Information processing device, information processing method, information processing system, and program

Abstract

This invention provides an information processing device, information processing method, information processing system, and program that enable centralized management of patient information by linking an electronic medical record database with databases from multiple customer acquisition media, and that utilize this information to propose medical services. [Solution] The information processing system includes a reception unit that receives patient needs, a patient information acquisition unit that acquires patient information including basic patient information and medical visit history information, a medical information acquisition unit that acquires medical information including medical treatment information and prescription details from medical institutions, an information centralized management unit that centrally manages patient information and medical information, a prompt generation unit that outputs generation commands based on the centrally managed patient information and medical information, and a proposal information generation unit that generates proposal information including medical services, medical institutions, treatment details, etc., suitable for the patient based on the generation commands.

Description

Technical Field

[0001] The present invention relates to an information processing apparatus, an information processing method, an information processing system, and a program for centrally managing patient information by linking an electronic medical record database and a database of a plurality of customer acquisition media.

Background Art

[0002] In recent years, medical institutions have been promoting the introduction of electronic medical record systems, and management of patient medical information through digitization has become common. In particular, clinics that mainly provide self-paid medical treatments currently acquire patient information by utilizing a plurality of customer acquisition media (e.g., websites, SNS advertisements, email marketing, etc.). However, each data is managed by an individual system, and patient information is scattered. For this reason, it is difficult to integrate and efficiently utilize information, and it has not been possible to comprehensively grasp a patient's treatment history and customer acquisition data and reflect them in medical services.

[0003] In Patent Document 1, a technology for centrally managing users' health information is disclosed. However, there is no description regarding the linkage with patient information obtained from clinics' customer acquisition media and the proposal of individualized medical services utilizing such information, and it does not sufficiently address the problems in practice.

[0004] Patent Document 2 discloses a system for improving business efficiency by linking information between medical institutions and nursing facilities and searching for acceptable facilities after a patient is discharged from the hospital.

Prior Art Documents

Patent Documents

[0005]

Patent Document 1

Patent Document 2

Summary of the Invention

Problems to be Solved by the Invention

[0006] However, while Patent Document 1 aims at centralized management of health information, it did not consider collaboration with customer acquisition media for clinics that primarily provide self-pay medical services, nor did it consider the proposal of medical services that utilize such collaboration.

[0007] Furthermore, while Patent Document 2 focuses on information sharing between medical institutions and nursing care facilities, it does not describe specific methods for linking the customer acquisition media used by clinics with electronic medical record systems, and does not disclose any technology related to proposing optimal medical services based on individual patient information.

[0008] Therefore, the present invention aims to provide an information processing device, an information processing method, an information processing system, and a program that can centrally manage patient information by linking an electronic medical record database with databases of multiple customer acquisition media, and that can utilize that information to propose medical services. [Effects of the Invention]

[0009] According to the present invention, it is possible to provide an information processing device, an information processing method, an information processing system, and a program that can centrally manage patient information by linking an electronic medical record database with databases of multiple customer acquisition media, and that can use that information to propose medical services. [Brief explanation of the drawing]

[0010] [Figure 1] This is a system configuration diagram showing an example of the overall configuration of the information processing system according to the present invention. [Figure 2] This is a block diagram showing an example of the hardware configuration of an information processing device according to the present invention. [Figure 3] This is a functional block diagram showing an example of the functional configuration of the information processing device according to the present invention. [Figure 4] This flowchart shows an example of the processing procedure for the information processing method according to the present invention. [Figure 5]This is a conceptual diagram showing an example of the details of the medical service proposal information generation process according to the present invention. [Figure 6] This figure shows an example of a patient information and medical information management screen according to the present invention. [Modes for carrying out the invention]

[0011] The present invention will be described below. However, the present invention is not limited to the embodiments shown below, and can be modified, added, altered, or deleted to the extent that a person skilled in the art can conceive of it. Any embodiment that achieves the function and effect of the present invention is included within the scope of the present invention.

[0012] The present invention comprises a communication interface that connects to an electronic medical record database and databases of multiple customer acquisition media, and a control unit that acquires patient information from the databases of multiple customer acquisition media, associates the patient information with the medical information contained in the electronic medical record database based on the patient ID, and centrally manages the information. The control unit analyzes the patient information and medical information recorded in the electronic medical record database and generates medical service proposal information based on the analysis results.

[0013] Medical information preferably includes information about the treatment provided to the patient.

[0014] Medical information preferably includes the patient's prescription history.

[0015] The control unit preferably obtains patient information from multiple customer acquisition media by scraping.

[0016] Preferably, the control unit uses a machine learning model when analyzing patient information and medical information, and generates suggestion information to support the medical staff in formulating treatment plans based on the analysis results.

[0017] The information processing method of the present invention is an information processing method in an information processing apparatus, and includes steps of connecting to an electronic medical record database and databases of a plurality of customer-attracting media, obtaining patient information from the databases of the plurality of customer-attracting media, associating and centrally managing the patient information based on medical treatment information included in the electronic medical record database and a patient ID, and analyzing the patient information and medical treatment information recorded in the electronic medical record database, and generating proposal information for medical services based on the analysis result.

[0018] The program of the present invention causes a computer to execute processes of connecting to an electronic medical record database and databases of a plurality of customer-attracting media, obtaining patient information from the databases of the plurality of customer-attracting media, associating and centrally managing the patient information based on medical treatment information included in the electronic medical record database and a patient ID, analyzing the patient information and medical treatment information recorded in the electronic medical record database, and generating proposal information for medical services based on the analysis result.

[0019] The information processing system of the present invention includes an electronic medical record database, a communication interface connecting to the electronic medical record database and databases of a plurality of customer-attracting media, a control unit that obtains patient information from the databases of the plurality of customer-attracting media, associates and centrally manages the patient information based on medical treatment information included in the electronic medical record database and a patient ID, utilizes a machine learning model when analyzing the patient information and the medical treatment information, and generates proposal information for medical services based on the analysis result.

Example

[0020] Hereinafter, the present invention will be described more specifically by showing examples, but the present invention is not limited by these examples.

[0021] Referring to Figure 1, the overall configuration of the information processing system 1 according to the present invention will be described. The information processing system 1 is configured with an information processing device 10 as its core. The information processing device 10 is connected to an electronic medical record database 20 and databases of multiple patient acquisition media 30 via a communication interface 11. The database of patient acquisition media 30 includes databases of multiple external media such as patient acquisition media A, patient acquisition media B, SNS1, and SNS2, and patient information 50 is obtained from each database by scraping. The information processing device 10 is also connected to a machine learning service 40, and based on the analysis of the acquired patient information 50 and medical information, it generates medical service proposal information 60, including treatment plan proposals 62 and next appointment proposals 64. This enables medical staff to efficiently provide optimal medical services to each patient.

[0022] Referring to Figure 2, the hardware configuration of the information processing device 10 will be described. The information processing device 10 includes a control unit 12 comprising a CPU (Central Processing Unit) 12A, RAM (Random Access Memory) 12B, and ROM (Read Only Memory) 12C, and is connected to the storage unit 14 and the communication interface 11. The CPU 12A executes various calculation processes according to the programs stored in ROM 12C and the programs loaded into RAM 12B, and controls the entire system. RAM 12B is used as the work area for the CPU 12A and temporarily stores programs and data necessary for the CPU 12A's processing. ROM 12C nonvolatilously stores the basic control programs and various parameters of the information processing device 10. The storage unit 14 is a nonvolatilous high-capacity storage device such as an SSD (Solid State Drive) or HDD (Hard Disk Drive), and stores medical information from the electronic medical record database 20 and patient information 50 from the patient acquisition media 30. Specifically, treatment information 22 and prescription history information 24 are stored in association with the patient ID 51. The communication interface 11 is a device for communicating with external systems via a wired or wireless network, and includes, for example, an Ethernet interface or a wireless LAN interface. This enables secure communication with the electronic medical record database 20 and the patient acquisition media 30. The input / output device 16 includes, for example, a display, keyboard, and mouse, and provides a user interface for exchanging information with medical staff. The generated suggestion information is displayed on the display, and necessary information can be input and manipulated via the keyboard and mouse. This allows medical staff to operate the system intuitively and efficiently. With this hardware configuration, the information processing device 10 achieves high-speed and stable processing capabilities, enabling efficient processing of large amounts of patient and medical information.

[0023] Referring to Figure 3, the functional configuration of the information processing device 10 will be explained. The information processing device 10 comprises a reception unit 110, a patient information acquisition unit 120, a medical information acquisition unit 130, an information centralized management unit 140, a prompt generation unit 150, and a suggestion information generation unit 160. The patient information acquisition unit 120 acquires patient information from the database of the customer acquisition media 30 by scraping, and the medical information acquisition unit 130 acquires medical information such as treatment information 22 and prescription history 24 from the electronic medical record database 20. This information is integrated by the information centralized management unit 140 based on the patient ID 51, analysis is performed using a machine learning model 40 based on the prompt instructions generated by the prompt generation unit 150, and optimal medical service suggestion information is generated by the suggestion information generation unit 160.

[0024] Referring to Figure 4, the processing procedure in the information processing system 1 will be explained in detail. First, the information processing device 10 connects to the electronic medical record database 20 (ST1) and the database of the patient acquisition media 30 (ST2). These connections are established via a secure communication protocol through the communication interface 11. Next, the control unit 12 acquires patient information 50 (ST3). Specifically, the patient information acquisition unit 120 performs scraping on the database of the patient acquisition media 30 to acquire basic patient information, desired treatment content, past inquiry history, etc. The acquired information is linked by the information centralized management unit 140 based on the patient ID 51. At this time, patient information 50, such as name, age, address, contact information, and reservation history on the patient acquisition media 30, as well as medical information, such as medical treatment content, treatment history 22, and prescription history 24, are integrated and centrally stored in the storage unit 14 (ST4). This allows medical staff to efficiently access patient information from a single platform.

[0025] Subsequently, the prompt generation unit 150 generates a diagnostic information analysis prompt P (ST5) based on the accumulated medical information. This diagnostic information analysis prompt P includes the patient's age, gender, medical history, current symptoms, desired treatment, past treatment history 22, prescription history 24, etc. The diagnostic information analysis prompt P is generated with a structure such as the following. (1) Basic Information Section: Basic data such as the patient's age, gender, height, and weight should be placed in a structured data format such as "age:35;gender:female;height:165cm;weight:55kg". (2) Medical History Section: Organize past medical information chronologically and describe it in the format "visit_date:2024-01-15;treatment:Cosmetic surgery;result:Good". (3) Request section: The patient's wishes and requests obtained from the customer acquisition media 30 are expressed in the format of "desired_treatment:wrinkle removal;budget:300000;preferred_date:weekend". (4) Constraints section: Medical constraints such as allergy information and medical history should be described in the format "allergy: local anesthesia; previous_condition: hypertension".

[0026] The prompt generation algorithm is executed in the following steps: (1) Extract the necessary information for each section from the electronic medical record database 20 and the customer acquisition media database 30. (2) The extracted information is converted into a structured data format that can be interpreted by the machine learning model 40. (3) Prioritize each section according to its importance and determine the order in which they will be placed within the prompt. (4) If there is missing data, skip that item or set a default value.

[0027] The generated diagnostic information analysis prompt P is sent to the suggestion information generation unit 160 and used as input for analysis by the machine learning model 40. Based on the structured prompt in this way, the machine learning model 40 comprehensively analyzes the information in each section and generates optimal medical service suggestion information R (ST6). The machine learning model 40 has learned from past treatment performance data and patient satisfaction data, etc., and proposes the optimal treatment plan according to the characteristics of each patient. Finally, the generated suggestion information R is provided to the user, who is a medical staff member (ST7). The information provided includes recommended treatment content, expected treatment period, expected treatment effect, and recommended next appointment date and time, which allows medical staff to efficiently propose the optimal medical services according to the patient's condition and needs. Additional suggestions for suggestion information include the following: 1. Treatment-related suggestion information: - Proposal of treatment combinations (proposal of combination therapies that are expected to have synergistic effects) - Suggestions for alternative treatments (options tailored to the patient's budget and time constraints) - Suggestions for stepping up / down treatment (a phased treatment plan based on the improvement of symptoms) - Proposal of a post-operative care plan (including home care methods after the procedure) 2. Reservations and scheduling related: - Suggestion of the optimal treatment interval - Suggesting treatment timing that takes seasonality into consideration (e.g., avoiding periods of strong UV radiation). - Suggestion for maintenance appointments (regular follow-up) 3. Cost-related: - Proposal of payment plans (installment payments, loans, etc.) - Proposal of alternative treatments covered by insurance - Pricing proposal for package treatments 4. Risk Management Related: - Proposals based on drug interaction checks - Proposal of alternative treatments that take allergy risks into consideration - Suggestions for precautions based on medical history 5. Counseling-related: - Suggesting the optimal timing for your counseling appointment - Online / In-person counseling options - Recommendation of explanatory materials (selection of materials according to the patient's level of understanding) 6. Lifestyle related: - Suggestions for improving lifestyle habits - Suggestions for home care methods - Recommendations regarding diet and exercise 7. Communication-related: - Suggestions for communication methods with patients (such as means of contact and frequency) - Suggestions for visual materials to be used during the explanation. - Proposing explanation methods tailored to the patient's level of understanding. 8. Follow-up related: - Proposed follow-up schedule - Suggestion for timing to confirm treatment effectiveness - Suggested timing for patient satisfaction surveys 9. Inventory management related: - Propose to medical staff the streamlining of inventory management based on equipment and drug usage.

[0028] Referring to Figure 5, the detailed flow of the medical service suggestion information generation process is explained. The information processing device 10 generates an analysis prompt P based on the acquired patient information 50 and medical information, and applies this to the machine learning model 40. The machine learning model 40 has learned data such as past treatment results and patient responses, and comprehensively analyzes the input information. Specifically, in addition to basic information such as the patient's age, gender, and medical history, it derives suggestions optimized for each individual patient based on information such as past treatment history, prescription history, treatment effectiveness, and satisfaction level. In particular, by utilizing the trends in each patient's response to treatment and satisfaction level as learning data, more accurate suggestions become possible. As a result, suggestion information R, such as an optimized treatment plan and next appointment candidates, is generated for each patient ID 51. The generated suggestion information R includes the specific recommended treatment content, expected treatment period, expected treatment effect, cost-effectiveness analysis results, and the optimal next appointment timing. In this way, by utilizing comprehensive analysis by AI, it becomes possible to propose more effective and individualized medical services, and as a result, it is possible to simultaneously improve patient satisfaction and increase the efficiency of medical staff's work.

[0029] Referring to Figure 6, the management screen 200 provided to medical staff will be explained. The management screen 200 displays a list for each patient, for example, in the format shown in Display 210, Display 220, including patient name, age, patient ID 51, application media, reservation route, reservation type, treatment menu, chief complaint, desired treatment content, reservation information, attending clinic, attending staff, equipment / facilities used, inquiry date, scheduled visit date, reservation status, sales revenue, initial contract date, and treatment record. Medical staff can efficiently consider the optimal treatment plan for each patient. In this way, the provision of necessary information in a visually easy-to-understand format in a centralized manner greatly improves the work efficiency of medical staff.

[0030] <Aspect 1> The information processing device 10 comprises a communication interface 11 that connects to an electronic medical record database 20 and databases of multiple customer acquisition media 30, and a control unit 12 that acquires patient information 50 from the databases of the multiple customer acquisition media 30 and centrally manages the patient information 50 by associating it with medical information contained in the electronic medical record database 20 based on the patient ID 51, wherein the control unit 12 analyzes the patient information 50 and medical information recorded in the electronic medical record database 20 and generates medical service proposal information 60 based on the analysis results.

[0031] According to this approach, by integrating and managing information recorded in the electronic medical record database and databases of multiple customer acquisition media, it becomes possible to effectively utilize patient information and medical treatment information. Furthermore, this allows healthcare professionals to quickly and accurately grasp a patient's medical history and current condition, and by proposing medical services optimized for each patient, it can contribute to increased efficiency in medical care and improved patient satisfaction.

[0032] <Aspect 2> The information processing device 10 of embodiment 1 is characterized in that the medical information includes treatment information 22 for the patient.

[0033] According to this approach, by including treatment information in medical records, precise analysis based on the patient's treatment becomes possible. This allows healthcare professionals to concretely understand the effects of treatment and formulate subsequent treatment and follow-up plans based on scientific evidence, thereby improving the quality of treatment and increasing patient satisfaction with treatment outcomes.

[0034] <Aspect 3> The information processing device 10 according to embodiment 1 or 2, characterized in that the medical information includes prescription history information 24 for the patient.

[0035] According to this embodiment, it is possible to accurately grasp a patient's treatment history based on medical information, including prescription history information. This allows for the optimization of the next treatment plan by referring to past treatment results and prescription details, ensuring patient safety by preventing over- or duplicate prescriptions, while also promoting the effective use of medical resources.

[0036] <Aspect 4> The information processing device 10 according to any one of embodiments 1 to 3, characterized in that the control unit 12 acquires patient information 50 from multiple customer acquisition media 30 by scraping.

[0037] This approach allows for the efficient collection of patient information using scraping technology, enabling the provision of medical services based on the latest information. Furthermore, by collecting data from a wide range of sources, it becomes possible to accurately grasp patient needs that are often overlooked in the past, and an improvement in the quality of suggested information reflecting these needs can be expected. In addition, automated information collection can reduce the workload of medical staff while enabling timely information updates.

[0038] <Aspect 5> The information processing device 10 according to any one of embodiments 1 to 4, characterized in that the control unit 12 uses a machine learning model 40 when analyzing patient information 50 and medical information of a patient, and generates suggestion information 62 to support the formulation of a treatment plan for medical staff based on the analysis results.

[0039] According to this configuration, patient information can be analyzed in a highly sophisticated manner using machine learning models, making it easier for medical staff to develop evidence-based treatment plans. This enables the promotion of personalized medicine, allowing for the provision of optimal treatment plans for each patient, as well as reducing the burden on healthcare professionals and improving the accuracy of their decisions, thereby contributing to an overall improvement in the quality of medical care. The information processing device may also be equipped with a machine learning model, or an external device may be equipped with a machine learning model and the information processing device may be connected to the external device to perform the analysis.

[0040] <Aspect 6> An information processing method in an information processing device 10, characterized by comprising the steps of: connecting to an electronic medical record database 20 and a database of a plurality of customer acquisition media 30; acquiring patient information 50 from the database of the plurality of customer acquisition media 30; associating the patient information 50 with medical information contained in the electronic medical record database 20 based on a patient ID 51 and managing them centrally; and analyzing the patient information 50 and medical information recorded in the electronic medical record database 20 and generating medical service proposal information 60 based on the analysis results.

[0041] This configuration enables the centralized management of information obtained from multiple databases and facilitates the provision of appropriate medical services based on analysis results, thereby reducing information dispersion and management burden. Furthermore, it allows healthcare professionals to efficiently access patient data and improve the accuracy and satisfaction of medical care through the provision of treatment plans optimized for each patient.

[0042] <Aspect 7> A program for causing a computer to connect to an electronic medical record database 20 and the databases of multiple customer acquisition media 30, to retrieve patient information 50 from the databases of the multiple customer acquisition media 30, to centrally manage the patient information 50 by associating it with the medical information contained in the electronic medical record database 20 based on the patient ID 51, to analyze the patient information 50 and medical information recorded in the electronic medical record database 20, and to execute a process to generate medical service proposal information 60 based on the analysis results.

[0043] This configuration makes it possible to efficiently provide medical recommendations based on electronic medical records and patient information through program execution. Furthermore, it reduces the burdensome administrative tasks for healthcare professionals, allowing them to spend more time communicating with patients and providing medical care, thereby improving the quality of medical services.

[0044] <Aspect 8> An information processing system 1 comprising: an electronic medical record database 20; a communication interface 11 that connects to the electronic medical record database 20 and the databases of multiple customer acquisition media 30; and a control unit 12 that acquires patient information 50 from the databases of multiple customer acquisition media 30, centrally manages the patient information 50 by associating it with the medical information contained in the electronic medical record database 20 based on the patient ID 51, uses a machine learning model 40 when analyzing the patient information 50 and the medical information, and generates medical service proposal information 60 based on the analysis results.

[0045] This configuration allows for efficient management of patient information across the entire system, enabling faster and more accurate medical recommendations. Furthermore, by generating recommendations that accurately reflect patient information, it supports the decision-making of healthcare professionals and improves the reliability and convenience of medical care for patients. In addition, appropriate access control linked to the electronic medical record database enables secure management of patient information. Analysis using machine learning models allows for more advanced and precise medical service recommendations. Note that the information processing system may also be equipped with a machine learning model, or an external device may be equipped with a machine learning model and the information processing system may be connected to the external device to perform the analysis. [Explanation of symbols]

[0046] 1. Information Processing System 10 Information Processing Devices 11 Communication Interface 12 Control Unit 14 Storage section 16 Input / Output Devices 20 Electronic Medical Record Database 22 Treatment Information 24. Prescription history information 30 Customer Acquisition Media 40 Machine Learning Services 50 Patient Information 51 Patient ID 60. Medical Service Proposal Information 62. Proposed Treatment Plan Information 64 Next Appointment Suggestion 110 Reception Department 120 Patient Information Acquisition Department 130 Medical Information Acquisition Department 140 Information Central Management Department 150 Prompt generation unit 160 Proposal information generation section 200 screens 210 display 1 220 display 2

Claims

1. A communication interface that connects to the electronic medical record database and the databases of multiple customer acquisition media, A control unit that acquires patient information from the databases of the aforementioned multiple customer acquisition media, and centrally manages the patient information by associating it with the medical information contained in the electronic medical record database based on the patient ID, Equipped with, The control unit analyzes the patient information and medical information recorded in the electronic medical record database and generates medical service proposal information based on the analysis results. An information processing device characterized by the following:

2. The information processing device according to claim 1, characterized in that the medical information includes treatment information for the patient.

3. The aforementioned medical information includes prescription history information for the patient. The information processing apparatus according to feature 1.

4. The control unit acquires the patient information from the multiple customer acquisition media by scraping. The information processing apparatus according to feature 1.

5. The control unit uses a machine learning model to analyze the patient information and medical information of the patient, and generates suggestion information to support the medical staff in formulating a treatment plan based on the analysis results. The information processing apparatus according to feature 1.

6. An information processing method in an information processing device, Steps include connecting to an electronic medical record database and databases of multiple customer acquisition media, The steps include obtaining patient information from the databases of the aforementioned multiple customer acquisition media, The steps include: centrally managing the aforementioned patient information by associating it with the medical information contained in the electronic medical record database and the patient ID; The steps include: analyzing the patient information and medical information recorded in the electronic medical record database, and generating medical service proposal information based on the analysis results; including An information processing method characterized by the following:

7. Computers, Connects to the electronic medical record database and the databases of multiple customer acquisition media, Patient information is obtained from the databases of the aforementioned multiple customer acquisition media, The aforementioned patient information is centrally managed by associating it with the medical information contained in the electronic medical record database and the patient ID. The system analyzes the patient information and medical information recorded in the electronic medical record database and generates medical service proposal information based on the analysis results. A program to execute a process.

8. Electronic medical record database and A communication interface that connects to the aforementioned electronic medical record database and the databases of multiple customer acquisition media, A control unit that acquires patient information from the databases of the aforementioned multiple customer acquisition media, centrally manages the patient information by associating it with the medical information contained in the electronic medical record database based on the patient ID, uses a machine learning model when analyzing the patient information and the medical information, and generates medical service proposal information based on the analysis results, An information processing system characterized by comprising the following features.

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