stomach sensors configured to detect GI or digestive activity); ingestible smart-pill devices; smart toilet devices and/or other devices for analyzing stool and/or urine samples from the patient; and other devices.
  • devices including one or more devices, such as, but not limited to: electronic health record-associated devices; wearable devices (e.g., wrist-borne wearable devices, head-mounted wearable devices, etc.) for monitoring behavior and activities (e.g., related to physiological/cognitive stress, related to respiration activity, related to sedentary
  • Non-survey-derived data can additionally or alternatively include data derived from API access of social networking platforms, other communication platforms (e.g., for extracting social behavior characteristics associated with text, voice, and other communications of the users), location-determining platforms, and/or other platforms, in order to assess social behaviors of the user.
  • FIG. 6 depicts a flowchart of a pre-assessment and onboarding process of a method for providing adaptive interventions, according to one or more embodiments.
  • the pre-assessment and onboarding process 600 can include operation 611, which facilitates downloading of an application associated with the system and/or using of a non-downloadable version of the system (e.g., via web application, etc.) for delivering the intervention regimen by a client device of the patient; operation 612, which renders a welcome/introduction screen within the application associated with the system; operation 613, which delivers content within the application for educating the patient regarding the purpose of the system and provides an overview of the intervention regimen; operation 614, which creates a patient profile within the online system, resulting in a first tier of personalization by implementing survey and non-survey based tools (e.g., to assess gender, age, preferences for scheduling of content delivery, specific GI and/or inflammatory health condition symptoms of the patient, etc.); and operation 615, which, within the application associated with the system, assesses goals of the patient, resulting in a second tier of personalization.
  • operation 611 which facilitates downloading of an application associated with the system and/
  • the second tier of personalization can operate by assessing goals related to anxiety reduction, depression reduction, reduction of IBS and/or IBD or other gastrointestinal (GI) and/or inflammatory disease or syndrome symptoms, improvement of sleep, improvement of socialization, and other goals.
  • FIG. 6 further depicts operation 616, which, in one embodiment, processes the data from operations 614 and 615 with an intervention-determining model to output a personalized intervention regimen with adaptive behavioral therapy tools and exercises for improving health and wellbeing of the patient, in relation to his/her specific goals.
  • FIG. 6 also depicts operation 617 where a first module of the intervention regimen is delivered to the patient within the application associated with the system, and operation 618, which provides further adaptation of modules of the intervention regimen as the patient progresses through the intervention regimen and interacts with content.
  • FIG. 6 While the operations of FIG. 6 are shown in a particular order, the operations can be performed in another suitable sequence, omit operations, and/or include additional operations (e.g., based on refinement and training of models, as described below, as well as based on other factors).
  • FIG. 7 depicts examples of system aspects of a program for personalized health condition monitoring and improvement, according to one or more embodiments.
  • components delivered through a PDT system may include content such as, but not limited to: onboarding material, daily (or other time scale) review, progress summaries, brain-gut connection content, personal model analyses, symptom management material, educational material, symptom tracking analyses, personalized treatment analyses, quick references, and multiple engagement tactics material.
  • process flow proceeds to operation 228.
  • an intervention regimen for the patient is generated upon processing data from the pre-assessment with an intervention-determining model.
  • one embodiment of the online system in coordination with the network and a client device, can process data from the pre-assessment with an intervention-determining model.
  • Operation 228 functions to generate an intervention regimen for the patient upon processing pre-assessment data, in order to design a customized intervention regimen to address specific symptoms and needs of the patient. While operation 228 is described in relation to pre-assessment data, model architecture and associated algorithms can additionally or alternatively be applied to assessment of patient data as the patient interacts with content of the intervention regimen, in order to adaptively modify delivery of intervention regimen components to the patient, with processing of incoming data.
  • the intervention-determining model contemporaneously processes data associated with patient goals, user GI and/or inflammatory health condition symptoms, patient mental health states, other characteristics, and interactions with content of the PDT system, providing the intervention regimen as inputs, in order to output a customized and modulatable intervention regimen to improve the health and/or wellbeing of the patient.
  • the intervention-determining model can include architecture for one or more of: conditional decision making (e.g., with conditional branching structure that processes input data in stages and determines an output at each node of the branching structure); ranking (e.g., with ranking algorithms configured to rank candidate intervention regimen components according to appropriateness, based on the input data); matching (e.g., with performance of best match operations between input data and different groups representing modules of the intervention regimen, with centroid-based approaches, etc.); correlation (e.g., correlation functions that process input data to generate outputs associated with different intervention regimen components); and/or any other suitable architecture. Training of models is further described below.
  • conditional decision making e.g., with conditional branching structure that processes input data in stages and determines an output at each node of the branching structure
  • ranking e.g., with ranking algorithms configured to rank candidate intervention regimen components according to appropriateness, based on the input data
  • matching e.g., with performance of best match operations between input data and different groups representing modules of the intervention regimen, with cent
  • method flow proceeds to operation 230.
  • the online system in coordination with other system components (e.g., the client device, external systems, network, etc.) delivers the intervention regimen to the patient, for instance, through an application associated with the PDT system executing at the client device of the patient.
  • content associated with the intervention regimen can be of visual (e.g., image format, video format), textual, audio, haptic, and/or other formats, through connected devices (e.g., mobile computing devices, wearable devices, audio output devices, displays, temperature control devices, lighting control devices, etc.) and generated in a manner that promotes user engagement.
  • connected devices e.g., mobile computing devices, wearable devices, audio output devices, displays, temperature control devices, lighting control devices, etc.
  • the system in providing the interventions (e.g., such as interventions described in more detail below), can coordinate with and/or provide instructions for control of other devices, for intervention delivery.
  • the system can coordinate with environmental control devices (e.g., connected audio output devices, connected temperature control devices, connected lighting control devices, connected pill dispensing devices, connected smart pill devices, etc.) to change aspects of the patient’s environment in association with provision of the intervention regimen.
  • environmental control devices e.g., connected audio output devices, connected temperature control devices, connected lighting control devices, connected pill dispensing devices, connected smart pill devices, etc.
  • the intervention regimen can provide a grounding exercise to reduce anxiety regarding GI and/or inflammatory health condition symptoms, where the user is prompted to observe aspects of the environment with multiple senses, and the system can coordinate with environmental control devices to adjust one or more of lighting (e.g., colors, intensity, etc.), sounds (e.g., through audio output devices), and/or temperature in the patient’s environment.
  • the intervention regimen can provide a relaxation exercise to reduce pain associated with GI and/or inflammatory health condition symptoms, and coordinate with an audio output device to play music pleasing to the patient.
  • the intervention regimen can provide an exercise activity involving movements or dancing, to reduce bloating and depression associated with GI and/or inflammatory health condition symptoms, and coordinate with an audio output device to play dance music to the user, while reducing environmental temperature with a smart thermostat device.
  • the system can provide coordinated interventions, however, in any other suitable manner, where details of interventions are provided in more detail above.
  • FIG. 8A, FIG. 8B, FIG. 8C, FIG. 8D, and FIG. 8E depict example schematics of conditional branching architecture implemented for delivery of intervention regimen components, according to one or more embodiments.
  • the interventiondetermining model includes architecture for processing input data (e.g., from the pre-assessment and in real-time as the patient interacts with content of the intervention regimen), with a conditional branching model (e.g., with if-then branches coupled to nodes associated with outputs) that processes input data to tailor individual psychological interventions to the patient in an individualized manner.
  • the conditional branching model thus includes decision rules linking characteristics of the patient (e.g., clinical and symptom presentation, demographics, etc.) to different components of the intervention regimen, as an adaptive intervention.
  • FIG. 8A depicts architecture of the conditional branching model for a generalized pathway where, based on severity of physical illness symptoms exhibited by a patient, the model guides (e.g., through an application associated with the PDT system executing at the client device) the patient through foundational behavioral skills appropriate to the state and goals of the patient.
  • the order of modules can vary from patient to patient. Decisions (within app) about which modules to prioritize first are based on patient’s presentation and needs (e.g., symptom patterns, etc.). For example, if abdominal pain is what is most bothersome to the patient, the digital therapeutic will recommend the pain management module after completing one of the modules (e.g. the relaxation module).
  • the conditional branching model shown in FIG. 8 A selects a Behavior Change and Avoidance module for delivery, where the module informs the patient of links between behaviors and moods/feelings, and actively coaches the patient with respect to addressing avoidance behaviors in relation to GI health condition symptoms, in order to replace avoidance behaviors with alternative healthier behaviors.
  • the behavioral therapy techniques implemented in the selected intervention can address problem-focused coping tools and/or emotion-focused coping tools, with additional tailoring for different mental health issues associated with the GI health condition symptoms of the patient.
  • conditional branching model outputs behavioral activation exercises, cognitive reframing techniques, talent practicing and reinforcement exercises, and/or other exercises to mitigate depression symptoms.
  • conditional branching model outputs exposure-based exercises associated with anxiety sources, anxiety tolerance skill-building exercises, grounding exercises, and/or other exercises to mitigate anxiety symptoms.
  • the conditional branching model outputs problem-solving exercises with respect to controllable vs. uncontrollable stressors, and other exercises to mitigate problem-solving issues.
  • the conditional branching model further receives inputs (e.g., rankings of symptom severity) related to symptoms that the patient wishes to improve (e.g., related to pain management, related to sleep, related to adherence, related to communication, related to social problem solving, related to relapse prevention, etc.), and then based upon the inputs, guides the user through additional cognitive skills tailored to improve symptoms in the manner that the patient desires.
  • inputs e.g., rankings of symptom severity
  • related to symptoms that the patient wishes to improve e.g., related to pain management, related to sleep, related to adherence, related to communication, related to social problem solving, related to relapse prevention, etc.
  • FIG. 8B depicts architecture of the conditional branching model for an anxiety-specific pathway where, based on severity of physical illness symptoms exhibited by a patient, the model guides (e.g., through an application associated with the PDT system executing at the client device) the patient through foundational behavioral skills appropriate to the state and goals of the patient.
  • the conditional branching model selects a Behavior Change and Avoidance module for delivery, where the module informs the patient of links between behaviors and moods/feelings, and actively coaches the patient with respect to addressing avoidance behaviors in relation to GI and/or inflammatory health condition symptoms, in order to replace avoidance behaviors with alternative healthier behaviors.
  • the conditional branching model of FIG. 8B outputs exposure-based desensitization exercises associated with anxiety sources, anxiety tolerance skill-building exercises, grounding exercises, and/or other exercises to mitigate anxiety symptoms.
  • the conditional branching model of FIG. 8B further receives inputs (e.g., rankings of symptom severity) related to sleep and/or other symptoms (e.g., fatigue, sleep hygiene, worry, etc.) that the patient wishes to improve, and then based upon the inputs, guides the user through additional cognitive skills, problem-solving exercises, and behavior change exercises, tailored to improve sleep symptoms related to his/her GI and/or inflammatory health condition.
  • FIG. 8C depicts architecture of the conditional branching model for a depression-specific pathway where, based on severity of physical illness symptoms exhibited by a patient, the model guides (e.g., through an application associated with the PDT system executing at the client device) the patient through foundational behavioral skills appropriate to the state and goals of the patient.
  • the conditional branching model selects a Behavior Change and Avoidance module for delivery, where the module informs the patient of links between behaviors and moods/feelings, and actively coaches the patient with respect to addressing avoidance behaviors in relation to GI and/or inflammatory health condition symptoms, in order to replace avoidance behaviors with alternative healthier behaviors.
  • the conditional branching model of FIG. 8C outputs behavioral activation exercises, cognitive reframing techniques, and reinforcement exercises, and/or other exercises to mitigate depression symptoms.
  • the conditional branching model of FIG. 8C further receives inputs (e.g., rankings of symptom severity) related to sleep and/or other symptoms (e.g., fatigue, sleep hygiene, worry, etc.) that the patient wishes to improve, and then based upon the inputs, guides the user through additional cognitive skills, problem-solving exercises, and behavior change exercises, tailored to improve sleep symptoms related to his/her GI and/or inflammatory health condition.
  • FIG. 8D depicts architecture of the conditional branching model for a pathway targeted to anxiety and depression (e.g., with a GAD-7 score greater than or equal to 11) where, the model guides (e.g., through an application associated with the PDT system executing at the client device) the patient through foundational behavioral skills appropriate to the state and goals of the patient.
  • the conditional branching model selects a Behavior Change and Avoidance module for delivery, where the module informs the patient of links between behaviors and moods/feelings, and actively coaches the patient with respect to addressing avoidance behaviors in relation to GI and/or inflammatory health condition symptoms, in order to replace avoidance behaviors with alternative healthier behaviors.
  • the conditional branching model of FIG. 8D outputs exposure-based desensitization exercises associated with anxiety sources, anxiety tolerance skill-building exercises, grounding exercises, and/or other exercises to mitigate anxiety symptoms.
  • the model also determines if the patient is suffering from pain symptoms, and provides the patient with pain management exercises.
  • the model also then sequentially determines if the user is exhibiting symptoms of depression (e.g., if PHQ-9 score is greater than or less than 10), and addresses depression symptoms sequentially relative to other symptoms (e.g., sleep, communication, medication adherence) based upon symptom severity.
  • FIG. 8E depicts architecture of the conditional branching model for a pathway that is not specific to anxiety or depression where, based on severity of physical illness symptoms exhibited by a patient, the model guides (e.g., through an application associated with the PDT system executing at the client device) the patient through foundational behavioral skills appropriate to the state and goals of the patient.
  • the conditional branching model selects a Behavior Change and Avoidance module for delivery, where the module informs the patient of links between behaviors and moods/feelings, and actively coaches the patient with respect to addressing avoidance behaviors in relation to GI and/or inflammatory health condition symptoms, in order to replace avoidance behaviors with alternative healthier behaviors.
  • the conditional branching model of FIG. 8E For a patient having no initial anxiety/depression symptoms, the conditional branching model of FIG. 8E outputs problem-solving exercises with respect to controllable vs. uncontrollable stressors, and other exercises to mitigate problem-solving issues.
  • the conditional branching model of FIG. 8E further receives inputs (e.g., rankings of symptom severity) related to sleep and/or other symptoms (e.g., fatigue, sleep hygiene, worry, etc.) that the patient wishes to improve, and then based upon the inputs, guides the user through additional cognitive skills, problem-solving exercises, and behavior change exercises, tailored to improve sleep symptoms related to his/her GI and/or inflammatory health condition.
  • inputs e.g., rankings of symptom severity
  • other symptoms e.g., fatigue, sleep hygiene, worry, etc.
  • method flow proceeds to operation 232.
  • operation 232 a set of interactions between the patient and modules of the intervention regimen and a health status progression of the patient are monitored contemporaneously with delivery of the intervention regimen.
  • an embodiment of the online system in coordination with the network and a client device, can monitor a set of interactions between the patient and modules of the intervention regimen and a health status progression of the patient contemporaneously with delivery of the intervention regimen.
  • Monitoring interactions functions to provide intimate understanding of progress of the patient in achieving health goals, and to provide further personalization of and delivery of intervention content at appropriate times, in order to maintain or improve progress of the patient.
  • Monitoring is preferably performed in near-real time or real time, such that actions can be taken to adjust interventions to user states according to just-in time adaptive intervention (JIT Al) protocols.
  • JIT Al just-in time adaptive intervention
  • monitoring can be performed with any suitable delay (e.g., in relation to achieving better accuracy of assessed states of the patient).
  • Monitoring can be performed using survey components delivered with interactive interventions of the intervention regimen, where the user is prompted and provided with interactive elements that allow the patient to provide self-report data indicating progress statuses. Monitoring can additionally or alternatively be performed with processing of other data streams, where the data streams are associated with system or device usage metrics, social networking behavior extracted from usage of social networking platforms and communication platforms, sensor-derived data, and/or other data. Monitoring can thus occur with any frequency and/or level of intrusiveness.
  • operation 232 can process monitoring data (e.g., real time data, non-real time data, dynamic data, static data) with a predictive model that outputs indications of one or more of symptom severity predictions, predictions of patient states, indications of predicted success of the patient in achieving goals, and/or other predictions, where training of the predictive model with training sets of data is described in additional detail below.
  • monitoring data e.g., real time data, non-real time data, dynamic data, static data
  • a predictive model that outputs indications of one or more of symptom severity predictions, predictions of patient states, indications of predicted success of the patient in achieving goals, and/or other predictions, where training of the predictive model with training sets of data is described in additional detail below.
  • ecological momentary assessments of the patient can be used for monitoring.
  • client device usage parameters can be used for monitoring.
  • client device usage parameters can include frequency of application switching, duration of time spent in association with each application login, screen time parameters, data usage associated with different applications and/or types of applications (e.g., social networking, creative, utility, travel, activity-related, etc.) executing on the client device of the patient, time of day of application usage, location of device usage, and other client device usage parameters.
  • applications e.g., social networking, creative, utility, travel, activity-related, etc.
  • the system can process voice data and/or text communication data of the patient for monitoring and modifying interventions and program aspects.
  • voice data can include voice sampling data from which emotional states can be extracted using voice processing models.
  • natural language processing of textual data e.g., from communication platforms, from social networking platforms
  • the client device can be used to provide context for behaviors of the patient and/or assess emotional or cognitive states of the patient.
  • electronic health record data can be used for monitoring.
  • the online system can be configured to receive a notification providing information regarding the type of care the patient has received, and to use this data for monitoring statuses of the patient.
  • the system can include architecture for processing data from other sensors of the client device, devices in the environment of the patient, and/or wearable computing devices can be used for monitoring.
  • device data can include activity data, location data, motion data, biometric data, and/or other data configured to provide context to behaviors associated with the health condition of the patient.
  • motion data from motion of sensors of the client device can indicate that the user is sedentary, and may be experiencing symptoms that can be addressed with components of the intervention regimen.
  • device usage data can indicate that the patient has been using a particular device (e.g., a tablet device in proximity to the patient, where use does not require extensive motion of the patient), in a fixed location (e.g., from GPS data), and in a prone position (e.g., from motion chip data), and may be experiencing GI health condition symptoms that can be addressed with components of the intervention regimen.
  • a particular device e.g., a tablet device in proximity to the patient, where use does not require extensive motion of the patient
  • a fixed location e.g., from GPS data
  • a prone position e.g., from motion chip data
  • process flow proceeds to operation 234.
  • an action configured to improve wellbeing of the patient with respect to the GI and/or inflammatory health condition is performed.
  • an embodiment of the online system in coordination with the network and a client device can, in response to at least one of the set of interactions and the health status progression, perform an action configured to improve health and wellbeing of the patient with respect to the GI and/or inflammatory health condition.
  • Operation 234 functions to provide further customization of the intervention regimen, in order to improve personalization of delivered content to needs of the patient, in an adaptive manner.
  • Operation 234 can also function to increase engagement between the patient and the intervention regimen, in order to improve effectiveness of provided treatments and increase success of the patient in achieving his/her goals.
  • the action performed according to operation 234 can include one or more of: adjusting order of and/or content of intervention modules provided, where intervention types and content are described above; updating electronic health records (EHRs), personal health records (PHRs), and/or open medical records, for instance by writing to or modifying records whenever new information is generated regarding the user/patient/patient; providing and/or facilitating provision of supplemental interventions (e.g., hypnotherapy, physical exercises, medications, supplements, etc.) beyond standard content of the intervention regimen, for instance, under physician-guidance or treatment recommendations; generating and/or providing notifications to the patient regarding changes in behavior or health statuses; generating and/or providing notifications to entities (e.g., relatives, acquaintances having permission of the patient, health care providers, etc.) associated with the patient regarding changes in behavior or health statuses; and/or any other suitable action.
  • EHRs electronic health records
  • PHRs personal health records
  • open medical records for instance by writing to or modifying records whenever new information is generated regarding the user/patient/patient
  • operation 234 can additionally or alternatively include functionality for increasing engagement of the patient with respect to interactions with content of the intervention regimen.
  • features for increasing engagement and optimal learning can include text-based functionality for self-monitoring and symptom tracking, where the system can process real time text interactions with provision of interactive tasks, which increases likelihood of patient responses.
  • specific descriptions self-reported by the patient can be used in subsequent portions of the intervention regimen to increase personalization of the intervention to drive engagement.
  • features for increasing engagement and optimal learning can include features that mimic therapist/healthcare provider, or social group interactions (e.g., patient testimonials, clinician video content, etc.).
  • features for increasing engagement and optimal learning can include features that link the patient’s specific current problems (e.g., from operation 232) and/or challenges faced by the patient as a trigger to notify the patient to interact with content of the intervention regimen and recommend appropriate skill for improving health states.
  • engagement can be promoted using one or more of: artificial reality tools (e.g., augmented reality platforms, virtual reality platforms) for reducing depression, anxiety, pain, and/or other symptoms; artificial intelligence-based coaching elements for driving interactions with the patient; smart assistants (e.g., AlexaTM, SiriTM, GoogleTM Assistant, etc.) for assisting the patient in relation to task management, gamification elements within intervention regimen-associated applications executing on the client device; gamification elements of other devices (e.g., smart toilet devices having interactive elements, such as buttons that control flushing and other subsystems, for promoting triggering of stool sample tracking in relation to various symptoms); smart pill devices and/or medication-dispensing devices that provide insights in an engaging manner in coordination with intervention regimen modules; adjustment of reinforcement schedules (e.g., in relation to reward sensitivity, positive reinforcement, negative reinforcement, etc.) for providing intervention regimen content to the patient; and other elements for increasing engagement.
  • artificial reality tools e.g., augmented reality platforms, virtual reality platforms
  • artificial intelligence-based coaching elements for driving
  • features for personalization and promoting engagement can be delivered within modules of the intervention regimen before and/or after monitoring of the patient according to operation 232.
  • method flow proceeds to END operation 236, and the method 200B for providing adaptive interventions for gastrointestinal and inflammatory health conditions is exited to await new instructions
  • FIG. 2C is a flowchart depicting a method 200C for providing adaptive interventions for gastrointestinal and inflammatory health conditions, in accordance with one embodiment.
  • method 200C begins at BEGIN 238, and method flow proceeds to operation 240.
  • operation 240 an interface between a device and a user is established.
  • method flow proceeds to operation 242.
  • a set of signals associated with a gastrointestinal (GI) and/or inflammatory health condition of the user is received from the interface, wherein the set of signals encodes physiological data, behavioral data, environmental stress data, emotional data, and cognitive data of the user.
  • GI gastrointestinal
  • a characterization of the GI and/or inflammatory health condition is determined upon processing the set of signals with a model.
  • method flow proceeds to operation 246.
  • content of a treatment comprising a set of components is modulated, wherein the set of components comprises a subset of cognitive behavioral therapy (CBT) components for improving a state of the user.
  • CBT cognitive behavioral therapy
  • method flow proceeds to operation 248.
  • the treatment is administered to the user.
  • method flow proceeds to END operation 250, and the method 200C for providing adaptive interventions for gastrointestinal and inflammatory health conditions is exited to await new instructions
  • the methods 200A, 200B, and/or 200C can further include operations for detecting performance of activities associated with the intervention regimen, by the patient; reinforcing user performance or engagement with the intervention regimen; determining undesired levels of performance or engagement with the intervention regimen; and driving improved engagement with the intervention.
  • the methods 200A, 200B, and/or 200C can include functionality for detecting performance or non-performance of activities (e.g., based on system engagement, based upon sensor-detected measures of activity, etc.).
  • the methods 200A, 200B, and/or 200C can include functionality for reinforcing performance through provision of various rewards (e.g., rests, rewards of monetary value, etc.). If the patient does not perform activities appropriately, the methods 200A, 200B, and/or 200C can include functionality for determining causes of non-performance (e.g., non-engaging content, external factors associated with the patient’s life, etc.) and adjust content delivery, provide modified interventions, and/or adjust reinforcement schedules accordingly.
  • causes of non-performance e.g., non-engaging content, external factors associated with the patient’s life, etc.
  • the methods 200 A, 200B, and/or 200C can include functionality for developing and training predictive models for predicting states of the patient during the course of the intervention regimen, in order to improve chances of success in outcomes.
  • the methods 200 A, 200B, and/or 200C can thus include functionality for aggregation of training datasets from various data sources described above, and processing training datasets with one or more types of model architecture in order to improve predictions and/or selection of appropriate modules of the intervention regimen for delivery to the patient.
  • Models associated with the methods 200A, 200B, and/or 200C can be defined within architecture of computing systems described above, and include elements for statistical analysis of data and/or machine learning.
  • input to a machine learning module comprises one or more textual words, phrases, or lengthier strings.
  • the input comprises various data elements, such as numerical values corresponding to user responses to a series of questions in a questionnaire (e.g., ranking various symptom severities on a scale).
  • one or more output values of a machine learning module comprise values representing a classification of a particular condition of a user.
  • machine learning modules implementing machine learning techniques are trained, for example using curated and/or manually annotated datasets. Such training may be used to determine various parameters of machine learning algorithms implemented by a machine learning module, such as weights associated with layers in neural networks.
  • machine learning module may receive feedback, e.g., based on user review of accuracy, and such feedback may be used as additional training data, for example to dynamically update the machine learning module.
  • a trained machine learning module is a classification algorithm with adjustable and/or fixed (e.g., locked) parameters, e.g., a random forest classifier.
  • two or more machine learning modules may be combined and implemented as a single module and/or a single software application.
  • two or more machine learning modules may also be implemented separately, e.g., as separate modules or applications.
  • a machine learning module may be software and/or hardware.
  • a machine learning module may be implemented entirely as software, or certain functions of a ANN module may be carried out via specialized hardware (e.g., via an application specific integrated circuit (ASIC)).
  • ASIC application specific integrated circuit
  • the method can include: generating a combined dataset upon applying a first set of transformations to an aggregate dataset including physiological data, behavioral data, environmental stress data, emotional data, and cognitive data from a set of users exhibiting a form of the GI and/or inflammatory health condition; collecting a treatment dataset comprising treatment outcome labels (e.g., quantitative or qualitative labels describing efficacy of individual treatment components) associated with the subset of behavioral therapy components applied to the set of users; creating a first training dataset comprising the combined dataset and the treatment dataset; and training the model with the first training dataset.
  • treatment outcome labels e.g., quantitative or qualitative labels describing efficacy of individual treatment components
  • the model can be structured and ultimately refined for receiving data objects associated with at least one of: physiological data, behavioral data, environmental stress data, emotional data, and cognitive data of the user, and returning a set of outputs comprising a selection of treatment subcomponents tagged with efficacy indicators.
  • Statistical analyses and/or machine learning algorithm(s) can be characterized by a learning style including any one or more of: supervised learning (e.g., using back propagation neural networks), unsupervised learning (e.g., K-means clustering), semi-supervised learning, reinforcement learning (e.g., using a Q-learning algorithm, using temporal difference learning, etc.), and any other suitable learning style.
  • supervised learning e.g., using back propagation neural networks
  • unsupervised learning e.g., K-means clustering
  • semi-supervised learning e.g., reinforcement learning (e.g., using a Q-learning algorithm, using temporal difference learning, etc.), and any other suitable learning style.
  • any algorithm(s) can implement any one or more of: a regression algorithm, an instance-based method (e.g., k-nearest neighbor, learning vector quantization, selforganizing map, etc.), a regularization method, a decision tree learning method (e.g., classification and regression tree, chi-squared approach, random forest approach, multivariate adaptive approach, gradient boosting machine approach, etc.), a Bayesian method (e.g., naive Bayes, Bayesian belief network, etc.), a kernel method (e.g., a support vector machine, a linear discriminate analysis, etc.), a clustering method (e.g., k-means clustering), an associated rule learning algorithm (e.g., an Apriori algorithm), an artificial neural network model (e.g., a back- propagation method, a Hopfield network method, a learning vector quantization method, etc.), a deep learning algorithm (e.g., a Boltzmann machine, a
  • FIG. 9A, FIG. 9B, FIG. 9C, and FIG. 9D are screenshots of several portions of an exemplary GUI for a system for treating gastrointestinal and/or inflammatory health conditions using digital therapeutics, according to one or more embodiments. Screenshots in FIG. 9A, FIG. 9B, FIG. 9C, and FIG. 9D show a GUI in an initial state, corresponding to a starting point for a user that has just begun to use the system.
  • FIG. 9 A shows a home screen that provides user access to an initial, first, lesson module.
  • a selectable icon 902 representing the initial lesson module may be displayed, which a user may select to begin.
  • FIG. 9B shows another screen of a GUI, through which a user may track their progress through a sequence of interactive lesson modules.
  • lesson modules are grouped into sub-sequences referred to as sessions, with each session comprising lessons that are related, e.g., thematically.
  • FIG. 9B shows a first icon 904a representing a first session directed to symptoms and stress, a second icon 904b representing a second session comprising lessons that introduce a user to tools for managing symptoms, and a third icon 904c representing a third session comprising lessons related to managing eating patterns.
  • a GUI restricts user access to subsequent sessions (i.e., sessions two and above in the example of FIG.
  • a GUI may include visual cues indicating which sessions are accessible and which are locked including, for example, graphical indicators (e.g., a picture of a lock), shading, colorization, etc., as shown in FIG. 9B.
  • FIG. 9C in some embodiments, certain lesson modules are associated with practice modules that allow a user to use and practice particular skills on a regular and/or as needed basis, outside of a sequence of lesson modules. In some embodiments, access to a particular practice module is restricted until the user has completed a lesson module with which it is associated. For example, as shown in FIG.
  • lesson modules may also be associated with resources, such as, but not limited to, video guides to particular breathing techniques and/or relevant articles.
  • access to resources may also be restricted such that a particular resource is locked (e.g., inaccessible) until a lesson module with which it is associated has been completed.
  • a GUI may also comprise a stored profile of the user.
  • a user profile may be populated via various lesson modules that solicit input from the user, for example regarding personal characteristics, thoughts and feelings, symptom logging, identification of stressors, stress level tracking, and completion of diagnostic assessments aimed at characterizing their condition.
  • various patient reported outcome instruments which, for example, measure condition symptom severity, quality of life, etc., can be used.
  • a patient/user suffering from IBS symptoms may complete an IBS symptom severity scale (IBS-SSS) evaluation, and/or other evaluations based on other patient reported outcome instruments, described in further detail above.
  • IBS-SSS IBS symptom severity scale
  • FIG. 10 A, FIG. 10B, FIG. 10C, and FIG. 10D are screenshots of example user interactions with an initial lesson module for content tailored for a patient with IBS, according to one or more embodiments.
  • FIG. 10 A a user may select icon 1002 representing the initial lesson module from their home-screen to begin the initial lesson module.
  • a user may step through content of a lesson module by tapping a selectable graphical button 1004, until they have viewed all screens comprising all graphical content and widgets of the lesson module.
  • FIG. 10D in some embodiments, a user may be presented with a final screen that provides an indication that they have completed a particular lesson module. The user may select a graphical button 1006 to confirm completion of the particular lesson module. Following completion of an initial lesson module, the user may progress onto a subsequent one.
  • FIG. 11 A and FIG. 1 IB are screenshots showing gate features of an exemplary GUI for a system for treating gastrointestinal and/or inflammatory health conditions using prescription digital therapeutics, in accordance with one or more embodiments.
  • progression onto a next lesson module is not necessarily instantaneous and/or direct. Instead, as described above, gate features may be used to introduce friction and/or to control a rate of progression from one lesson module to a next.
  • FIG. 11 A shows an example soft-gate, wherein a user is not fully prevented from beginning a second lesson module, but is encouraged to delay moving on, and required to provide additional input to do so.
  • Inter-lesson gate screen 1102 represents a soft-gate, and includes graphical content prompting the user to delay progressing onto the second lesson until the next day.
  • Example screen 1104 also includes delay button 1104a and continue button 1104b graphical widgets, wherein selection of the delay button 1104a graphical widget returns the user to the homescreen.
  • delay button 1104a and continue button 1104b graphical widgets are rendered graphically so as to visually emphasize delay button 1104a, and de-emphasize continue button 1104b, thereby encouraging the user to delay moving on to the second lesson module.
  • a soft-gate is based on time-relationship criteria with respect to a user’s time of completion of the first lesson module.
  • a soft-gate is used to encourage a user to wait until a next day to begin the second lesson module.
  • inter-lesson gate screen 1106 represents a hard-gate and does not allow for continued user progression onto the second lesson module. Instead, inter-lesson gate screen 1106 includes graphical content that encourages the user to take a break and practice particular behavioral skills via a practice module identified by graphical icon 506a.
  • graphical icon 1108a is a graphical widget - e.g., a selectable graphical button.
  • a graphical icon 1108a provides a link to a particular practice module, such that user selection of the graphical icon 1108a causes initiation (e.g., display) of a particular practice module to which it links (e.g., a symptom diary practice module, as shown in the example screen of FIG.1 IB, or other practice modules).
  • an inter- lesson gate screen may comprise a graphical widget that returns a user to a home screen.
  • inter-lesson gate screen 1106 comprises graphical widget 1108b, displaying text “Okay,” whereupon a user selection of graphical widget 1108b, they are returned to a home screen shown.
  • FIG. 12A, FIG. 12B, FIG. 12C, and FIG. 12D are screenshots of an exemplary GUI for a symptom diary lesson module, according to one or more embodiments.
  • a sequence of interactive lesson modules may include a symptom diary lesson module that introduces and familiarizes a user with techniques for tracking their GI and/or inflammatory health condition symptoms.
  • technologies described herein provide a convenient GUI that can (e.g., be demonstrated and/or designed to) facilitate user tracking and/or monitoring of their GI and/or inflammatory health symptoms on a regular basis.
  • a tracking GUI may be included within a same system that provides, and controls user progression through interactive lesson modules, for example as a symptom diary practice module associated with a symptom diary lesson module.
  • access to a symptom diary practice module may be unlocked following completion of a symptom diary lesson module by the user, for example, as shown in FIG. 12C.
  • a selectable icon 1202 representing, and providing access to, the symptom diary practice module may be displayed on a user home-screen.
  • FIG. 13 A, FIG. 13B, FIG. 13C, and FIG. 13D are screenshots of example user interactions with a symptom diary practice module, in accordance with one or more embodiments.
  • a symptom diary practice module may be a stand-alone module, or it may be part of a different module, such as, but not limited to, the introduction and education module discussed above.
  • a user may use graphical widgets to provide input associated with one or more aspects of their disease, disorder, and/or condition.
  • patient input include, but are not limited to, rating pain and stress on a scale (FIG. 13B), providing ratings characterizing additional symptoms specific to their disease, disorder, and/or condition (FIG. 13C) and providing information characterizing their daily meals (FIG. 13D).
  • FIG. 14A, FIG. 14B, FIG. 14C, and FIG. 14D are screenshots of an exemplary GUI for introducing a personal model lesson module, in accordance with one or more embodiments.
  • a personal model lesson module may be a stand-alone module, or it may be part of a different module, such as, but not limited to, the physical illness narrative module discussed above.
  • a sequence of interactive lesson modules includes a personal model lesson module that allows a user to identify cycles of behaviors, thoughts, emotions, and stressors that influence symptoms associated with their particular condition (e.g., from which they are suffering).
  • a personal model lesson module is used to implement, via a GUI, a structured process for conveniently soliciting user input of specific counter-productive behaviors, unhelpful thoughts, and negative emotions that they identify, e.g., in their life and/or as associated with their particular condition.
  • a particular condition from which the user is suffering is a GI and/or inflammatory health condition, such as, but not limited to, IBS.
  • a personal model lesson module introduces a user to process for creating a personal model, for example so as to orient them and provide content designed to offer helpful motivation.
  • graphical content representing educational material is displayed to a user, for example to introduce them to concept of vicious cycles, and explain how symptoms, stress, and pain can create a feedback loop.
  • graphical content corresponding to shared user experiences and/or testimonials is displayed. For example, as shown in FIG. 14D, a user may be prompted to read about another user’s experiences with their GI and/or inflammatory health condition and guided behavioral therapy approaches such as those described herein.
  • a user may view exemplary personal models created by and shared by others.
  • Other lesson modules for example any lesson modules described herein and/or additional lesson modules, providing for development of other behavioral therapy skills provided via the technologies described herein may also include content comprising patient experiences and/or testimonials.
  • FIG. 15A, FIG. 15B, FIG. 15C, and FIG. 15D are screenshots of an exemplary GUI for a personal model lesson module, according to one or more embodiments.
  • a personal model lesson module may be a stand-alone module, or it may be part of a different module, such as, but not limited to, the physical illness narrative module discussed above.
  • a personal model lesson module may retrieve stored information, previously input by a user. For example, in various embodiments, a user may have previously provided input identifying causes and/or stressors that impact their particular GI and/or inflammatory health condition, and previously input user identifications of causes and stressors that impact the user’s GI and/or inflammatory health condition may be retrieved and displayed, as shown in FIG. 15B. In some embodiments, a user provides input corresponding to causes and/or stressors associated with their particular GI and/or inflammatory health condition via a personal model lesson module. In some embodiments, a user may be provided with a graphical list of selectable elements.
  • the user is prompted to select a predefined number of counter-productive behaviors, as shown in FIG. 15C.
  • FIG. 15D in some embodiments, for each user selected counter-productive behavior, the user is prompted to select one or more unhelpful thoughts related to the counter-productive behavior.
  • unhelpful thoughts are selected from a list of pre-defined thoughts.
  • a user may provide free-form textual input, for example via a text box.
  • negative emotions are selected from a list of pre-defined emotions.
  • a user may provide free-form textual input, for example via a text box.
  • FIG. 16 A, 16B, and 16C are screenshots of an exemplary personal model graphical representation, according to one or more embodiments.
  • a personal model graphical representation comprises text corresponding to user selected counter-productive behavior(s), unhelpful thought(s), and negative emotion(s), superimposed on a flow diagram illustrating links between each other, as shown in FIG. 16A and FIG. 16B.
  • a personal model graphical representation comprises text corresponding to causes and/or stressors of symptoms, previously input by the user and retrieved via the personal model lesson module and/or input within the personal model lesson module, as described herein.
  • a personal model graphical representation is rendered to have a form factor fitting one or more mobile device screens.
  • a personal model graphical representation can be rendered in a narrow, rectangular format, allowing a user to scroll through the rendered diagram to view its content.
  • a personal model graphical representation can be displayed as a zoom-able diagram, such that a user may zoom in and out to view portions of the diagram.
  • a personal model graphical representation can be displayed so as to allow a user to navigate through its content by panning, for example in a two-dimensional fashion.
  • FIG. 17A, FIG. 17B, FIG. 17C, and FIG. 17D are screenshots of an exemplary GUI for a reflections section of a personal model lesson module, according to one or more embodiments.
  • a personal model lesson module includes graphical content prompting a user to review their personal model.
  • a series of questions e.g., from a predefined list of questions, e.g., based on a therapeutic protocol
  • a series of questions are displayed and presented to the user along with their personal model graphical representation, prompting the user to consider their selections, identify links, consider possible changes in their behavior that could be implemented to address their symptoms, and the like.
  • FIG. 17A, FIG. 17B, and FIG. 17C a sequence of user questions are presented.
  • Graphical content including passages of rendered text, mimicking conversation with a therapist can be displayed.
  • encouraging graphical content is displayed, and the user is returned to a home screen.
  • FIG. 18A, FIG. 18B, FIG. 18C, and FIG. 18D are screenshots of an exemplary GUI for a symptom management lesson module, according to one or more embodiments.
  • a symptom management lesson module may be a stand-alone module, or it may be part of a different module, such as, but not limited to, the pain management module discussed above.
  • FIG. 18 A, FIG. 18B, FIG. 18C, and FIG. 18D show an example symptom management lesson module and an associated symptom management goals practice module.
  • a symptom management goals practice module can be unlocked and made accessible to the user, as shown in FIG. 18B.
  • FIG. 18C and FIG. 18D a user may access a symptom management goals module to create goals to manage their GI and/or inflammatory health condition symptoms.
  • a user may, e.g., regularly, use a goals module to set goals such as goals pertaining to a regular timing and/or type of food and/or activity (e.g., physical exercise, meditation, breathing and/or relaxation exercises, reflection exercise, e.g., including skills introduced via lesson modules and/or practicable via interaction with one or more other practice modules, such as keeping a regular symptom diary, etc.).
  • a goals module may provide for setting goals pertaining to medication adherence.
  • FIG. 19A, FIG. 19B, FIG. 19C, and FIG. 19D are screenshots of an exemplary GUI for a unhelpful thought pattern lesson module, according to one or more embodiments.
  • an unhelpful thought pattern lesson module may be a stand-alone module, or it may be part of a different module, such as, but not limited to, the cognitive restructuring and flexibility module discussed above.
  • FIG. 19A, FIG. 19B, FIG. 19C, and FIG. 19D show an example unhelpful thought pattern lesson module and an associated thought record practice module.
  • a thought record practice module can be unlocked and made accessible to the user.
  • a user may access a thought record practice module to create thought entries tracking their thoughts and associated activities and feelings.
  • completed sessions may be indicated visually to a user.
  • completion of certain lesson modules unlocks various associated practice modules, which are then made accessible to the user via a screen of a GUI.
  • completion of lesson modules may cause population of portions of a user profile, which a user may review via a GUI.
  • completion of a user personal model module as described herein provides for creation of a personal model that identifies a particular user’s individual vicious cycle of related stressors, behaviors, emotions, and thoughts.
  • the data corresponding to a previously created personal model is stored and may be rendered for review and reflection by a user, via a profile screen.
  • interactive lesson modules, associated practice modules, user profile content, and the like may include a variety of other lesson modules, additionally or alternatively to those described herein.
  • various lesson modules and content thereof as described herein may be combined with other content, for example from other lesson modules described herein.
  • embodiments of the present disclosure provide a technical solution to the technical problem of effectively, efficiently, and remotely treating gastrointestinal and inflammatory health conditions using prescription digital therapeutics in combination with other therapies in order to ensure that patients receive adequate care, support, and treatment for their GI and/or inflammatory health condition.
  • the inventions covered by the system and method disclosed herein can confer several benefits over conventional systems and methods, and such inventions are further implemented into many practical applications related to improvement of user health.
  • a computing system implemented method for treating gastrointestinal and inflammatory health conditions using prescription digital therapeutics in combination with other therapies comprises: providing a patient with a user interface to a therapeutics system; performing, by the therapeutics system, a pre-assessment of a patient exhibiting one or more health condition symptoms; generating, by the therapeutics system, patient profile and pre-assessment data based on the results of the patient pre-assessment; processing, by the therapeutics system, the patient profile and pre-assessment data to generate patient condition data; and processing, by the therapeutics system, the patient profile and preassessment data and the patient condition data to generate a personalized intervention regimen for the patient wherein the personalized intervention regimen defines a combination of first therapeutic treatment components and second therapeutic treatment components.
  • the computing system implemented method further comprises administering one or more of the first therapeutic treatment components to the patient through the user interface of the therapeutics system according to the personalized intervention regimen generated for the patient; administering one or more of the second therapeutic treatment components to the patient in combination with the one or more first therapeutic treatment components according to the personalized intervention regimen generated for the patient; monitoring the patient’s interactions with the first therapeutic treatment components and the second therapeutic treatment components to generate patient interaction data representing the patient’s interactions with the first and second therapeutic treatment components; processing, by the therapeutics system, the patient interaction data to generate intervention modification data representing recommended modifications to the patient’s personalized intervention regimen; at least partly based on the intervention modification data, dynamically modifying aspects of the patient’s personalized intervention regimen to generate a modified personalized intervention regimen for the patient; and administering one or more of the first therapeutic treatment components in combination with one or more of the second therapeutic treatment components according to the modified personalized intervention regimen for the patient.
  • the therapeutics system is a prescription digital therapeutics (PDT) system.
  • the patient health condition symptoms are associated with one or more of: a gastrointestinal (GI) health condition; and an inflammatory health condition.
  • performing a pre-assessment of a patient includes utilizing surveying tools derived from one or more patient reported outcome instruments selected from the group of patient reported outcome instruments consisting of: a Functional Bowel Disorder Severity Index (FBDSI) instrument; a Gastrointestinal Symptom Rating Scale - IBS (GSRS- IBS) instrument; an IBS-Adequate Relief (IBS-AR) instrument; an IBS Global Assessment of Improvement Scale (IBS-GAI) instrument; an IBS Symptom Severity Score (IBS-SSS) instrument; an IBS Quality of Life (IBS-QOL) instrument; a Patient Reported Outcome Measurement Information System (PROMIS) instrument; a Visual Analogue Scale for Irritable Bowel Syndrome (VA
  • performing a pre-assessment of a patient includes utilizing non-survey data obtained from one or more devices selected from the group of devices consisting of: electronic health record-associated devices; torso-coupled devices, wearable devices; ingestible devices; implanted devices; smart-pill devices; smart toilet devices; location monitoring devices; and social networking tracking devices.
  • generating the patient profile and pre-assessment data includes obtaining one or more of: patient demographics data; patient electronic health record data; patient physiological health data; patient psychological health data; patient condition data; patient symptoms data; patient medications data; patient illness narrative data; patient goals data; and patient preferences data.
  • generating the patient condition data includes of one or more of identifying the patient’s condition as a gastrointestinal (GI) health condition; identifying a subtype of the patient’s gastrointestinal (GI) health condition; identifying a severity of the patient’s gastrointestinal (GI) health condition; identifying the patient’s condition as an inflammatory health condition; identifying a subtype of the patient’s inflammatory health condition; and identifying a severity of the patient’s inflammatory health condition.
  • GI gastrointestinal
  • GI gastrointestinal
  • GI gastrointestinal
  • generating a personalized intervention regimen includes one or more of processing, through the therapeutics system, the patient profile and pre-assessment data and the patient condition data to determine a first therapeutic treatment to be administered to the patient; defining a first plurality of therapeutic components associated with the first therapeutic treatment; processing, through the therapeutics system, the patient profile and preassessment data and the patient condition data to select one or more of the first plurality of therapeutic components to be administered to the patient; generating first therapeutic treatment component data representing the selected one or more of the first plurality of therapeutic components; defining a first plurality of therapeutic protocols to be utilized in administration of the components represented by the first therapeutic treatment component data; processing, through the therapeutics system, the patient profile and pre-assessment data and the patient condition data to select one or more of the first plurality of therapeutic protocols to utilize in administration of the components represented by the first therapeutic treatment component data; and generating first therapeutic treatment protocol data representing the selected one or more of the first plurality of therapeutic protocols to utilize in administration of the components represented by the first therapeutic treatment component data;
  • generating a personalized intervention regimen further includes one or more of processing, through the therapeutics system, the patient profile and preassessment data and the patient condition data to determine a second therapeutic treatment to be administered to the patient in combination with the first therapeutic treatment; defining a second plurality of therapeutic components associated with the second therapeutic treatment; processing, through the therapeutics system, the patient profile and pre-assessment data and the patient condition data to select one or more of the second plurality of therapeutic components to be administered to the patient; generating second therapeutic treatment component data representing the selected one or more of the second plurality of therapeutic components; defining a second plurality of therapeutic protocols to be utilized in administration of the components represented by the second therapeutic treatment component data; processing, through the therapeutics system, the patient profile and pre-assessment data and the patient condition data to select one or more of the second plurality of therapeutic protocols to utilize in administration of the components represented by the second therapeutic treatment component data; and generating second therapeutic treatment protocol data representing the selected one or more of the second plurality of therapeutic protocols to utilize in administration of the components represented by the second therapeutic
  • generating a personalized intervention regimen further includes one or more of: generating, by the therapeutics system, a personalized intervention regimen for the patient, wherein the personalized intervention regimen for the patient defines the first therapeutic treatment component data to be administered to the patient according to the first therapeutic treatment protocol data in combination with the second therapeutic treatment component data to be administered to the patient according to the second therapeutic treatment protocol data.
  • the first therapeutic treatment is a guided behavioral therapeutic treatment, further wherein the guided behavioral therapeutic treatment is administered remotely through a user interface of the therapeutics system.
  • the guided behavioral therapeutic treatment includes components of therapies selected from the group of therapies consisting of: psychotherapy; cognitive behavioral therapy (CBT); acceptance commitment therapy (ACT); dialectical behavioral therapy (DBT); exposure therapy; mindfulness-based cognitive therapy (MCBT); hypnotherapy; experiential therapy; and psychodynamic therapy.
  • the second type of therapeutic treatment is a non-behavioral therapeutic treatment including components of non-behavioral therapeutic treatments selected from the group of non-behavioral therapeutic treatments consisting of: treatments utilizing one or more pharmaceutical compositions; treatments utilizing one or more nutraceutical compositions; treatments utilizing one or more medical devices; treatments utilizing one or more physical activities; treatments utilizing one or more mind-body interventions; and treatments utilizing whole system medicine.
  • monitoring the patient’s interactions with the first therapeutic treatment components and the second therapeutic treatment components includes utilizing surveying tools derived from one or more patient reported outcome instruments selected from the group of patient reported outcome instruments consisting of a Functional Bowel Disorder Severity Index (FBDSI) instrument; a Gastrointestinal Symptom Rating Scale - IBS (GSRS-IBS) instrument; an IBS- Adequate Relief (IBS-AR) instrument; an IBS Global Assessment of Improvement Scale (IBS-GAI) instrument; an IBS Symptom Severity Score (IBS-SSS) instrument; an IBS Quality of Life (IBS-QOL) instrument; a Patient Reported Outcome Measurement Information System (PROMIS) instrument; a Visual Analogue Scale for Irritable Bowel Syndrome (VAS-IBS); a work and social adjustment scale (WSAS)-derived instrument; a clinical disease activity measurement instrument; a PHQ-9 patient health questionnaire; a GAD-7 anxiety disorder questionnaire; and a pain assessment questionnaire.
  • FBDSI Functional Bowel Disorder Sever
  • monitoring the patient’ s interactions with the first therapeutic treatment components and the second therapeutic treatment components includes utilizing non-survey data obtained from one or more devices selected from the group of devices consisting of electronic health record-associated devices; torso-coupled devices; wearable devices; ingestible devices; implanted devices; smart-pill devices; smart toilet devices; location monitoring devices; and social networking tracking devices.
  • monitoring the patient’ s interactions with the first therapeutic treatment components and the second therapeutic treatment components includes obtaining patient data including one or more of patient physiological health data; patient psychological health data; patient condition data; patient symptoms data; patient medications data; patient medication adherence data; patient progress report data; patient system usage data; patient device usage data; patient social networking behavior data; patient voice data; patient textual data; patient activity data; patient location data; patient motion data; and patient biometric data.
  • the patient’ s interactions with the first therapeutic treatment components and the second therapeutic treatment components are monitored remotely, in near- real time, contemporaneously with administration of one or more of the first therapeutic treatment; and the second therapeutic treatment.
  • a request for approval of the intervention modification data is communicated remotely to one or more of a health care practitioner associated with the patient; the patient; a relative of the patient; a caregiver of the patient; and a third party associated with the patient.
  • dynamically modifying aspects the patient’s personalized intervention regimen includes one or more of: adjusting the order of administration of the behavioral therapy components; adjusting the order of administration of the non-behavioral therapy components; adjusting the frequency of administration of the behavioral therapy components; adjusting the frequency of administration of the non-behavioral therapy components; adjusting the mode of administration of the behavioral therapy components; adjusting the mode of administration of the non-behavioral therapy components; adjusting the content of the behavioral therapy components; adjusting the content of the non-behavioral therapy components; adjusting the content size of the behavioral therapy components; adjusting the dosage of the non-behavioral therapy components; adjusting the presentation of the behavioral therapy components; adjusting the layout of the behavioral therapy components; updating the patient’s electronic health records; updating the patient’s personal health records; updating the patient’s open medical records; and increasing personalization of the intervention regimen.
  • the patient’s personalized intervention regimen is modified remotely, in near-real time, contemporaneously with administration of one or more of: the first therapeutic treatment; and the second therapeutic treatment.
  • a method for providing a prescription digital therapeutics (PDT) system for remotely administering guided behavioral therapy in combination with other types of gastrointestinal (GI) and/or inflammatory health conditions comprises: providing a patient with a therapeutics system; performing a pre-assessment of a patient exhibiting one or more health condition symptoms; generating patient profile and pre-assessment data based on the results of the patient pre-assessment; processing the patient profile and pre-assessment data to generate patient condition data; processing the patient profile and pre-assessment data and the patient condition data to generate a personalized intervention regimen for the patient wherein the personalized intervention regimen defines a combination of first therapeutic treatment components and second therapeutic treatment components; administering one or more of the first therapeutic treatment components to the patient according to the personalized intervention regimen generated for the patient; administering one or more of the second therapeutic treatment components to the patient in combination with the one or more first therapeutic treatment components according to the personalized intervention regimen generated for the patient; monitoring the patient’s interactions with the first therapeutic treatment components and the second therapeutic
  • a system comprises one or more processors and one or more physical memories, the one or more physical memories having stored therein data; a patient computing system; a user interface provided to the patient computing system, the user interface providing access to a therapeutics system; a therapeutics system which provides remotely located patients and caretakers access to the therapeutics system, the therapeutics system using the one or more processors and one or more physical memories to perform the above described methods/processes.
  • the systems and methods disclosed herein allow behavioral therapy to be administered to patients suffering from gastrointestinal (GI) and/or inflammatory health conditions in a convenient and flexible, yet structured fashion, via a prescription digital therapeutics (PDT) system in combination with one or more non-behavioral therapies.
  • the invention(s) can employ non-traditional systems and methods for providing interventions to patients exhibiting symptoms associated with one or more health conditions.
  • the invention(s) can deliver psychological -based interventions, such as behavioral therapy-based interventions and other interventions (described in more detail above) to users/patients, by way of a platform having components implemented in a mobile device environment and/or other computer or internet-based architecture.
  • prescription digital therapeutics (PDT) technologies may be used to administer behavioral therapies in combination with a variety of non- behavioral therapies in a controlled fashion, as treatment for one or more conditions described herein.
  • the invention(s) use components of the platform to process large amounts of user data, remotely deliver personalized interventions, and remotely monitor user interactions with such interventions in near real-time in a manner that cannot be practically implemented by the human mind. [ 0424 ] Consequently, the embodiments disclosed herein are not an abstract idea, and are well-suited to a wide variety of practical applications.
  • the disclosed method and system for effectively, efficiently, and remotely administering guided behavioral therapy in combination with other types of GI and/or inflammatory therapies requires specific processes that utilize components of the platform disclosed herein to process user data, deliver interventions, and monitor user interactions with such interventions, and as such, does not encompass, embody, or preclude other forms of innovation in the area of healthcare technologies.
  • the disclosed embodiments of systems and methods for dynamically, efficiently, and remotely treating gastrointestinal and inflammatory health conditions using prescription digital therapeutics are not abstract ideas for at least several reasons.
  • portions of one or more of the process steps and/or operations and/or instructions can be re-grouped as portions of one or more other of the process steps and/or operations and/or instructions discussed herein. Consequently, the particular order and/or grouping of the process steps and/or operations and/or instructions discussed herein do not limit the scope of the invention as claimed below.
  • the present invention also relates to an apparatus or system for performing the operations described herein.
  • This apparatus or system may be specifically constructed for the required purposes, or the apparatus or system can comprise a system selectively activated or configured/reconfigured by a computer program stored on a non-transitory computer readable medium for carrying out instructions using a processor to execute a process, as discussed or illustrated herein that can be accessed by a computing system or other device.
  • the present invention is well suited to a wide variety of computer network systems operating over numerous topologies.
  • the configuration and management of large networks comprise storage devices and computers that are communicatively coupled to similar or dissimilar computers and storage devices over a private network, a LAN, a WAN, a private network, or a public network, such as the Internet.

Landscapes

  • Health & Medical Sciences (AREA)
  • Life Sciences & Earth Sciences (AREA)
  • Engineering & Computer Science (AREA)
  • Public Health (AREA)
  • Medical Informatics (AREA)
  • General Health & Medical Sciences (AREA)
  • Biomedical Technology (AREA)
  • Pathology (AREA)
  • Physics & Mathematics (AREA)
  • Surgery (AREA)
  • Biophysics (AREA)
  • Animal Behavior & Ethology (AREA)
  • Molecular Biology (AREA)
  • Heart & Thoracic Surgery (AREA)
  • Veterinary Medicine (AREA)
  • Primary Health Care (AREA)
  • Epidemiology (AREA)
  • Psychiatry (AREA)
  • Artificial Intelligence (AREA)
  • Databases & Information Systems (AREA)
  • Data Mining & Analysis (AREA)
  • Hospice & Palliative Care (AREA)
  • Physiology (AREA)
  • Gastroenterology & Hepatology (AREA)
  • Evolutionary Computation (AREA)
  • Fuzzy Systems (AREA)
  • Mathematical Physics (AREA)
  • Computer Vision & Pattern Recognition (AREA)
  • Signal Processing (AREA)
  • Child & Adolescent Psychology (AREA)
  • Developmental Disabilities (AREA)
  • Educational Technology (AREA)
  • Psychology (AREA)
  • Social Psychology (AREA)
  • Chemical & Material Sciences (AREA)
  • Bioinformatics & Cheminformatics (AREA)
  • Medicinal Chemistry (AREA)
  • Human Computer Interaction (AREA)
  • Endocrinology (AREA)
  • Computer Networks & Wireless Communication (AREA)

Abstract

Un système de thérapie numérique sur prescription (PDT) est fourni à des patients/utilisateurs souffrant d'états de santé gastro-intestinaux (GI) et/ou inflammatoires, le système de PDT permettant d'administrer une thérapie comportementale guidée de manière pratique et flexible, mais néanmoins structurée, en association avec une ou plusieurs thérapies non comportementales. Les technologies de thérapie comportementale guidée peuvent être basées au moins en partie sur des techniques de thérapie comportementale cognitive (CBT) pour permettre le développement de compétences pour traiter des maladies, troubles et/ou états gastro-intestinaux (GI) et/ou inflammatoires, et pour gérer le stress et/ou d'autres symptômes psychologiques associés à de tels maladies, troubles et/ou états. Des thérapies non comportementales comprennent l'administration de compositions pharmaceutiques, de compositions nutraceutiques et/ou d'autres thérapies associées à divers dispositifs médicaux. Les interactions du patient avec le système de PDT sont surveillées en temps quasi réel pour modifier en continu un ou plusieurs schémas d'intervention personnalisés associés à l'association de thérapies.
PCT/US2021/054984 2020-10-22 2021-10-14 Méthodes et systèmes pour traiter des états de santé gastro-intestinaux et inflammatoires faisant appel à des thérapies numériques sur prescription en association avec d'autres thérapies WO2022086784A1 (fr)

Applications Claiming Priority (4)

Application Number Priority Date Filing Date Title
US202063104322P 2020-10-22 2020-10-22
US63/104,322 2020-10-22
US17/499,576 US20220028541A1 (en) 2019-06-27 2021-10-12 Methods and systems for treating gastrointestinal and inflammatory health conditions using prescription digital therapeutics in combination with other therapies
US17/499,576 2021-10-12

Publications (1)

Publication Number Publication Date
WO2022086784A1 true WO2022086784A1 (fr) 2022-04-28

Family

ID=81291130

Family Applications (1)

Application Number Title Priority Date Filing Date
PCT/US2021/054984 WO2022086784A1 (fr) 2020-10-22 2021-10-14 Méthodes et systèmes pour traiter des états de santé gastro-intestinaux et inflammatoires faisant appel à des thérapies numériques sur prescription en association avec d'autres thérapies

Country Status (1)

Country Link
WO (1) WO2022086784A1 (fr)

Citations (4)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
WO2007130491A2 (fr) * 2006-05-02 2007-11-15 Proteus Biomedical, Inc. Régimes thérapeutiques personnalisés pour un patient
US20100169409A1 (en) * 2008-08-04 2010-07-01 Fallon Joan M Systems and methods employing remote data gathering and monitoring for diagnosing, staging, and treatment of parkinsons disease, movement and neurological disorders, and chronic pain
US20110077971A1 (en) * 2000-01-11 2011-03-31 Surwit Richard S Apparatus and Methods for Monitoring and Modifying Anticoagulation Therapy of Remotely Located Patients
US9536052B2 (en) * 2011-10-28 2017-01-03 Parkland Center For Clinical Innovation Clinical predictive and monitoring system and method

Patent Citations (4)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US20110077971A1 (en) * 2000-01-11 2011-03-31 Surwit Richard S Apparatus and Methods for Monitoring and Modifying Anticoagulation Therapy of Remotely Located Patients
WO2007130491A2 (fr) * 2006-05-02 2007-11-15 Proteus Biomedical, Inc. Régimes thérapeutiques personnalisés pour un patient
US20100169409A1 (en) * 2008-08-04 2010-07-01 Fallon Joan M Systems and methods employing remote data gathering and monitoring for diagnosing, staging, and treatment of parkinsons disease, movement and neurological disorders, and chronic pain
US9536052B2 (en) * 2011-10-28 2017-01-03 Parkland Center For Clinical Innovation Clinical predictive and monitoring system and method

Non-Patent Citations (1)

* Cited by examiner, † Cited by third party
Title
DANG AMIT, ARORA DIMPLE, RANE PAWAN: "Role of digital therapeutics and the changing future of healthcare", JOURNAL OF FAMILY MEDICINE AND PRIMARY CARE, ACADEMY OF FAMILY PHYSICIANS OF INDIA / MEDKNOW, INDIA, vol. 9, no. 5, 1 January 2020 (2020-01-01), India , pages 2207, XP055924091, ISSN: 2249-4863, DOI: 10.4103/jfmpc.jfmpc_105_20 *

Similar Documents

Publication Publication Date Title
US20200411185A1 (en) Adaptive interventions for gastrointestinal health conditions
Reyes et al. Factors influencing diabetes self-management among medically underserved patients with type II diabetes
Ng et al. Self-determination theory applied to health contexts: A meta-analysis
US20220028529A1 (en) Methods and systems for treating gastrointestinal and inflammatory health conditions using prescription digital therapeutics
US20220028541A1 (en) Methods and systems for treating gastrointestinal and inflammatory health conditions using prescription digital therapeutics in combination with other therapies
US20220028528A1 (en) Methods and systems for treating health conditions using prescription digital therapeutics
Matthews et al. An education programme influencing health professionals to recommend exercise to their type 2 diabetes patients–understanding the processes: a case study from Oxfordshire, UK
Woodruff et al. An interpretive description of women’s experience in coordinated, multidisciplinary treatment for an eating disorder
Hill et al. Temperament based therapy with support for anorexia nervosa: a novel treatment
WO2022086781A1 (fr) Méthodes et systèmes pour le traitement d'états de santé à l'aide de thérapies numériques de prescription
Lungu Computerized trans-diagnostic dialectical behavior therapy skills training for emotion dysregulation
WO2022086784A1 (fr) Méthodes et systèmes pour traiter des états de santé gastro-intestinaux et inflammatoires faisant appel à des thérapies numériques sur prescription en association avec d'autres thérapies
Potter et al. Physician-authored feedback in a type 2 diabetes self-management app: acceptability study
WO2022086783A1 (fr) Méthodes et systèmes pour traiter des troubles gastro-intestinaux et des états de santé inflammatoires à l'aide de thérapies numériques de prescription
Orte et al. BECOME: A Modular Recommender System for Coaching and Promoting Empowerment in Healthcare
WO2024011105A1 (fr) Méthodes et systèmes de traitement d'acouphènes à l'aide d'agents thérapeutiques numériques
WO2023133575A2 (fr) Méthodes et systèmes de traitement d'états de démangeaison chronique à l'aide d'agents thérapeutiques numériques en combinaison avec d'autres thérapies
WO2023141376A2 (fr) Méthodes et systèmes de traitement d'affections respiratoires à l'aide d'agents thérapeutiques numériques en combinaison avec d'autres thérapies
WO2023133573A1 (fr) Méthodes et systèmes de traitement d'états de douleur chronique à l'aide d'agents thérapeutiques numériques en combinaison avec d'autres thérapies
Jafari Assessing the Feasibility, Acceptability, Preliminary Efficacy, and Anticipated Clinical Practice Implementation of a Mindful Eating Smartphone Application: A Mixed Methods Analysis among Undergraduate Women with Binge Eating and Clinical Experts.
Frates et al. Empowering Behavior Change in Patients: Practical Strategies for the Healthcare Professional
Jans et al. Digital single-session interventions for youth mental health
Makori Improving Self-Management of Diabetes with Culturally Sensitive Interventions
Crouch Lifestyle Behaviors that Contribute to Wellness of Healthy 30–40 Year Olds
De Villiers The observing self as a catalyst for behaviour change and wellbeing: Effective personal informatics system design to promote behaviour change in the changing health paradigm

Legal Events

Date Code Title Description
121 Ep: the epo has been informed by wipo that ep was designated in this application

Ref document number: 21883584

Country of ref document: EP

Kind code of ref document: A1

NENP Non-entry into the national phase

Ref country code: DE

32PN Ep: public notification in the ep bulletin as address of the adressee cannot be established

Free format text: NOTING OF LOSS OF RIGHTS PURSUANT TO RULE 112(1) EPC (EPO FORM 1205A DATED 13/09/2023)

122 Ep: pct application non-entry in european phase

Ref document number: 21883584

Country of ref document: EP

Kind code of ref document: A1