WO2023052832A1

WO2023052832A1 - A healthcare management system and a method to operate the same

Info

Publication number: WO2023052832A1
Application number: PCT/IB2021/060854
Authority: WO
Inventors: Gnaneshwer Jadav
Original assignee: Gnaneshwer Jadav
Priority date: 2021-09-28
Filing date: 2021-11-23
Publication date: 2023-04-06

Abstract

A healthcare management system (100) is disclosed. A patient information collection module (110) collects health information of a patient, generates a unique patient identification number. A patient health monitoring module (120) monitors a plurality of health parameters of a registered patient, analyses a deviation in the plurality of health parameters monitored from a plurality of corresponding threshold limit of parameters. A prescription generation module (130) generates a digital prescription for the registered patient. A healthcare recommendation module (140) recommends one or more healthcare providers for serving the registered patient. An appointment scheduling module (150) schedules the medical appointment of one or more recommended healthcare providers with the registered patient, generates a token number corresponding to the medical appointment scheduled between the one or more recommended healthcare providers and the registered patient. A patient supporting module (160) generates a patient supporting recommendation for the registered patient to manage the healthcare service based on the disease diagnosed.

Description

A HEALTHCARE MANAGEMENT SYSTEM AND A METHOD TO OPERATE THE SAME

EARLIEST PRIORITY DATE:

This Application claims priority from a patent application filed in India having Patent Application No. 202141043963, filed on September 28, 2021 and titled “A HEALTHCARE MANAGEMENT SYSTEM AND A METHOD TO OPERATE THE SAME”

BACKGROUND

Embodiments of the present disclosure relate to a platform for medical collaboration services and more particularly to, a healthcare management system and a method to operate the same.

India needs better technology in which everyone can access resources not only for educational purposes, but also to promote medical strategy. Government of India has taken major initiative to secure health coverage for India's poor and weakest. This initiative is consistent with the government's perspective on ensuring that its citizens, especially poor and weaker groups have access to proper medical care. In order to ensure proper medical care, remote medical assistance has become popular for at least two-way communication between a healthcare provider such as a physician or a physical therapist, and a patient using audio and/or audio-visual and/or other sensorial or perceptive communications. The remote medical assistance such as a telemedicine concept is an option for the healthcare providers to communicate with patients and provide patient care when the patients do not want to or cannot easily go to the healthcare providers' offices. Various systems are available which provides medical assistance to the patient as well as the healthcare providers for healthcare management.

Conventionally, the system available for the healthcare management includes managing a medical consultation of the patient with the health care providers through remote options. However, such a conventional system has substantive limitations as the healthcare providers cannot conduct physical examinations of the patients. Rather, the healthcare providers must rely on verbal communication and/or limited remote observation of the patient. Also, such a conventional system provides limited access of health records of the patient as such health records are not completely stored in digital format, thereby leads to data loss issue as well as creates difficulty in accessing the health records from several platform.

Hence, there is a need for an improved system and a method for healthcare management in order to address the aforementioned issues.

BRIEF DESCRIPTION

In accordance with an embodiment of the present disclosure, a healthcare management is disclosed. The system includes a processing subsystem hosted on a server, wherein the processing subsystem is configured to execute on a network to control bidirectional communications among a plurality of modules. The processing subsystem includes a patient information collection module configured to collect health information of a patient for storing in a patient information database. The patient information collection module is configured to generate a unique patient identification number, upon registration process, based on the health information of the patient collected. The processing subsystem also includes a patient health monitoring module configured to monitor a plurality of health parameters of a registered patient in real-time, wherein the plurality of health parameters are accumulated via a wearable device associated with the registered patient. The patient health monitoring module is configured to analyse a deviation in the plurality of health parameters monitored from a plurality of corresponding threshold limit of parameters. The processing subsystem also includes a prescription generation module configured to generate a digital prescription for the registered patient for a medical appointment by accessing the health information from the patient information database when the deviation in the plurality of health parameters is analysed. The processing subsystem also includes a healthcare recommendation module configured to recommend one or more healthcare providers for serving the registered patient upon generation of the digital prescription based on a plurality of factors. The healthcare recommendation module is also configured to enable the one or more healthcare providers and one or more pharmacies upon recommendation to access the digital prescription generated for providing healthcare service to the registered patient. The processing subsystem also includes an appointment scheduling module configured to schedule the medical appointment of one or more recommended healthcare providers with the registered patient based on the digital prescription accessed upon requirement. The appointment scheduling module is also configured to generate a token number corresponding to the medical appointment scheduled between the one or more recommended healthcare providers and the registered patient. The appointment scheduling module is also configured to notify the one or more recommended healthcare providers and the registered patient corresponding to the medical appointment scheduled for the healthcare service based on the token number generated. The processing subsystem also includes a patient supporting module configured to diagnose a disease associated with the registered patient using a pattern recognition and segmentation technique based on an analysis of the one or more recommended healthcare providers during the medical appointment scheduled. The patient supporting module is also configured to generate a patient supporting recommendation for the registered patient to manage the healthcare service based on the disease diagnosed.

In accordance with another embodiment of the present disclosure, a method to operate the healthcare management is disclosed. The method includes collecting, by a patient information collection module of a processing subsystem, health information of a patient for storing in a patient information database. The method also includes generating, by the patient information collection module of the processing subsystem, a unique patient identification number, upon registration process, based on the health information of the patient collected. The method also includes monitoring, by a patient health monitoring module of the processing subsystem, a plurality of health parameters of a registered patient in real-time, wherein the plurality of health parameters are accumulated via a wearable device associated with the registered patient. The method also includes analysing, by the patient health monitoring module of the processing subsystem, a deviation in the plurality of health parameters monitored from a plurality of corresponding threshold limit of parameters. The method also includes generating, by a prescription generation module of the processing subsystem, a digital prescription for the registered patient for a medical appointment by accessing the health information from the patient information database when the deviation in the plurality of health parameters is analysed. The method also includes recommending, by a healthcare recommendation module of the processing subsystem, one or more healthcare providers for serving the registered patient upon generation of the digital prescription based on a plurality of factors. The enabling, by the healthcare recommendation module of the processing subsystem, the one or more healthcare providers and one or more pharmacies upon recommendation to access the digital prescription generated for providing healthcare service to the registered patient. The method also includes scheduling, by an appointment scheduling module of the processing subsystem, the medical appointment of one or more recommended healthcare providers with the registered patient based on the digital prescription accessed upon requirement. The method also includes generating, by the appointment scheduling module of the processing subsystem, a token number corresponding to the medical appointment scheduled between the one or more recommended healthcare providers and the registered patient. The method also includes notifying, by the appointment scheduling module of the processing subsystem, the one or more recommended healthcare providers and the registered patient corresponding to the medical appointment scheduled for the healthcare service based on the token number generated. The method also includes diagnosing, by a patient supporting module of the processing subsystem, disease associated with the registered patient using a pattern recognition and segmentation technique based on an analysis of the one or more recommended healthcare providers during the medical appointment scheduled. The method also includes generating, by the patient supporting module of the processing subsystem, a patient supporting recommendation for the registered patient to manage the healthcare service based on the disease diagnosed.

To further clarify the advantages and features of the present disclosure, a more particular description of the disclosure will follow by reference to specific embodiments thereof, which are illustrated in the appended figures. It is to be appreciated that these figures depict only typical embodiments of the disclosure and are therefore not to be considered limiting in scope. The disclosure will be described and explained with additional specificity and detail with the appended figures.

BRIEF DESCRIPTION OF THE DRAWINGS

The disclosure will be described and explained with additional specificity and detail with the accompanying figures in which: FIG. 1 is a block diagram of a healthcare management system in accordance with an embodiment of the present disclosure;

FIG. 2 is a block diagram representation of an embodiment of a healthcare management system in accordance with an embodiment of the present disclosure;

FIG. 3 is a schematic representation of an exemplary embodiment of a healthcare management system of FIG. 1 in accordance with an embodiment of the present disclosure;

FIG. 4 is a block diagram of a computer or a server in accordance with an embodiment of the present disclosure; and

FIG. 5 (a) and FIG. 5 (b) is a flow chart representing the steps involved in a method of a healthcare management system in accordance with an embodiment of the present disclosure.

Further, those skilled in the art will appreciate that elements in the figures are illustrated for simplicity and may not have necessarily been drawn to scale. Furthermore, in terms of the construction of the device, one or more components of the device may have been represented in the figures by conventional symbols, and the figures may show only those specific details that are pertinent to understanding the embodiments of the present disclosure so as not to obscure the figures with details that will be readily apparent to those skilled in the art having the benefit of the description herein.

DETAILED DESCRIPTION

For the purpose of promoting an understanding of the principles of the disclosure, reference will now be made to the embodiment illustrated in the figures and specific language will be used to describe them. It will nevertheless be understood that no limitation of the scope of the disclosure is thereby intended. Such alterations and further modifications in the illustrated system, and such further applications of the principles of the disclosure as would normally occur to those skilled in the art are to be construed as being within the scope of the present disclosure. The terms "comprises", "comprising", or any other variations thereof, are intended to cover a non-exclusive inclusion, such that a process or method that comprises a list of steps does not include only those steps but may include other steps not expressly listed or inherent to such a process or method. Similarly, one or more devices or sub-systems or elements or structures or components preceded by "comprises... a" does not, without more constraints, preclude the existence of other devices, sub-systems, elements, structures, components, additional devices, additional sub-systems, additional elements, additional structures or additional components. Appearances of the phrase "in an embodiment", "in another embodiment" and similar language throughout this specification may, but not necessarily do, all refer to the same embodiment.

Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by those skilled in the art to which this disclosure belongs. The system, methods, and examples provided herein are only illustrative and not intended to be limiting.

In the following specification and the claims, reference will be made to a number of terms, which shall be defined to have the following meanings. The singular forms “a”, “an”, and “the” include plural references unless the context clearly dictates otherwise.

Embodiments of the present disclosure relate to a healthcare management system and a method to operate the same. The system includes a processing subsystem hosted on a server, wherein the processing subsystem is configured to execute on a network to control bidirectional communications among a plurality of modules. The processing subsystem includes a patient information collection module configured to collect health information of a patient for storing in a patient information database. The patient information collection module is configured to generate a unique patient identification number, upon registration process, based on the health information of the patient collected. The processing subsystem also includes a patient health monitoring module configured to monitor a plurality of health parameters of a registered patient in real-time, wherein the plurality of health parameters are accumulated via a wearable device associated with the registered patient. The patient health monitoring module is configured to analyse a deviation in the plurality of health parameters monitored from a plurality of corresponding threshold limit of parameters. The processing subsystem also includes a prescription generation module configured to generate a digital prescription for the registered patient for a medical appointment by accessing the health information from the patient information database when the deviation in the plurality of health parameters is analysed. The processing subsystem also includes a healthcare recommendation module configured to recommend one or more healthcare providers for serving the registered patient upon generation of the digital prescription based on a plurality of factors. The healthcare recommendation module is also configured to enable the one or more healthcare providers and one or more pharmacies upon recommendation to access the digital prescription generated for providing healthcare service to the registered patient. The processing subsystem also includes an appointment scheduling module configured to schedule the medical appointment of one or more recommended healthcare providers with the registered patient based on the digital prescription accessed upon requirement. The appointment scheduling module is also configured to generate a token number corresponding to the medical appointment scheduled between the one or more recommended healthcare providers and the registered patient. The appointment scheduling module is also configured to notify the one or more recommended healthcare providers and the registered patient corresponding to the medical appointment scheduled for the healthcare service based on the token number generated. The processing subsystem also includes a patient supporting module configured to diagnose a disease associated with the registered patient using a pattern recognition and segmentation technique based on an analysis of the one or more recommended healthcare providers during the medical appointment scheduled. The patient supporting module is also configured to generate a patient supporting recommendation for the registered patient to manage the healthcare service based on the disease diagnosed.

FIG. 1 is a block diagram of a healthcare management system (100) in accordance with an embodiment of the present disclosure. The system (100) includes a processing subsystem (105) hosted on a server. In one embodiment, the server (108) may include a cloud server. In another embodiment, the server (108) may include a local server. The processing subsystem (105) is configured to execute on a network (not shown in FIG. 1) to control bidirectional communications among a plurality of modules. In one embodiment, the network may include a wired network such as local area network (LAN). In another embodiment, the network may include a wireless network such as Wi-Fi, Bluetooth, Zigbee, near field communication (NFC), infra-red communication (RFID) or the like.

The processing subsystem (105) includes a patient information collection module (110) configured to collect health information of a patient for storing in a patient information database. In some embodiment, the patient information database may be hosted on a cloud infrastructure. In one embodiment, the health information may include at least one of a health record, a diagnostic report, a medical prescription, a patient name, a patient age, a patient gender, a patient contact details or a combination thereof. The patient information collection module (110) is configured to generate a unique patient identification number, upon registration process, based on the health information of the patient collected.

The processing subsystem (105) also includes a patient health monitoring module (120) configured to monitor a plurality of health parameters of a registered patient in real-time, wherein the plurality of health parameters are accumulated via a wearable device associated with the registered patient. In one embodiment, the plurality of health parameters may include at least one of blood pressure, pulse rate, oxygen level, body temperature or a combination thereof. The patient health monitoring module (120) is configured to analyse a deviation in the plurality of health parameters monitored from a plurality of corresponding threshold limit of parameters. As used herein, the term ‘corresponding threshold limit of parameters’ is defined as an ideal value set for each of the plurality of health parameters. In a particular embodiment, the wearable device may include, but not limited to, a smart watch, a fitness band, a wearable vest, a wearable ring and the like.

The processing subsystem (105) also includes a prescription generation module (130) configured to generate a digital prescription for the registered patient for a medical appointment by accessing the health information from the patient information database when the deviation in the plurality of health parameters is analysed. In one embodiment, the deviation may include a positive deviation. In such embodiment, the positive deviation may represent a value of a plurality of parameters which is higher than the corresponding plurality of health parameters. In a specific embodiment, the prescription generation module is configured to generate a unique code corresponding to the digital prescription, wherein the unique code enables access of the digital prescription for healthcare service. In some embodiment, the unique code may include, but not limited to, a barcode, a quick response code, an alphanumeric code and the like. The unique code could be generated and used for medicine collection at any pharmacy at any location. Paperless digital prescription is sent directly to the pharmacy for the medicines. The digital prescriptions are recorded and accessible to the one or more healthcare providers (HCP) by searching for patient IDs. In case the medicines recall the same prescriptions can be used by the consulting HCPs without visiting the hospital again. Also, results from the diagnostic laboratory are directly linked and displayed in the digital prescription.

The processing subsystem (105) also includes a healthcare recommendation module (140) configured to recommend one or more healthcare providers for serving the registered patient upon generation of the digital prescription based on a plurality of factors. In one embodiment, the plurality of factors may include atleast one of location, experience, cost, route, working hours, diagnostic reports or a combination thereof. The healthcare recommendation module (140) is also configured to enable the one or more healthcare providers and one or more pharmacies upon recommendation to access the digital prescription generated for providing healthcare service to the registered patient. In one embodiment, the plurality of healthcare providers may include at least one of a doctor, a nurse, a paramedical staff, a hospital, a nursing home, a diagnostic laboratory or a combination thereof. In some embodiment, the healthcare service may include, but not limited to, medicine delivery, treatment, diagnostic tests and the like.

The processing subsystem (105) also includes an appointment scheduling module (150) configured to schedule the medical appointment of one or more recommended healthcare providers with the registered patient based on the digital prescription accessed upon requirement. The appointment scheduling module (150) is also configured to generate a token number corresponding to the medical appointment scheduled between the one or more recommended healthcare providers and the registered patient. The appointment scheduling module (150) is also configured to notify the one or more recommended healthcare providers and the registered patient corresponding to the medical appointment scheduled for the healthcare service based on the token number generated. The processing subsystem (105) also includes a patient supporting module (160) configured to diagnose a disease associated with the registered patient using a pattern recognition and segmentation technique based on an analysis of the one or more recommended healthcare providers during the medical appointment scheduled. Based on the experience and department of the one or more recommended healthcare providers, a type of the disease is determined. The patient supporting module (160) is also configured to generate a patient supporting recommendation for the registered patient to manage the healthcare service based on the disease diagnosed. In one embodiment, the patient supporting recommendation may include at least one of a food recommendation, a medicine recommendation, a lifestyle recommendation, a vaccination recommendation, an organ donation recommendation, a disease information notification or a combination thereof.

FIG. 2 is a block diagram representation of another embodiment of a healthcare management system in accordance with an embodiment of the present disclosure. As described in aforementioned FIG. 1, the system (100) includes a processing subsystem (105) which includes a patient information collection module (110), a patient health monitoring module (120), a prescription generation module (130), a healthcare recommendation module (140), an appointment scheduling module (150) and a patient supporting module (160). In addition, the processing subsystem (105) further includes a cross-functional collaboration module (165) configured to establish collaboration with the one or more healthcare providers and one or more researchers for facilitating the healthcare service upon diagnosis of the disease based on specialisation, geographical location and research topics. In another embodiment, the processing subsystem (105) further includes a medication interaction module (170) configured to identify an interaction of one or more drugs recommended for the treatment of the disease based on the digital prescription generated. The medication interaction module (170) is also configured to suggest a damage to one or more internal organs of the registered patient based on an ill-effect of the interaction of the one or more drugs identified.

In a particular embodiment, the processing subsystem (105), further includes a vaccination scheduling module (175) configured to recommend the registered patient for vaccination based on the diagnosis of the disease. The vaccination recommendation module is also configured to notify a vaccination schedule and one or more vaccination centres in vicinity to the registered patient upon recommendation of the vaccination. In one embodiment, the processing subsystem (105) further includes a clinical trial module (180) configured to employ a trained machine learning model to interpret physiological data, environmental influences, and genetic factors for suggesting a medical strategy to the one or more healthcare providers for treatment of the disease diagnosed. The clinical trial module (180) is also configured to utilize the trained machine learning model to predict pharmaceutical properties of one or more molecular compounds associated with a drug or a vaccine discovered for treatment of the disease.

In one embodiment, the processing subsystem (105) further includes a donation management module (185) configured to enable the registered patient to enrol for organ and blood donation for aiding in the treatment of the disease. In another embodiment, the processing subsystem (105) further includes an infant registration module (190) configured to share information associated with infant care and vaccination with a corresponding parent of an infant for upbringing health. In addition, the processing subsystem (105) further includes a medical strategy formation module (195) configured to provide insights into specific diseases and medical strategy. The medical strategy formation module (195) also enables actively learning within the medical community about clinical trials or a particular disease. The medical strategy formation module also responds to health care professionals' requests for medical information and provides patient education in clinical trials. The medial strategy formation module (195) is also configured to prevent diseases by depending on the patient profile considering the different health parameters. It entirely depends upon patients, if they want to analyze their health records and discuss future therapies with HCPs, if necessary. For example, pre-diabetes parameters is analysed, and other measures are taken based on the results of the analysis. Further, the medical strategy formation module creates video recordings of patients while the foreign doctor’s consultation. If a patient required a translator for the medical consultation from a foreign doctor, then the option is given to the patient, whether they want to record the conversation for cross-verification or not. If the patient wants to record it, the system automatically assign a nurse to clarify the conversation after the consultation if required. FIG. 3 is a schematic representation of an exemplary embodiment of a healthcare management system of FIG. 1 in accordance with an embodiment of the present disclosure. Considering an example, wherein the system (100) is utilised in day-to-day life by an individual for obtaining a telemedicine service. Let’s assume that the individual wants to obtain remote medical assistance without physically visiting any healthcare organizations. In such a scenario, the system (100) helps in health monitoring as well as providing diagnostic support to the individual remotely.

For health monitoring of the individual, the system needs to obtain information associated with the individual. A patient information collection module (110) which is hosted on a processing subsystem (105) of the system (100), collects health information of the individual such as a patient (104) for storing in a patient information database. For example, the health information may include at least one of a health record, a diagnostic report, a medical prescription, a patient name, a patient age, a patient gender, a patient contact details or a combination thereof. Once, the patient information is collected, the patient information collection module (110) generates a unique patient identification number, upon registration process, based on the health information of the patient (104) collected.

Upon registration of the patient, a patient health monitoring module (120) monitors a plurality of health parameters of a registered patient in real-time, wherein the plurality of health parameters are accumulated via a wearable device associated with the registered patient. In the example used herein, the plurality of health parameters may include, but not limited to, blood pressure, pulse rate, oxygen level, body temperature and the like. Upon receiving the plurality of health parameters, the patient health monitoring module (120) analyses a deviation in the plurality of health parameters monitored from a plurality of corresponding threshold limit of parameters. For example, if value of the plurality of health parameters is higher than the corresponding threshold limit of parameters, then such deviation is analysed.

Further based on the deviation, a prescription generation module (130) generates a digital prescription for the registered patient for a medical appointment by accessing the health information from the patient information database. Here the prescription generation module (130) generates a unique code corresponding to the digital prescription, wherein the unique code enables access of the digital prescription for healthcare service. For example, the unique code may include a barcode. The bar code generated of a paperless digital prescription is used for medicine collection at any pharmacy at any location.

Again, upon generation of the digital prescription, a healthcare recommendation module (140) recommends one or more healthcare providers for serving the registered patient (104) based on a plurality of factors. For example, the plurality of factors may include atleast one of location, experience, cost, route, working hours, diagnostic reports or a combination thereof. In the example used herein, the healthcare provider may include a doctor. An appointment scheduling module (150) schedules the medical appointment of the recommended healthcare provider such as the doctor with the registered patient based on the digital prescription accessed. Also, the appointment scheduling module (150) generates a token number corresponding to the medical appointment scheduled. Based on the token number generated, the appointment scheduling module (150) notifies the recommended healthcare provider and the registered patient about the medical appointment scheduled.

The processing subsystem (105) also includes a patient supporting module (160) to diagnose a disease associated with the registered patient using a pattern recognition and segmentation technique based on an analysis of the one or more recommended healthcare providers during the medical appointment scheduled. Not only this, the patient supporting module (160) also generates a patient supporting recommendation for the registered patient to manage the healthcare service based on the disease diagnosed. For example, the patient supporting recommendation may include at least one of a food recommendation, a medicine recommendation, a lifestyle recommendation, a vaccination recommendation, an organ donation recommendation, a disease information notification or a combination thereof.

Along with the aforementioned features of the system (100), a medication interaction module (170) identifies an interaction of one or more drugs recommended for the treatment of the disease based on the digital prescription generated. Also, the medication interaction module (170) suggests a damage to one or more internal organs of the registered patient based on an ill-effect of the interaction of the one or more drugs identified. Again, based on the type of the disease diagnosed, if there is a requirement for prevention of a pandemic kind of situation, then in such a scenario, a vaccination scheduling module (175) recommends the registered patient for vaccination. The vaccination recommendation module (175) is also configured to notify a vaccination schedule and one or more vaccination centres in vicinity to the registered patient upon recommendation of the vaccination. Further, a clinical trial module (180) employs a trained machine learning model to interpret physiological data, environmental influences, and genetic factors for suggesting a medical strategy to the one or more healthcare providers for treatment of the disease diagnosed. Also, the trained machine learning model is utilised to predict pharmaceutical properties of one or more molecular compounds associated with a drug or a vaccine discovered for treatment of the disease.

Again, in case of some emergency situation if there is requirement of organ transplantation or blood requirement, then in such a case an organ donation management module (185) enables the registered patient to enrol for organ and blood donation for aiding in the treatment of the disease. Similarly, in case of organ transplantation requirement by the registered patient, the organ donation management module (185) also establishes communicates with a donor.

In addition, the system (100) also facilitates sharing of information associated with infant care and vaccination with a corresponding parent of an infant for upbringing health with the help of an infant registration module (190). Further, a medical strategy formation module (195) provides insights into specific diseases and medical strategy. The medical strategy formation module (195) also enables actively learning within the medical community about clinical trials or a particular disease. The medical strategy formation module also responds to health care professionals' requests for medical information and provides patient education in clinical trials. Thereby, the system (100) helps in remote health monitoring as well as diagnosis, hence ensures complete healthcare management in an effective manner.

FIG. 4 is a block diagram of a computer or a server in accordance with an embodiment of the present disclosure. The server (200) includes processor(s) (230), and memory (210) operatively coupled to the bus (220). The processor(s) (230), as used herein, means any type of computational circuit, such as, but not limited to, a microprocessor, a microcontroller, a complex instruction set computing microprocessor, a reduced instruction set computing microprocessor, a very long instruction word microprocessor, an explicitly parallel instruction computing microprocessor, a digital signal processor, or any other type of processing circuit, or a combination thereof.

The memory (210) includes several subsystems stored in the form of executable program which instructs the processor (230) to perform the method steps illustrated in FIG. 1. The memory (210) includes a processing subsystem (105) of FIG.l. The processing subsystem (105) further has following modules: a patient information collection module (110), a patient monitoring module (120), a prescription generation module (130), healthcare recommendation module (140), an appointment scheduling module (150) and a patient supporting module (160).

The patient information collection module (110) configured to collect health information of a patient for storing in a patient information database. The patient information collection module (110) is configured to generate a unique patient identification number, upon registration process, based on the health information of the patient collected. The patient health monitoring module (120) is configured to monitor a plurality of health parameters of a registered patient in real-time, wherein the plurality of health parameters are accumulated via a wearable device associated with the registered patient. The patient health monitoring module (120) is configured to analyse a deviation in the plurality of health parameters monitored from a plurality of corresponding threshold limit of parameters. The prescription generation module (130) is configured to generate a digital prescription for the registered patient for a medical appointment by accessing the health information from the patient information database when the deviation in the plurality of health parameters is analysed. The healthcare recommendation module (140) is configured to recommend one or more healthcare providers for serving the registered patient upon generation of the digital prescription based on a plurality of factors. The healthcare recommendation module (140) is also configured to enable the one or more healthcare providers and one or more pharmacies upon recommendation to access the digital prescription generated for providing healthcare service to the registered patient. The appointment scheduling module (150) is configured to schedule the medical appointment of one or more recommended healthcare providers with the registered patient based on the digital prescription accessed upon requirement. The appointment scheduling module (150) is also configured to generate a token number corresponding to the medical appointment scheduled between the one or more recommended healthcare providers and the registered patient. The appointment scheduling module (150) is also configured to notify the one or more recommended healthcare providers and the registered patient corresponding to the medical appointment scheduled for the healthcare service based on the token number generated. The patient supporting module (160) is configured to diagnose a disease associated with the registered patient using a pattern recognition and segmentation technique based on an analysis of the one or more recommended healthcare providers during the medical appointment scheduled. The patient supporting module (160) is also configured to generate a patient supporting recommendation for the registered patient to manage the healthcare service based on the disease diagnosed.

The bus (220) as used herein refers to be internal memory channels or computer network that is used to connect computer components and transfer data between them. The bus (220) includes a serial bus or a parallel bus, wherein the serial bus transmits data in bit-serial format and the parallel bus transmits data across multiple wires. The bus (220) as used herein, may include but not limited to, a system bus, an internal bus, an external bus, an expansion bus, a frontside bus, a backside bus and the like.

FIG. 5 (a) and FIG. 5 (b) is a flow chart representing the steps involved in a method of a healthcare management system in accordance with an embodiment of the present disclosure. The method (300) includes collecting, by a patient information collection module of a processing subsystem, health information of a patient for storing in a patient information database in step 310. In one embodiment, collecting the health information of the patient or storing in the patient information database may include collecting the health information which may include at least one of a health record, a diagnostic report, a medical prescription, a patient name, a patient age, a patient gender, a patient contact details or a combination thereof.

The method (300) also includes generating, by the patient information collection module of the processing subsystem, a unique patient identification number, upon registration process, based on the health information of the patient collected in step 320. The method (300) also includes monitoring, by a patient health monitoring module of the processing subsystem, a plurality of health parameters of a registered patient in real-time, wherein the plurality of health parameters are accumulated via a wearable device associated with the registered patient in step 330. In one embodiment, monitoring the plurality of health parameters of the registered patient may include monitoring at least one of blood pressure, pulse rate, oxygen level, body temperature or a combination thereof.

The method (300) also includes analysing, by the patient health monitoring module of the processing subsystem, a deviation in the plurality of health parameters monitored from a plurality of corresponding threshold limit of parameters in step 340. The method (300) also includes generating, by a prescription generation module of the processing subsystem, a digital prescription for the registered patient for a medical appointment by accessing the health information from the patient information database when the deviation in the plurality of health parameters is analysed in step 350. In some embodiment, generating the digital prescription for the registered patient for the medical appointment by accessing the health information may include generating the digital prescription with a corresponding unique code, wherein the unique code enables access of the digital prescription for healthcare service. In some embodiment, the unique code may include, but not limited to, a barcode, a quick response code, an alphanumeric code and the like.

The method (300) also includes recommending, by a healthcare recommendation module of the processing subsystem, one or more healthcare providers for serving the registered patient upon generation of the digital prescription based on a plurality of factors in step 360. In one embodiment, recommending the one or more healthcare providers for serving the registered patient may include recommending at least one of a doctor, a nurse, a paramedical staff, a hospital, a nursing home, a diagnostic laboratory or a combination thereof. In some embodiment, recommending the one or more healthcare providers for serving the registered patient upon generation of the digital prescription based on the plurality of factors may include generation of the digital prescription based on atleast one of location, experience, cost, route, working hours, diagnostic reports or a combination thereof.

The method (300) also includes enabling, by the healthcare recommendation module of the processing subsystem, the one or more healthcare providers and one or more pharmacies upon recommendation to access the digital prescription generated for providing healthcare service to the registered patient in step 370. In one embodiment, enabling the one or more healthcare providers and the one or more pharmacies to access the digital prescription for providing the healthcare service may include accessing the digital prescription for providing the healthcare service including, but not limited to, medicine delivery, treatment, diagnostic tests and the like.

The method (300) also includes scheduling, by an appointment scheduling module of the processing subsystem, the medical appointment of one or more recommended healthcare providers with the registered patient based on the digital prescription accessed upon requirement in step 380. The method (300) also includes generating, by the appointment scheduling module of the processing subsystem, a token number corresponding to the medical appointment scheduled between the one or more recommended healthcare providers and the registered patient in step 390. The method (300) also includes notifying, by the appointment scheduling module of the processing subsystem, the one or more recommended healthcare providers and the registered patient corresponding to the medical appointment scheduled for the healthcare service based on the token number generated in step 400.

The method (300) also includes diagnosing, by a patient supporting module of the processing subsystem, disease associated with the registered patient using a pattern recognition and segmentation technique based on an analysis of the one or more recommended healthcare providers during the medical appointment scheduled in step 410. The method (300) also includes generating, by the patient supporting module of the processing subsystem, a patient supporting recommendation for the registered patient to manage the healthcare service based on the disease diagnosed in step 420. In one embodiment, generating the patient supporting recommendation for the registered patient to manage the healthcare service may include generating the patient supporting recommendation may include at least one of a food recommendation, a medicine recommendation, a lifestyle recommendation, a vaccination recommendation, an organ donation recommendation, a disease information notification or a combination thereof. Various embodiments of the present disclosure provide a system which establish cross -functional collaboration with healthcare providers and researchers to provide better patient care through a medical artificial intelligence strategy.

Moreover, the present disclosed system through an integrated platform manages medical strategy, medical education, patient support, prescription support, diagnostic support and patient monitoring.

Furthermore, the present disclosed system utilises machine learning technology for diagnosis of the disease by discovering which variables are more associated with the risk of suffering a disease, increases diagnosis efficiency by improving accuracy and reducing unnecessary hospital visits.

It will be understood by those skilled in the art that the foregoing general description and the following detailed description are exemplary and explanatory of the disclosure and are not intended to be restrictive thereof.

While specific language has been used to describe the disclosure, any limitations arising on account of the same are not intended. As would be apparent to a person skilled in the art, various working modifications may be made to the method in order to implement the inventive concept as taught herein.

The figures and the foregoing description give examples of embodiments. Those skilled in the art will appreciate that one or more of the described elements may well be combined into a single functional element. Alternatively, certain elements may be split into multiple functional elements. Elements from one embodiment may be added to another embodiment. For example, the order of processes described herein may be changed and are not limited to the manner described herein. Moreover, the actions of any flow diagram need not be implemented in the order shown; nor do all of the acts need to be necessarily performed. Also, those acts that are not dependent on other acts may be performed in parallel with the other acts. The scope of embodiments is by no means limited by these specific examples.

Claims

WE CLAIM:

1. A healthcare management system (100) comprising: a processing subsystem (105) hosted on a server (108), wherein the processing subsystem (105) is configured to execute on a network to control bidirectional communications among a plurality of modules comprising: a patient information collection module (110) configured to: collect health information of a patient for storing in a patient information database; and generate a unique patient identification number, upon registration process, based on the health information of the patient collected; a patient health monitoring module (120) operatively coupled to the patient information collection module (110), wherein the patient health monitoring module (120) is configured to: monitor a plurality of health parameters of a registered patient in real-time, wherein the plurality of health parameters are accumulated via a wearable device associated with the registered patient; and analyse a deviation in the plurality of health parameters monitored from a plurality of corresponding threshold limit of parameters; a prescription generation module (130) operatively coupled to the patient health monitoring module (120), wherein the prescription generation module (130) is configured to generate a digital prescription for the registered patient for a medical appointment by accessing the health information from the patient information database when the deviation in the plurality of health parameters is analysed; a healthcare recommendation module (140) operatively coupled to the prescription generation module (130) and the patient health monitoring module (120), wherein the healthcare recommendation module (140) is configured to: recommend one or more healthcare providers for serving the registered patient upon generation of the digital prescription based on a plurality of factors; and enable the one or more healthcare providers and one or more pharmacies upon recommendation to access the digital prescription generated for providing healthcare service to the registered patient; an appointment scheduling module (150) operatively coupled to the healthcare recommendation module (140), wherein the appointment scheduling module (150) is configured to: schedule the medical appointment of one or more recommended healthcare providers with the registered patient based on the digital prescription accessed upon requirement; generate a token number corresponding to the medical appointment scheduled between the one or more recommended healthcare providers and the registered patient; and notify the one or more recommended healthcare providers and the registered patient corresponding to the medical appointment scheduled for the healthcare service based on the token number generated; and a patient supporting module (160) operatively coupled to the appointment scheduling module (150), wherein the patient supporting module (160) is configured to: diagnose a disease associated with the registered patient using a pattern recognition and segmentation technique based on an analysis of the one or more recommended healthcare providers during the medical appointment scheduled; and generate a patient supporting recommendation for the registered patient to manage the healthcare service based on the disease diagnosed.

2. The system (100) as claimed in claim 1, wherein the health information comprises at least one of a health record, a diagnostic report, a medical prescription, a patient name, a patient age, a patient gender, a patient contact details or a combination thereof.

3. The system (100) as claimed in claim 1, wherein the plurality of health parameters comprises at least one of blood pressure, pulse rate, oxygen level, body temperature or a combination thereof.

4. The system (100) as claimed in claim 1, wherein the prescription generation module is configured to generate a unique code corresponding to the digital prescription, wherein the unique code enables access of the digital prescription for healthcare service.

5. The system (100) as claimed in claim 1, wherein the plurality of factors comprises atleast one of location, experience, cost, route, working hours, diagnostic reports or a combination thereof.

6. The system (100) as claimed in claim 1, wherein the plurality of healthcare providers comprises at least one of a doctor, a nurse, a paramedical staff, a hospital, a nursing home, a diagnostic laboratory or a combination thereof.

7. The system (100) as claimed in claim 1, wherein the patient supporting recommendation comprises at least one of a food recommendation, a medicine recommendation, a lifestyle recommendation, a vaccination recommendation, an organ donation recommendation, a disease information notification or a combination thereof.

8. The system (100) as claimed in claim 1, wherein the processing subsystem (105) further comprising a cross-functional collaboration module (170) configured to establish collaboration with the one or more healthcare providers and one or more researchers for facilitating the healthcare service upon diagnosis of the disease based on specialisation, geographical location and research topics.

9. The system (100) as claimed in claim 1, wherein the processing subsystem (105) further comprising a medication interaction module (175) configured to: identify an interaction of one or more drugs recommended for the treatment of the disease based on the digital prescription generated; and suggest a damage to one or more internal organs of the registered patient based on an ill-effect of the interaction of the one or more drugs identified.

10. The system (100) as claimed in claim 1, wherein the processing subsystem (105) further comprising a vaccination scheduling module (180) configured to: recommend the registered patient for vaccination based on the diagnosis of the disease; and notify a vaccination schedule and one or more vaccination centres in vicinity to the registered patient upon recommendation of the vaccination.

11. The system (100) as claimed in claim 1, wherein the processing subsystem (105) further comprising a clinical trial module (185) configured to: employ a trained machine learning model to interpret physiological data, environmental influences, and genetic factors for suggesting a medical strategy to the one or more healthcare providers for treatment of the disease diagnosed; and utilize the trained machine learning model to predict pharmaceutical properties of one or more molecular compounds associated with a drug or a vaccine discovered for treatment of the disease.

12. The system (100) as claimed in claim 1, wherein the processing subsystem (105) further comprising a donation management module (190) configured to enable the registered patient to enrol for organ and blood donation for aiding in the treatment of the disease.

13. The system (100) as claimed in claim 1, wherein the processing subsystem (105) comprising an infant registration module (195) configured to share information associated with infant care and vaccination with a corresponding parent of an infant for upbringing health.

14. A method (300) comprising: collecting, by a patient information collection module of a processing subsystem, health information of a patient for storing in a patient information database (310); generating, by the patient information collection module of the processing subsystem, a unique patient identification number, upon registration process, based on the health information of the patient collected (320); monitoring, by a patient health monitoring module of the processing subsystem, a plurality of health parameters of a registered patient in real-time, wherein the plurality of health parameters are accumulated via a wearable device associated with the registered patient (330); analysing, by the patient health monitoring module of the processing subsystem, a deviation in the plurality of health parameters monitored from a plurality of corresponding threshold limit of parameters (340); generating, by a prescription generation module of the processing subsystem, a digital prescription for the registered patient for a medical appointment by accessing the health information from the patient information database when the deviation in the plurality of health parameters is analysed (350); recommending, by a healthcare recommendation module of the processing subsystem, one or more healthcare providers for serving the registered patient upon generation of the digital prescription based on a plurality of factors (360); enabling, by the healthcare recommendation module of the processing subsystem, the one or more healthcare providers and one or more pharmacies upon recommendation to access the digital prescription generated for providing healthcare service to the registered patient (370); scheduling, by an appointment scheduling module of the processing subsystem, the medical appointment of one or more recommended healthcare providers with the registered patient based on the digital prescription accessed upon requirement (380); generating, by the appointment scheduling module of the processing subsystem, a token number corresponding to the medical appointment scheduled between the one or more recommended healthcare providers and the registered patient (390); notifying, by the appointment scheduling module of the processing subsystem, the one or more recommended healthcare providers and the registered patient corresponding to the medical appointment scheduled for the healthcare service based on the token number generated (400); diagnosing, by a patient supporting module of the processing subsystem, disease associated with the registered patient using a pattern recognition and segmentation technique based on an analysis of the one or more recommended healthcare providers during the medical appointment scheduled (410); and generating, by the patient supporting module of the processing subsystem, a patient supporting recommendation for the registered patient to manage the healthcare service based on the disease diagnosed (420).