WO2018067585A1 - Système de surveillance à distance de patient - Google Patents

Système de surveillance à distance de patient Download PDF

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Publication number
WO2018067585A1
WO2018067585A1 PCT/US2017/054965 US2017054965W WO2018067585A1 WO 2018067585 A1 WO2018067585 A1 WO 2018067585A1 US 2017054965 W US2017054965 W US 2017054965W WO 2018067585 A1 WO2018067585 A1 WO 2018067585A1
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WO
WIPO (PCT)
Prior art keywords
patient
peri
information
admission
vital sign
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PCT/US2017/054965
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English (en)
Inventor
Anne Lin
Wentai Liu
Yi-kai LO
Peyman Benharash
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The Regents Of The University Of California
The United States Government Represented By The Department Of Veterans Affairs
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Application filed by The Regents Of The University Of California, The United States Government Represented By The Department Of Veterans Affairs filed Critical The Regents Of The University Of California
Publication of WO2018067585A1 publication Critical patent/WO2018067585A1/fr

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Classifications

    • 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
    • A61B5/7271—Specific aspects of physiological measurement analysis
    • A61B5/7275—Determining trends in physiological measurement data; Predicting development of a medical condition based on physiological measurements, e.g. determining a risk factor
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00—Measuring for diagnostic purposes; Identification of persons
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00—Measuring for diagnostic purposes; Identification of persons
    • A61B5/24—Detecting, measuring or recording bioelectric or biomagnetic signals of the body or parts thereof
    • A61B5/316—Modalities, i.e. specific diagnostic methods
    • A61B5/318—Heart-related electrical modalities, e.g. electrocardiography [ECG]
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00—Measuring for diagnostic purposes; Identification of persons
    • A61B5/24—Detecting, measuring or recording bioelectric or biomagnetic signals of the body or parts thereof
    • A61B5/316—Modalities, i.e. specific diagnostic methods
    • A61B5/318—Heart-related electrical modalities, e.g. electrocardiography [ECG]
    • A61B5/332—Portable devices specially adapted therefor
    • 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
    • G16H40/00—ICT specially adapted for the management or administration of healthcare resources or facilities; ICT specially adapted for the management or operation of medical equipment or devices
    • G16H40/60—ICT specially adapted for the management or administration of healthcare resources or facilities; ICT specially adapted for the management or operation of medical equipment or devices for the operation of medical equipment or devices
    • G16H40/67—ICT specially adapted for the management or administration of healthcare resources or facilities; ICT specially adapted for the management or operation of medical equipment or devices for the operation of medical equipment or devices for remote operation
    • 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
    • A61B5/0002—Remote monitoring of patients using telemetry, e.g. transmission of vital signals via a communication network
    • A61B5/0004—Remote monitoring of patients using telemetry, e.g. transmission of vital signals via a communication network characterised by the type of physiological signal transmitted
    • A61B5/0006—ECG or EEG signals
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00—Measuring for diagnostic purposes; Identification of persons
    • A61B5/02—Detecting, measuring or recording pulse, heart rate, blood pressure or blood flow; Combined pulse/heart-rate/blood pressure determination; Evaluating a cardiovascular condition not otherwise provided for, e.g. using combinations of techniques provided for in this group with electrocardiography or electroauscultation; Heart catheters for measuring blood pressure
    • A61B5/021—Measuring pressure in heart or blood vessels
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00—Measuring for diagnostic purposes; Identification of persons
    • A61B5/02—Detecting, measuring or recording pulse, heart rate, blood pressure or blood flow; Combined pulse/heart-rate/blood pressure determination; Evaluating a cardiovascular condition not otherwise provided for, e.g. using combinations of techniques provided for in this group with electrocardiography or electroauscultation; Heart catheters for measuring blood pressure
    • A61B5/024—Detecting, measuring or recording pulse rate or heart rate
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00—Measuring for diagnostic purposes; Identification of persons
    • A61B5/05—Detecting, measuring or recording for diagnosis by means of electric currents or magnetic fields; Measuring using microwaves or radio waves 
    • A61B5/053—Measuring electrical impedance or conductance of a portion of the body
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00—Measuring for diagnostic purposes; Identification of persons
    • A61B5/145—Measuring characteristics of blood in vivo, e.g. gas concentration, pH value; Measuring characteristics of body fluids or tissues, e.g. interstitial fluid, cerebral tissue
    • A61B5/1455—Measuring characteristics of blood in vivo, e.g. gas concentration, pH value; Measuring characteristics of body fluids or tissues, e.g. interstitial fluid, cerebral tissue using optical sensors, e.g. spectral photometrical oximeters

Definitions

  • the disclosed Remote Patient Monitoring System is a
  • a mobile application that facilitates communications between patients and care providers (i.e., physicians, nurses, home health, skilled nursing facility, ancillary care, and so forth) in the peri-hospitalization and peri-procedural (episode of care) settings.
  • care providers i.e., physicians, nurses, home health, skilled nursing facility, ancillary care, and so forth
  • the application utilizes survey questions, logs, camera, video, third-party sensors, and other methods for monitoring health (e.g., calorie intake, pedometer, HealthKit®, iWatch®, and any desired sensor, monitoring device, or combination thereof) in an integrated and purposeful manner to monitor patient conditions (e.g., status, complications) which may help promote patient health and behavior, allow earlier recognition of signs and symptoms, and provide alerts to providers to intervene on changes in clinical status.
  • patient conditions e.g., status, complications
  • the platform can also reduce initial length of stay by allowing earlier discharge.
  • the RPMS platform increases communications, thus allowing the patient 'voice' to be heard in an organized way while allowing their direct patient participation in postoperative / post-discharge care management.
  • FIG. 1 is a schematic diagram of usage architecture for interaction with and processing information from a remote patient monitoring system (RPMS) according to an embodiment of the present disclosure.
  • RPMS remote patient monitoring system
  • FIG. 2 is a block diagram of vital sign sensing within a remote patient monitoring system (RPMS) according to an embodiment of the present disclosure.
  • RPMS remote patient monitoring system
  • FIG. 3 is a block diagram of motion artifact removal within EKG, PPG, or similar signals, as utilized according to an embodiment of the present disclosure.
  • FIG. 4 is a block diagram of a portion of FIG. 2, in which an
  • impedance measurement method is depicted according to an embodiment of the present disclosure.
  • FIG. 5 is a side view of a sensor configuration, showing example interaction and placement on the patient, according to an embodiment of the present disclosure.
  • FIG. 6A and FIG. 6B are depictions of a capacitive electrode and electrode integration, respectively, into the same substrate with other active components, according to an embodiment of the present disclosure.
  • the disclosed remote patient monitoring system improves the collection and processing of patient reported outcomes (PROs).
  • the patient reported outcomes for a given service line e.g., colorectal, cardiothoracic, etc.
  • condition e.g., pneumonia, congestive heart failure, or other conditions
  • a given service line e.g., colorectal, cardiothoracic, etc.
  • condition e.g., pneumonia, congestive heart failure, or other conditions
  • the manner in which the patient reported outcome data is organized and analyzed by the system allows providers to predict type and risk of complication during each subsequent peri-operative (peri-intervention, peri- admission, etc.) day and provides guidance on detection of complications while simultaneously influencing patient behavior toward reducing risk. For example, with the system knowing (containing information) that the patient has a smoking history the system then increases the number and / or depth of questions asked about 'pneumonia / atelectasis' symptoms, and patient instructions then include additional guidance on breathing exercises and increased use of incentive spirometer.
  • the system tailors questions given to a patient undergoing a colorectal operation to increase detection rate of
  • these questions are further personalized using built-in logic and data analytics.
  • this further personalization includes patient's individual risk factors, current complications, and patient feedback.
  • Clinical care operations by the disclosed system are applicable to any episode of care, and are particularly well-suited when following an operation, intervention or admission for a problem (e.g., a medical admission for pneumonia or congestive heart failure).
  • RPMS post-discharge patient care
  • home health nurse agencies for instance but not limited to, home health nurse agencies, skilled nursing facilities, and post-operative clinics.
  • the RPMS system beneficially decreases length of stay duration for hospitalized patients in a peri-operative / peri-admission setting. For example, by giving providers a tool for more closely monitoring their post-operative patients, earlier detection of either clinical improvement or worsening conditions aid clinicians toward earlier interventions on those patients. This may allow patients to be discharged sooner, thus decreasing the duration of a hospital stay without increasing readmissions or emergency department (ED) visits. Having the RPMS in place improves the disparate gap in care between the hospital and the home (or skilled nursing facility (SNF)). Thus, physicians obtain additional confidence in discharging a patient earlier than would be otherwise planned, because of this additional remote monitoring which provides pertinent patient recovery information.
  • SNF skilled nursing facility
  • Embodiments of the disclosed system also facilitate obtaining patient information in the patient's own voice, upon which increasing attention is being paid in clinical situations.
  • the RPMS provides a mechanism for patients to directly participate in their care by giving them a method of communicating their post-operative / post-discharge states in a well-defined way that fits into provider and patient workflows. Additionally, RPMS can improve patient safety as well as the overall patient experience, both of which are also utilized as performance measurements in at least one embodiment of the disclosure.
  • the mobile application is comprised of an application designed to be downloaded onto a personal technology device (e.g., smart phone, tablet, computer or other electronic device having a processor and user interface) with a consumer-friendly user interface.
  • a personal technology device e.g., smart phone, tablet, computer or other electronic device having a processor and user interface
  • the system also provides back-end data and analytic server reporting to support updates, optimizations, and rules-driven alerting to the providers and patients.
  • FIG. 1 illustrates an embodiment 10 of usage architecture of RPMS.
  • RPMS 18 the user-data interface comprising RPMS 18 is seen with additional system components in a utilization architecture according to at least one embodiment of the present disclosure.
  • RPMS 18 is seen for interacting with user 12 and receiving vital sign information from a vital sign sensor device (or module) 14.
  • Output from RPMS is directed to a back-end data and analytic server of the disclosure, referred to in the figure as signal search engine 20 which comprises processing and data archiving for the present disclosure.
  • Output from signal search engine 20 comprises classification and analytics 26, and is directed to feedback processing 24 which determines metrics, alerts and guidance, and which initiates and generates outputs 28 (electronically) through the web, mobile, FAX, electronic health records, or other electronic communications mechanism to healthcare providers 16 (e.g., physicians, nurses, home health providers, skilled nursing facility (SNF) staff, clinics, and other health providers working with a specific patient) which interact with one another, user 12, electronic health records processing 22, and the signal search engine 20.
  • Electronic health records processing 22 is configured for utilizing patient information, device registration, training information and maintaining records for the patients which are seen utilized by signal search engine 20.
  • the overall system has a number of general features, which include but are not limited to the following.
  • the system utilizes a patient-facing application with a convenient, easy to understand, user interface.
  • Secure data transfers are performed through the use of encrypted data.
  • Any desired data formats can be supported, including but not limited to data formats for survey responses, images, video recordings, sensor data, and background analytics stored on secure servers with protected PHI, compliant with HIPAA standards.
  • Data output flexibility is provided by the system for integrating data output to respective clinical electronic health record (EHR) services, and other integrations with provider-based clinical workflows.
  • the system is configured to allow the clinical care
  • communication process to be tailored in any desired manner, including curating the desired process steps from peer-reviewed publications, existing health care databases, clinical practice, patient feedback, data analysis, and other sources without limitation.
  • processes can include the following.
  • the manner in which the data is organized and analyzed (e.g., built-in logic and data analytics) in the disclosed system allows the providers to predict type and risk of complication during each subsequent peri-operative (peri-admission) day and provides guidance on detection of complication as well as influencing patient behavior to reduce risk.
  • Each patient receives a personalized set of questions, tasks, alerts, or other activity / inputs, based on patient risk factors, type of operation, procedure, admission, existing complication, patient response, provider input, or other information made available to the system.
  • Adaptive logic in the system aids in minimizing survey fatigue while improving early detection of
  • the system also includes general features including the following.
  • the application is configured to provide the best outcome in the most effective way while providing value along the whole from the patient interfacing with RPMS to the healthcare providers overseeing each user and the various 3 rd parties, including those involved with health records, registration, training, reimbursement or other services.
  • the system is configured for compliance with reimbursement guidelines.
  • monitoring of wound complications may have any of the following.
  • (2)(a) Camera input is supported and the system provides instructions on what to photograph, how to photograph it correctly, and feedback on successful capture.
  • (2)(b) Video (e.g., WebEx) is supported and the system also provides instructions on how to perform video capture successfully.
  • (2)(c) In addition, the system is configured to readily support any other desired method or path of communication.
  • Patient event logging is provided, such as allowing any event to be logged, in particular those which require multiple inputs to achieve effective surveillance, which include but are not limited to pain level, fluid intake, urine or ostomy output, bowel movements, activity levels, sleep, and other event sources.
  • the sensor interface in at least one embodiment is configured to be compatible with both new and existing technology.
  • sensor devices such as heart rate (e.g., iWatch), blood pressure, weight, blood sugar, accelerometer (e.g., Fitbit), abdominal sensors, and so forth.
  • the system is configured for proper integration or compatibility with existing platforms (e.g., Apple HealthKit, ResearchKit, Google, EHR, or other platforms).
  • (4)(c) Communication may be provided to and from the RPMS sensing device by any desired communication form, such as by utilizing WiFi, Bluetooth, other wireless protocols, manual entry, or any desired input source.
  • Patient task notifications and / or reminders are configured to be initiated and sent as alerts to other personal devices of the patient (e.g., mobile phone or tablet via voice/text message, computer via email, notifications through a third party, internet and/or private network
  • other personal devices of the patient e.g., mobile phone or tablet via voice/text message, computer via email, notifications through a third party, internet and/or private network
  • the tasks for which notification are provided are 'adaptive' based on user behavior and the goals of the monitoring toward improving user compliance.
  • (6) Physician, nurse, or provider alerts are initiated and generated based on patient responses.
  • the alerts include a response level that is generated by provider preference and severity of symptoms.
  • Alerts are based on provider preferences (e.g., alert to mobile phone through voice message, text message, pager, email, web connectivity, uploaded to an intermediary communication mechanism (e.g., EPIC CareConnect or In Basket), internet and / or private network communications, or other selected preferences).
  • provider preferences e.g., alert to mobile phone through voice message, text message, pager, email, web connectivity, uploaded to an intermediary communication mechanism (e.g., EPIC CareConnect or In Basket), internet and / or private network communications, or other selected preferences).
  • (7)(b) Improving communication between providers, patient, home health or skilled nursing facility nurse (e.g., regarding patient condition, changing orders, obtaining and viewing lab work, signing home health orders and other administrative paperwork, and the like).
  • (7)(c) Options are provided to prescribe RPMS solely or to be utilized in conjunction with a visiting nurse.
  • Any other communication e.g., camera, video, messaging, audio, text, or other communication stream / recording
  • the system can initiate and generate an alert for urgent care for a patient having wound or drain issues, or has urinary symptoms, or is dehydrated and needs intravenous (IV) hydration, or requires blood work, or a need exists in regard to other issues or necessary interventions.
  • IV intravenous
  • the system can initiate and generate communications toward facilitating and / or expediting communications between the critical care parties.
  • communication is facilitated (initiated and generated) with payors, such as insurance companies, laboratories, or other parties which are not strictly involved in the critical care (e.g., Quest for patient lab work, other ancillary services).
  • payors such as insurance companies, laboratories, or other parties which are not strictly involved in the critical care (e.g., Quest for patient lab work, other ancillary services).
  • (10) Patient experience and education is facilitated by utilizing the disclosed system.
  • (10)(a) This system allows the patient voice to be heard in a pre-scripted way by incorporating technology into the clinical care pathway.
  • (10)(b) Patient education is increased. For example, patients develop an understanding of their symptoms, become more inclined to ambulate, and are more cognizant of their wounds.
  • (10)(c) Links to patient resources are made increasingly available (e.g., educational websites, videos, articles, news feeds, holistic health feedback, nutrition, Gl and health, mental health, physical therapy exercises, incentive spirometer and other breathing exercises, yoga, and any other patient-centric resources).
  • Information is provided by the system based on responses of patients.
  • the system directs case focus onto patient or caregiver's feedback and / or voice inputs.
  • interactive quizzes are provided and / or generated which aid both providers and patients in understanding and addressing deficits in the care process.
  • the system provides and / or links the patient to infotainment (e.g., health games and relaxation, psychosocial, entertainment, and other sources in this category).
  • Interfacing is performed by the system for direct communication between physician and home health / skilled nursing facility (e.g., any other party) or direct communication between provider and patient.
  • the disclosed system is flexible and can be configured to
  • Data visualization is provided by the RPMS device (e.g., patient- reported surveys, camera, sensor, graphs, plots, indicia, alerts, or other desired visual outputs) which allows immediate feedback regarding patient condition during an episode of care.
  • Data visualization is provided by the system for patient task (e.g., oral intake of fluids, ostomy output, or any other patient task), for home health or skilled nursing facility (e.g., view of patient-reported condition over a period of time (e.g., last few days) along with pertinent patient information and instructions or concerns from providers), and for providers (e.g., dashboard of all patient-reported outcomes).
  • An interface is provided by the dashboard for communication between providers (e.g., between physician and home health / skilled nursing facility, or other health care providers); and / or for a
  • RPMS is configured for adapting and personalizing surveys based on patient condition, risk factors, type of operation / intervention, provider preferences, or other conditions and inputs.
  • Patient and provider task scheduling is facilitated using the dashboard of RPMS.
  • Patient condition alert settings can be set within RPMS for transmission to a healthcare provider, such as utilizing email, EHR, text or pager communications, or other mode of electronically generated communication typically selected based on provider preference.
  • the server of RPMS has a number of features included in one or more of its embodiments.
  • An interface is provided with enterprise EHR systems and other systems or database by the RPMS server.
  • (2) User customization and modification options are provided by the RPMS server.
  • (3) Application analytics are made available in response to storage and / or processing within the RPMS server.
  • the disclosed system is configured for performing a wide range of analytical processes in its various embodiments.
  • (1 ) Analyses and cross- validation is performed by the system using external EHR and internal data.
  • Prediction of complication or readmission risk using patient condition is performed by the system, for instance using external risk calculators, internal database, EHR records, and other data sources and risk determination procedures.
  • FIG. 2 illustrates an example embodiment 30 of a vital sign sensor device.
  • the sensor device is designed to perform multi-modality sensing, which are selected from the group of sensor inputs consisting of:
  • EKG electrocardiogram
  • arrhythmia bio-impedance
  • PPG photoplethysmogram
  • Electrodes 32 are seen comprising separate electrodes 34a, 34b, 34c, by way of example and not limitation, which are connected to the EKG measurement circuits 36 composed of amplifiers and filters. Electrodes 32 are also shared by the impedance measurement unit 38 to reduce device form factor. Impedance and skin conductance are acquired by delivering a current stimulus and measuring the evoked electrode overpotential. Output 37 from EKG measurement circuit 36, and impedance measurement 39 from impedance measurement circuit 38, are directed to control processor 40 (e.g., microcontroller, DSP, FPGA, other control circuits, or combinations thereof).
  • control processor 40 e.g., microcontroller, DSP, FPGA, other control circuits, or combinations thereof.
  • Photodiodes and LEDs 42 comprising at least 44a, 44b respectively, in the device are configured for emitting light and capturing its reflection as processed by SpO2 and photoplethysmogram circuit 46 which determines peripheral capillary oxygen saturation (SpO2) and a PPG measurement, which is directed to control processor 40.
  • SpO2 peripheral capillary oxygen saturation
  • PPG peripheral capillary oxygen saturation
  • Patient sounds e.g., bowel, breath, voiced, heart rate sounds or other physiological sounds
  • at least one microphone 48 or other sound / vibration transducer
  • a sound processing circuit 50 before being received by control processor 40.
  • Each sensing modality can be activated independently or
  • control processor i.e., microcontroller, digital-signal-processor (DSP), field-programmable-gate-array (FPGA), application-specific integrated circuit (ASIC), or other forms of control circuitry without limitation.
  • DSP digital-signal-processor
  • FPGA field-programmable-gate-array
  • ASIC application-specific integrated circuit
  • Communications to and from control processor 40 are exemplified with at least one wireless communications module 52 and antenna 54, such as comprising WiFi, Bluetooth, or other communications standard which is most compatible within the architecture within which the RPMS device is operating.
  • environmental information is received from at least one circuit 56 and associated antenna 58 by control processor 40.
  • this environmental information is depicted as a global positioning sensor (GPS) 56 and its antenna 58 for obtaining patient location and motion information. It will be appreciated that other environmental information may be obtained without limitation, such as body range of motion, temperature, humidity, wind, environmental audio, still picture, video, and / or other inputs depending on the needs of the patient and the specific application to which the RPMS is being utilized.
  • GPS global positioning sensor
  • the recorded signals from control processor 40 are transmitted through wireless communications 52 to both the RPMS system and the user's mobile device or cloud storage for further signal processing. It is important to point out that although the proposed sensing modalities are similar to other vital sign sensors or biosensors, novel hardware configurations and schemes are disclosed toward achieving improved performance and facilitating device operation and patient usage.
  • Important elements of the sensor design include, but are not limited to the following, (a) Motion Artifact Removal: The removal of motion artifacts is one of the most challenging problems in EKG / ECK or PPG recording as these artifacts contaminate the recorded signals of interest.
  • One common approach to artifact removal is through adaptive noise filtering using a noise reference signal derived from accelerometers. It is assumed that the motion of the device / sensor is related to the artifact. Nonetheless, this leads to extra hardware cost, and more critically, there is not significant correlation between PPG and the acceleration data from the accelerometer. Motion artifacts more particularly arise from the
  • FIG. 3 illustrates an example embodiment 70 of motion artifact
  • a signal 72 for motion induced impedance is seen received by an adaptive filter 74 (i.e., least mean square, Kalman, or Wiener filter, and other adaptive filters) in which its computation can be made in the microcontroller / FPGA / DSP of the sensor device.
  • EKG (ECK) or PPG signals containing motion artifacts 76 are received at the positive input of a summing junction 78.
  • Output from filter 74 is received at the negative input 80 of summing junction 78, with the summing junction outputting a signal 82 which is also seen coupled back to filter 74 so that the filter can adapt to the output.
  • Filter 74 adaptively adjusts the magnitude of the impedance signal to match that of the motion artifact captured in EKG (ECK) or PPG recording. Subsequently, the adjusted impedance signal is used as the approximated motion artifact and is subtracted from the artifact contaminated EKG / PPG signal to produce an artifact-free signal.
  • FIG. 4 illustrates an example embodiment 90 showing the unique approach of the disclosure for acquiring impedance information.
  • the same group of electrodes 32 shown with separate electrodes 34a, 34b, 34c, as well as EKG measurement 36 with output 37, impedance measurement 38 with output 39.
  • the control circuitry is not shown.
  • Example signals 93 are shown in the figure for PPG and EKG.
  • a circuit 100 having a current pulse generator 104 and high pass filter 102 are seen coupled to electrode inputs (e.g., shown for electrodes 34a, 34b).
  • the current pulse generator 104 is utilized to deliver a current stimulus to these EKG electrode inputs to the EKG measurement block 36, as exemplified by the injected high frequency current pulses 105.
  • a high frequency square current pulse e.g., greater than 1 kHz
  • the pulse repetition frequency is set greater than or equal to 10 Hz to sample the changing impedance.
  • the advantage of the short square stimulation pulse is that it facilitates the derivation of the tissue resistance and electrode-interface capacitance, and is not limited to deriving the impedance at a fixed frequency.
  • An additional advantage lies in that it simplifies the hardware design and reduces system power consumption (i.e., main components are merely a high pass filter (HPF) and analog-to- digital converter (ADC) as a front end to the processing circuitry).
  • HPF high pass filter
  • ADC analog-to- digital converter
  • the electrode-tissue interface is modeled as a Randel's cell electrode model 92 shown with parallel resistance R c t and capacitor C d i, which are in series with resistor R s .
  • the resulting electrode overpotential V c 98 will only comprise: (a) V e : the voltage drop across the tissue resistance (R s ) and (2) V c : the following voltage crosses the double layer capacitance (C d i) due to capacitive current charging.
  • the value of R s and C d i can be determined by measuring the electrode overpotential.
  • a high-pass filter is used herein to remove low frequency signal, such EKG and PPG.
  • the approach allows the sharing of the electrodes with EKG measurement circuits as the signal frequency used for impedance measurement is substantially higher, for instance greater than 1 kHz, than that of the EKG and PPG signals which for example range up-to approximately tens of Hz.
  • the impedance change i.e., R s and C d i variation
  • Motion artifact can thus be extracted by first sampling the peak voltage changes of the V c 98 and then by low-pass filtering to derive its voltage waveform V e 96.
  • V e is low-pass filtered and then fed to a filter as seen in FIG. 3 in order to derive an artifact-free recording signal.
  • an EKG measurement output 94 is shown as well as an LPF filtered V e 96.
  • Measurements of skin conductance have been utilized to infer sympathetic activity. It is thought that skin conductance varies due to sweating in the skin which is governed by the sympathetic nerve system.
  • the system can perform continuous measurements of skin conductance by acquiring values for R s and C d
  • PTT pulse transition time
  • At least one embodiment of the present disclosure utilizes a patch sensor which overcomes the synchronization issue and provides convenient BP measurements.
  • FIG. 5 illustrates an example embodiment 1 10 of a sensor
  • the sensor device 1 16 is configured for attachment to the chest of user 1 14, although it could be configured to attach at other locations of the body that would not impede activities of the user.
  • sensors, processing and telemetry circuitry are retained in a first circuit module 1 18, which is coupled through connectors 124a, 124b, and more preferably additional connectors not seen in the figure, with an electrode base 126 configured for retention on the skin of a user.
  • Electrodes 120a, 120b, 128, 132a, 132b) for EKG measurement and LED/Photodiodes (122a, 122b, 130a, 130b) face outwardly on opposing sides of the device.
  • first circuit module 1 18 can be disconnected from electrode base 126, without the need of breaking the adhesive attachment between electrode base 126 and the skin of the patient, toward facilitating servicing of module 1 18, and allowing the patient to bath or perform other daily activities with the sensor out of the way.
  • the system is configured to work with an option of a patch that can be worn in the shower, while sleeping, exercising and so forth.
  • 132a, 132b are activated to acquire an EKG signal, with its motion artifacts being suppressed, such as described in the previous section.
  • LEDs (122a, 122b, 130a, 130b) on both sides of the device are enabled to acquire PPG signals from either the fingertip or the chest.
  • the LED/photodiodes on the bottom side are activated to record PPG while at the same time, the EKG is measured from the fingertips of a user's hand 1 12 using two electrodes on top of the sensor device. PTT from the heart to the fingertip can then be acquired. Both measurements are also synchronized due to the use of the same device and the procedure is convenient because no additional wire connecting different sensors is required.
  • FIG. 6A and FIG. 6B illustrate example embodiments 150a, 150b of electrodes for use in the present disclosure.
  • the electrode on top of the device is seen as a capacitive electrode, such as comprising a flexible substrate (i.e., polyimide, silicone, parelyene, or other flexible base material) which can support a metal electrode 154 insulated 152 from the patient skin surface, or by way of further example a simple low-cost printed circuit board may be utilized.
  • a capacitive electrode such as comprising a flexible substrate (i.e., polyimide, silicone, parelyene, or other flexible base material) which can support a metal electrode 154 insulated 152 from the patient skin surface, or by way of further example a simple low-cost printed circuit board may be utilized.
  • the benefit of using a capacitive electrode are as follows, (a) The capacitive electrode does not require direct contact between patient skin surface and the device, thus allowing measurements to be made even when cloth is on top of the electrodes, (b) Using the capacitive electrode generates a quality signal which is insensitive to skin condition.
  • FIG. 6B illustrates an example embodiment 150b of integrating
  • elements 158a and 158b are examples of active circuits / components (e.g. batteries, amplifiers, processors, and wireless transceiver, or other circuitry) that acquire and process the recorded physiological signals.
  • the active components can be placed on either side of substrate 150b, depending on the need of the application.
  • Trace 156 is an example of conductive (e.g., metal) traces used to form the necessary electrical connection between each active component as well as the conductive trace that forms an inductive coil inside the sensor substrate for wireless charging the sensor patch. Section 154 in FIG.
  • conductive section 154 in FIG. 6B can also be connected to other types of sensors, providing the flexibility that different types of sensors can be incorporated into the sensor patch (e.g., temperature sensor, PH sensor, and accelerometer).
  • At least one embodiment of the present disclosure integrates the capacitive electrode with the active circuits on the same flexible substrate of PCB board.
  • the electrode is covered by an insulation layer and connected to active circuits for signal recording.
  • Table 1 presents an embodiment of program code utilized for
  • program code is provided by way of example and not limitation, as the general technique is applicable to variations of this code example.
  • RPMS remote patient monitoring system
  • Remote monitoring can be easily incorporated into existing clinical care pathways to capture essential peri-operative information in order to detect complications sooner, thereby allowing opportunities for intervention.
  • patients undergoing colorectal operations may experience wound infection or dehydration.
  • Monitoring of the wound and of fluid intake, urine output, and ostomy output would allow for earlier detection, thereby providing an opportunity for earlier clinical care guidance to be given to patients, potentially reducing readmissions or ED visits and cost.
  • the RPMS platform application targets individual patient risk factors following each procedure, operation, or admission based on the best information available, such as from clinical information curated for each service line from peer-reviewed publications, best practice guidelines, existing health care database, actual clinical practice and use, patient feedback, and data analysis to determine outcome, effectiveness, and value.
  • the manner in which the data is organized and analyzed by the disclosed system allows providers to predict type and risk of complication during each subsequent peri-operative / peri-admission day and provide guidance on detection of complication while also influencing patient behavior toward reducing risk.
  • the RPMS platform may also decrease length of stay duration for hospitalized patients in the peri-operative / peri-admission setting.
  • RPMS integrates with other support services which are vital to patient care post-discharge including home health nurse agencies, skilled nursing facilities, and post-operative clinics. Historically, these support service areas have had limited connectivity. RPMS helps bridge this support services communication gap by providing relevant patient monitoring information in respective care settings.
  • RPMS provides a mechanism for patients to directly participate in their care by giving them a method of communicating their post-operative / post-discharge states in a well-defined way that fits into the provider and patient workflow. Additionally, RPMS improves patient safety and patient experience both of which are also being used as performance measurements.
  • RPMS capitalizes on the opportunity to improve patient care by reducing readmissions to the hospital as well as reducing hospital length of stay. This is achieved by tailoring the application and platform to focus on optimizing the provider-patient interaction in the peri-operative / peri-admission period using patient self-reported data, image data, log data, and wireless sensor data.
  • the system has the capability to support the clinical care pathway for respective service lines to capture the relevant data elements in order to provide the right guidance to improve patient care.
  • the clinical algorithm described can be applied to patients
  • the system and its analytics are clinically validated through analysis of patient information, patient-reported data, user experience, and evaluation of outcome data to demonstrate effectiveness and value.
  • a set of questions is pre-determined based on features including type of operation, risk factors of the patient, and clinical care pathways of the specialty service. Selection of patient survey questions is described below.
  • patient surveys are selected from a comprehensive repository of questions (e.g., surveys, serial logs, camera, video, sensors, and other inputs without limitation), and the survey set can be further personalized in the system for a patient based on any one of the following or combinations thereof: (a) type of operation, procedure, admission determines the type of patient survey; (b) personal risk factors (e.g., age, co-morbidities, lives alone, malnutrition, smoker, or other data or condition) are factored into the patient survey; (c) complications that occurred during hospitalization (e.g., urinary tract infection), are also registered in the survey; (d) risk factors from peer-reviewed publications that predict higher complication or readmission rates, are taken into account; (e) risk factors from local (hospital) or national patient database that predict higher complication or readmission rates after a particular operation, procedure, admission are accounted for; (f) time period after surgery, intervention, admission (e.g., liberalize diet two weeks post- discharge; progressive increase
  • Logs of interest include fluid intake, ostomy output, blood pressure, ambulation activity,
  • the patient provides input into the RPMS application in response to specific personalized prompts and instructions (e.g., survey questions, instructions to upload images of wounds, sensor data, etc.).
  • specific personalized prompts and instructions e.g., survey questions, instructions to upload images of wounds, sensor data, etc.
  • the disclosed system not only generates questions for the patient regarding their symptoms, but includes objective surgery-specific / admission-specific data (e.g., ostomy output, wounds, HR, or other information important for the admissions process).
  • objective surgery-specific / admission-specific data e.g., ostomy output, wounds, HR, or other information important for the admissions process.
  • dashboard retains RPMS data as well as data abstracted from the electronic health records (EHR). Providers are able to document data observations and patient interactions. In at least one embodiment, this data is made available for review by all parties, while the system can support one or more modes in which data is restricted to, or from, designated parties. In at least one embodiment, this documentation and RPMS data is integrated into the EHR to provide for basic charting, (b) RPMS offers analysis of outcomes (e.g., metrics or outcomes such as readmissions, length of stay, weight loss, patient experience, behavioral change, depression, or any other outcome analysis), (c) RPMS is a learning system across levels ranging from learning more about each type of post-operative care, to learning more about each patient. With iterative evaluation of daily data from a patient and then from multiple patients undergoing the same type of operation with the same risk factors, the system learns method of predicting complications, promoting behavioral changes, detecting health problems such as mental health problems, and many other areas.
  • EHR electronic health records
  • the analytic system is configured for branching decision tree questions.
  • the system provides a method for analyzing answers based on clinical course and knowledge,
  • Patient data can be analyzed using statistical methods such as correlation / regression and other methods so that evaluation of answers to certain questions will enhance predictive capability (e.g., patients undergoing a particular type of operation who answer select questions a certain way may have an early complication),
  • One goal is to decrease survey fatigue by asking the least number of questions to obtain the best answer. For example, patients who answer one way a few times may not need to be asked this question again in the future. Or alternatively, one answer will lead the patient to a series of questions which will more quickly indicate that the patient has depression or an early complication, (g)
  • accumulation of a large number of patients will allow for use of big data analytics.
  • Additional purposes of RPMS includes any one or more of the
  • RPMS renal spastic syndrome
  • Embodiments of the present technology may be described herein with reference to flowchart illustrations of methods and systems according to embodiments of the technology, and / or procedures, algorithms, steps, operations, formulae, or other computational depictions, which may also be implemented as computer program products.
  • each block or step of a flowchart, and combinations of blocks (and / or steps) in a flowchart, as well as any procedure, algorithm, step, operation, formula, or computational depiction can be implemented by various means, such as hardware, firmware, and/or software including one or more computer program instructions embodied in computer-readable program code.
  • any such computer program instructions may be executed by one or more computer processors, including without limitation a general purpose computer or special purpose computer, or other programmable processing apparatus to produce a machine, such that the computer program instructions which execute on the computer processor(s) or other programmable processing apparatus create means for
  • blocks of the flowcharts, and procedures, algorithms, steps, operations, formulae, or computational depictions described herein support combinations of means for performing the specified function(s), combinations of steps for performing the specified function(s), and computer program instructions, such as embodied in computer-readable program code logic means, for performing the specified function(s).
  • each block of the flowchart illustrations, as well as any procedures, algorithms, steps, operations, formulae, or computational depictions and combinations thereof described herein can be implemented by special purpose hardware-based computer systems which perform the specified function(s) or step(s), or combinations of special purpose hardware and computer-readable program code.
  • these computer program instructions may also be stored in one or more computer-readable memory or memory devices that can direct a computer processor or other programmable processing apparatus to function in a particular manner, such that the instructions stored in the computer-readable memory or memory devices produce an article of manufacture including instruction means which implement the function specified in the block(s) of the flowchart(s).
  • the computer program instructions may also be executed by a computer processor or other programmable processing apparatus to cause a series of operational steps to be performed on the computer processor or other programmable processing apparatus to produce a computer-implemented process such that the instructions which execute on the computer processor or other programmable processing apparatus provide steps for implementing the functions specified in the block(s) of the flowchart(s), procedure (s) algorithm(s), step(s), operation(s), formula(e), or computational
  • programming or “program executable” as used herein refer to one or more instructions that can be executed by one or more computer processors to perform one or more functions as described herein.
  • the instructions can be embodied in software, in firmware, or in a combination of software and firmware.
  • the instructions can be stored local to the device in non-transitory media, or can be stored remotely such as on a server, or all or a portion of the instructions can be stored locally and remotely. Instructions stored remotely can be downloaded (pushed) to the device by user initiation, or automatically based on one or more factors.
  • processors hardware processor, computer processor, central processing unit (CPU), and computer are used synonymously to denote a device capable of executing the instructions and communicating with input/output interfaces and/or peripheral devices, and that the terms processor, hardware processor, computer processor, CPU, and computer are intended to encompass single or multiple devices, single core and multicore devices, and variations thereof.
  • An apparatus for real-time post-operative or post-admission monitoring of a patient comprising: (a) an electronic vital sign sensor module configured for attachment to a patient, said electronic vital sign sensor module comprising an electrocardiogram (EKG) sensor and measurement circuit configured for collecting EKG measurements, and a plurality of sensors configured to perform multi-modality sensing with sensors for collecting bio-impedance, skin conductance, peripheral capillary oxygen saturation (Sp0 2 ) and photoplethysmogram (PPG), blood pressure (BP), temperature, and having at least one microphone for sound collection; (b) a processor configured for receiving and processing sensor information from said vital sign sensor; (c) a non-transitory processor-readable memory storing instructions executable by said processor, wherein said instructions, when executed by said processor, performs steps comprising: (c)(i) compiling one or more individual patient risk factors following a procedure, an operation, or an admission based on clinical information, and
  • determining clinical care processing (c)(ii) predicting a type and risk of one or more peri-operative or peri-admission complications based on measured patient vital sign information in relation to patient-reported information, and patient history using said clinical care processing; (c)(iii) electronically initiating and communicating said predicted type and risk of said one or more peri-operative or peri-admission complications to a health care provider; and (c)(iv) electronically initiating and communicating instructions and information back to the patient to reduce said predicted type and risk of said one or more peri-operative or peri-admission complications.
  • a method for predicting type and risk of peri-operative or peri- admission complications comprising: (a) attaching a processor- enabled vital sign sensor device to a patient for collecting patient sensor information and for recording and transferring patient-reported information; (b) transferring said patient sensor information and said patient-reported information from said processor-enabled vital sign sensor device to a computer processor; (c) compiling individual patient risk factors on a computer processor and associated memory following each procedure, operation, or admission based on clinical information to construct a clinical care algorithm; (d) predicting a type and a risk of one or more peri-operative or peri-admission complications on the computer processor based on collected patient sensor information, patient-reported information in relation to patient history using said clinical care algorithm; (e) communicating from the computer processor said predicted type and risk of said one or more peri-operative or peri-admission complications to a health care provider; and (f) communicating instructions and information from said computer processor back to the patient to reduce said predicted type and risk of said one or
  • An apparatus for real-time post-operative or post-admission monitoring of a patient comprising: (a) a vital sign sensor module configured for attachment to a patient, said electronic vital sign sensor module configured to perform multi-modality sensing, including electrocardiogram (EKG) and arrhythmia, bio-impedance, skin
  • PPG photoplethysmogram
  • BP blood pressure
  • temperature white blood cell count
  • accelerometer range of motion
  • processor configured for receiving and processing patient sensor information from said vital sign sensor into measured patient vital sign information
  • a non-transitory processor- readable memory storing instructions executable by said processor, wherein said instructions, when executed by said processor, performs steps comprising: (c)(i) compiling one or more individual patient risk factors following a procedure, an operation, or an admission based on clinical information, and determining clinical care processing; (c)(ii) predicting a type and a risk of one or more peri-operative or peri-admission
  • said electronic vital sign sensor module is further configured for collecting vital signs from the group of vital signs consisting of white blood cell count, acceleration, and range of body motion.
  • electrocardiogram (EKG) sensor and measurement circuit further comprises EKG amplifiers and filters.
  • said electronic vital sign sensor module is configured with photodiodes and LEDs for emitting light and capturing light reflection from the LEDs in measuring peripheral capillary oxygen saturation (Sp0 2 ) and
  • PPG photoplethysmogram
  • said electronic vital sign sensor module is configured for delivering a current stimulus and measuring evoked electrode overpotential in determining said bio-impedance and said skin conductance.
  • said predicted type and risk of said one or more peri-operative or peri-admission complications is electronically communicated to a health care provider based on provider communication preferences selected from the group of communication types consisting of voice message, text message, pager notification, electronic mail, internet and/or private network communications, uploaded to an intermediary communication mechanism, or combination.
  • communicating instructions and information back to the patient is performed using an electronic communications medium selected from the group of electronic communications medium consisting of voice message, text message, electronic mail, internet and/or private network
  • set refers to a collection of one or more objects.
  • a set of objects can include a single object or multiple objects.
  • the terms “substantially” and “about” are used to describe and account for small variations.
  • the terms can refer to instances in which the event or circumstance occurs precisely as well as instances in which the event or circumstance occurs to a close approximation.
  • the terms can refer to a range of variation of less than or equal to ⁇ 10% of that numerical value, such as less than or equal to ⁇ 5%, less than or equal to ⁇ 4%, less than or equal to ⁇ 3%, less than or equal to ⁇ 2%, less than or equal to ⁇ 1 %, less than or equal to ⁇ 0.5%, less than or equal to ⁇ 0.1 %, or less than or equal to ⁇ 0.05%.
  • substantially aligned can refer to a range of angular variation of less than or equal to ⁇ 10°, such as less than or equal to ⁇ 5°, less than or equal to ⁇ 4°, less than or equal to ⁇ 3°, less than or equal to ⁇ 2°, less than or equal to ⁇ 1 °, less than or equal to ⁇ 0.5°, less than or equal to ⁇ 0.1 °, or less than or equal to ⁇ 0.05°.
  • range format is used for convenience and brevity and should be understood flexibly to include numerical values explicitly specified as limits of a range, but also to include all individual numerical values or sub-ranges encompassed within that range as if each numerical value and sub-range is explicitly specified.
  • a ratio in the range of about 1 to about 200 should be understood to include the explicitly recited limits of about 1 and about 200, but also to include individual ratios such as about 2, about 3, and about 4, and sub-ranges such as about 10 to about 50, about 20 to about 100, and so forth.

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Abstract

L'invention concerne un appareil de surveillance post-opératoire ou post-admission de patient en temps réel, configuré pour prédire le type et le risque d'apparition d'une ou de plusieurs complications. Un système de surveillance à distance de patient réalise une détection multimodale portant sur un patient, laquelle détection peut comprendre, mais sans y être limitée : EKG et arythmie, bio-impédance, conduction cutanée, SpO2 et photopléthysmogramme (PPG), bruits du patient, pression artérielle, température, numération des globules blancs, accéléromètre, amplitude de mouvement et d'autres paramètres du patient. Sur la base de ces informations et d'une base de données, le système de surveillance à distance de patient compile des facteurs de risque pour le patient suite à une intervention/opération/admission, et communique des informations aux soignants avec des instructions en retour au patient pour améliorer les soins apportés au patient et réduire les complications.
PCT/US2017/054965 2016-10-03 2017-10-03 Système de surveillance à distance de patient WO2018067585A1 (fr)

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