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

Abstract

The present invention provides an information processing device, information processing method, information processing system, and program that can centrally manage patient information by linking an electronic medical record database with databases of multiple customer acquisition media, and utilize that information to propose medical services. [Solution] The information processing system has a reception unit that accepts patient needs, a patient information acquisition unit that acquires patient information including the patient's basic information and medical visit history information, a medical information acquisition unit that acquires medical information including medical institution's medical information and prescription details, a centralized information management unit that manages patient information and medical information in a unified manner, a prompt generation unit that outputs a generation command based on the centrally managed patient information and medical information, and a proposed information generation unit that generates proposed information including medical services, medical institutions, treatment details, etc. suitable for the patient based on the generation command.

Description

[Technical Field]

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

[0002] In recent years, medical institutions have increasingly adopted electronic medical record systems, and the electronic management of patient medical information has become commonplace. In particular, clinics that primarily provide private medical care currently obtain patient information through multiple customer acquisition media (e.g., websites, social media advertising, email marketing, etc.), but each type of data is managed in a separate system, leaving patient information scattered across multiple platforms. This makes it difficult to integrate and efficiently utilize this information, and it is not possible to comprehensively grasp patients' treatment histories and customer acquisition data and reflect this information in medical services.

[0003] Patent Document 1 discloses technology for centrally managing users' health information, but it does not specifically mention linking it with patient information obtained from the clinic's customer attraction media or using that information to propose individualized medical services, and does not adequately address practical issues.

[0004] Patent Document 2 discloses a system that aims to improve operational efficiency by linking information between medical institutions and nursing care facilities and searching for facilities that can accept patients after they are discharged from the hospital. [Prior art documents] [Patent documents]

[0005] [Patent Document 1] Japanese Patent Application Publication No. 2019-105913 [Patent Document 2] Japanese Patent Application Publication No. 2023-104978 Summary of the Invention [Problem to be solved by the invention]

[0006] However, although Patent Document 1 aims to centrally manage health information, it does not take into consideration collaboration with customer-attracting media in clinics that primarily provide private medical care, or the proposal of medical services that utilize this.

[0007] Furthermore, although Patent Document 2 focuses on information sharing between medical institutions and nursing care facilities, it does not describe specific methods for linking the customer attraction 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, information processing method, information processing system, and program that can centrally manage patient information by linking an electronic medical record database with the databases of multiple customer acquisition media, and 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, information processing method, information processing system, and program that can centrally manage patient information by linking an electronic medical record database with the databases of multiple customer acquisition media, and utilize that information to propose medical services. [Brief explanation of the drawings]

[0010] [Figure 1] 1 is a system configuration diagram showing an example of the overall configuration of an information processing system according to the present invention; [Figure 2] 1 is a block diagram showing an example of a hardware configuration of an information processing device according to the present invention; [Figure 3] 1 is a functional block diagram showing an example of a functional configuration of an information processing device according to the present invention; [Figure 4] 1 is a flowchart showing an example of a processing procedure of an information processing method according to the present invention. [Figure 5]FIG. 2 is a conceptual diagram showing an example of details of a medical service proposal information generation process according to the present invention. [Figure 6] FIG. 10 is a diagram showing an example of a management screen for patient information and medical information according to the present invention. DETAILED DESCRIPTION OF THE INVENTION

[0011] The present invention will be described below. Note that the present invention is not limited to the embodiments shown below, and can be modified, added, modified, deleted, or otherwise altered within the scope of what a person skilled in the art can conceive. Any embodiment that achieves the functions and effects of the present invention is 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 and associates the patient information with medical information contained in the electronic medical record database based on a patient ID and centrally manages it, and is characterized in that 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] The medical information preferably includes treatment information for the patient.

[0014] The medical information preferably includes prescription history information for the patient.

[0015] It is preferable that the control unit acquires patient information from multiple customer acquisition media by scraping.

[0016] It is preferable that the control unit uses a machine learning model when analyzing the patient information and medical information of the patient, and generates proposal information based on the analysis results to assist medical staff in formulating a treatment plan.

[0017] The information processing method of the present invention is an information processing method in an information processing device, and is characterized by including the steps of connecting to an electronic medical record database and databases of multiple customer acquisition media, acquiring patient information from the databases of multiple customer acquisition media, associating the patient information with medical information contained in the electronic medical record database based on a patient ID and centrally managing it, and 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.

[0018] The program of the present invention is characterized in that it causes a computer to execute the following process: connect to an electronic medical record database and a database of multiple customer acquisition media, acquire patient information from the database of multiple customer acquisition media, associate the patient information with medical information contained in the electronic medical record database based on a patient ID and centrally manage it, analyze the patient information and medical information recorded in the electronic medical record database, and generate medical service proposal information based on the analysis results.

[0019] The information processing system of the present invention is characterized by comprising an electronic medical record database, a communication interface connected to the electronic medical record database and databases of multiple customer acquisition media, and a control unit that acquires patient information from the databases of the multiple customer acquisition media, associates the patient information with medical information contained in the electronic medical record database based on a patient ID and centrally manages it, 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. [Example]

[0020] The present invention will be explained in more detail below by showing examples, but the present invention is not limited to these examples.

[0021] The overall configuration of an information processing system 1 according to the present invention will be described with reference to FIG. 1. 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 multiple customer attraction media 30 databases via a communication interface 11. The customer attraction media 30 database includes multiple external media databases, such as customer attraction media A, customer attraction media B, SNS 1, and SNS 2, and patient information 50 is acquired from each database by scraping. The information processing device 10 is also connected to a machine learning service 40, which generates medical service proposal information 60, including a treatment plan proposal 62 and a next appointment proposal 64, based on an analysis of the acquired patient information 50 and medical information. This allows medical staff to efficiently provide optimal medical services to each patient.

[0022] The hardware configuration of the information processing device 10 will be described with reference to FIG. 2. The information processing device 10 includes a control unit 12 including a CPU (Central Processing Unit) 12A, a RAM (Random Access Memory: volatile memory) 12B, and a ROM (Read Only Memory: nonvolatile memory) 12C, and is connected to a storage unit 14 and a communication interface 11. The CPU 12A executes various arithmetic processes according to programs stored in the ROM 12C and programs loaded into the RAM 12B, thereby controlling the entire system. The RAM 12B is used as a work area for the CPU 12A and temporarily stores programs and data required for processing by the CPU 12A. The ROM 12C stores basic control programs and various parameters of the information processing device 10 in a nonvolatile manner. The storage unit 14 is a nonvolatile large-capacity storage device, such as an SSD (Solid State Drive) or HDD (Hard Disk Drive), and accumulates medical information from an electronic medical record database 20 and patient information 50 from a customer acquisition media 30. Specifically, treatment information 22, prescription history information 24, etc. are stored in association with a 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 customer acquisition media 30. The input / output device 16 includes, for example, a display, a keyboard, a mouse, etc., and provides a user interface for exchanging information with medical staff. The generated proposal information is displayed on the display, and necessary information can be input and operated via the keyboard or mouse. This allows medical staff to operate the system intuitively and efficiently. This hardware configuration enables the information processing device 10 to achieve high-speed and stable processing capabilities, enabling it to efficiently process large amounts of patient information and medical treatment information.

[0023] The functional configuration of the information processing device 10 will be described with reference to Figure 3. The information processing device 10 includes a reception unit 110, a patient information acquisition unit 120, a medical information acquisition unit 130, a centralized information management unit 140, a prompt generation unit 150, and a proposal information generation unit 160. The patient information acquisition unit 120 acquires patient information by scraping from the database of the customer attraction media 30, 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 centralized information management unit 140 based on the patient ID 51, and analysis is performed using the machine learning model 40 based on instructions of the prompt generated by the prompt generation unit 150, and the proposal information generation unit 160 generates optimal medical service proposal information.

[0024] The processing steps in the information processing system 1 will be described in detail with reference to FIG. 4. First, the information processing device 10 connects to the electronic medical record database 20 (ST1) and the database of the customer acquisition media 30 (ST2). These connections are established via the communication interface 11 using a secure communication protocol. Next, the control unit 12 acquires patient information 50 (ST3). Specifically, the patient information acquisition unit 120 performs a scraping process on the database of the customer acquisition media 30 to acquire basic patient information, desired treatment, past inquiry history, etc. The acquired information is associated by the centralized information management unit 140 based on the patient ID 51. At this time, the patient information 50, such as name, age, address, contact information, and reservation history on the customer acquisition media 30, and medical information, such as medical treatment details, 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] Thereafter, the prompt generation unit 150 generates a diagnostic information analysis prompt P based on the accumulated medical information (ST5). This diagnostic information analysis prompt P includes the patient's age, sex, medical history, current symptoms, desired treatment, past treatment history 22, prescription history 24, etc. The diagnostic information analysis prompt P is generated, for example, in the following structure: (1) Basic information section: Basic data such as the patient's age, gender, height, and weight are placed in a structured data format such as "age:35;gender:female;height:165cm;weight:55kg". (2) Medical history section: Organize past medical information in chronological order and write it in a format such as "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 a format such as "desired_treatment: wrinkle removal; budget: 300000; preferred_date: weekend". (4) Constraints section: Medical constraints such as allergy information and medical history are described in a format such as "allergy:local anesthesia;previous_condition:high blood pressure".

[0026] The prompt generation algorithm involves the following steps: (1) The information required for each section is extracted from the electronic medical record database 20 and the database of the customer acquisition media 30. (2) Convert the extracted information 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 its placement within the prompt. (4) If there is missing data, skip the item or set a default value.

[0027] The generated diagnostic information analysis prompt P is sent to the proposal information generation unit 160 and used as input for analysis by the machine learning model 40. Based on the prompt structured in this way, the machine learning model 40 comprehensively analyzes the information in each section and generates optimal medical service proposal information R (ST6). The machine learning model 40 learns past treatment performance data, patient satisfaction data, etc., and proposes an optimal treatment plan tailored to the characteristics of each patient. Finally, the generated proposal information R is provided to the user, who is medical staff (ST7). The provided information includes recommended treatment content, expected treatment period, expected treatment effect, recommended next appointment date and time, etc., which allows medical staff to efficiently propose optimal medical services tailored to the patient's condition and requests. Other possible proposal information includes the following: 1. Treatment-related suggestions: - Proposal of treatment combinations (proposal of combined treatments that can be expected to have a synergistic effect) - Proposing alternative treatments (options that fit the patient's budget and time constraints) - Suggestions for stepping up / down treatment (step-by-step treatment plan according to the improvement of symptoms) - Proposal of post-operative care plan (home care method after surgery, etc.) 2. Reservation and Schedule Information: - Proposal of optimal treatment intervals - Proposals for treatment timing that take seasonality into consideration (such as avoiding periods with strong UV rays) - Maintenance appointment suggestions (regular follow-up) 3. Cost-related: - Propose payment plans (installments, loans, etc.) - Proposal of alternative treatments that are covered by insurance - Price proposals for package treatments 4. Risk Management Related: - Suggestions based on drug interaction checks - Proposing alternative treatments that take into account allergy risks - Suggestions for precautions based on medical history 5. Counseling-related: - Proposal for the best time to book a counseling appointment - Online / face-to-face counseling options - Recommendation of explanatory materials (selection of materials according to the patient's level of understanding) 6. Lifestyle Related: - Lifestyle improvement suggestions - Home care suggestions - Diet and exercise recommendations 7. Communication-related: - Suggestions for communication methods with patients (contact methods, frequency, etc.) - Suggestions for visual aids to use during explanations - Proposing explanation methods according to the patient's level of understanding 8. Follow-up related: - Proposed follow-up schedule - Proposal for timing to check the effectiveness of treatment - Suggested timing for patient satisfaction surveys 9. Inventory Management Related: - Propose to medical staff ways to improve inventory management efficiency based on equipment and drug usage.

[0028] The detailed flow of the medical service proposal information generation process will be described with reference to FIG. 5. The information processing device 10 generates an analysis prompt P based on acquired patient information 50 and medical information and applies it to the machine learning model 40. The machine learning model 40 learns data such as past treatment results and patient responses and comprehensively analyzes the input information. Specifically, it derives proposals optimized for each patient based on basic information such as the patient's age, gender, and medical history, as well as information such as past treatment history, prescription history, treatment effectiveness, and satisfaction level. In particular, using each patient's treatment response and satisfaction trends as learning data enables more accurate proposals. As a result, proposal information R, such as an optimized treatment plan and next appointment candidates for each patient ID 51, is generated. The generated proposal information R includes the specific recommended treatment content, expected treatment duration, expected treatment effectiveness, cost-effectiveness analysis results, and the optimal next appointment timing. In this way, utilizing comprehensive analysis using AI enables more effective and personalized medical service proposals, thereby simultaneously improving patient satisfaction and streamlining medical staff work.

[0029] Referring to FIG. 6, the management screen 200 provided to medical staff will be described. The management screen 200 displays, for each patient, information such as the patient's name, age, patient ID 51, application medium, reservation route, reservation type, treatment menu, chief complaint, desired treatment, reservation information, attending clinic, attending staff, equipment and facilities used, inquiry date, scheduled visit date, reservation status, sales, initial contract date, and treatment record in a list format such as display 210 and display 220. Medical staff can efficiently consider the optimal treatment plan for each patient. In this way, providing necessary information in a visually easy-to-understand format in a unified manner significantly improves the work efficiency of medical staff.

[0030] <Aspect 1> An information processing device (10) comprising: a communication interface (11) connected to an electronic medical record database (20) and a database of a plurality of customer acquisition media (30); and a control unit (12) that acquires patient information (50) from the database of the plurality of customer acquisition media (30) and associates the patient information (50) with medical information contained in the electronic medical record database (20) based on a patient ID (51) and manages them in a unified manner, 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 aspect, by managing the information recorded in the electronic medical record database and the databases of multiple customer acquisition media in an integrated manner, it becomes possible to effectively utilize patient information and medical information. Furthermore, this allows medical professionals to quickly and accurately grasp the medical history and current condition of patients, and by proposing medical services optimized for each patient, it can contribute to improving the efficiency of medical treatment and patient satisfaction.

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

[0033] According to this aspect, by including treatment information in the medical information, precise analysis based on the treatment details of the patient becomes possible. This allows medical professionals to specifically understand the effects of the treatment and plan the next treatment and follow-up based on scientific evidence, thereby improving the quality of treatment and increasing patient satisfaction with the treatment results.

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

[0035] According to this aspect, it is possible to accurately grasp a patient's treatment history based on medical information including prescription history information. This makes it possible to optimize the next treatment plan by referring to past treatment results and prescription contents, and is expected to ensure patient safety by preventing over-administration and duplicate administration of medicines, while also making effective use of medical resources.

[0036] <Aspect 4> The information processing device 10 according to any one of aspects 1 to 3, wherein the control unit 12 acquires patient information 50 from a plurality of customer-attracting media 30 by scraping.

[0037] This method uses scraping technology to efficiently collect patient information, enabling the provision of medical services based on the latest information. Furthermore, by collecting data from a wide range of sources, it is possible to accurately grasp patient needs that have traditionally been overlooked, and this can be reflected in the quality of the proposed information. Furthermore, automated information collection can reduce the workload of medical staff while enabling timely information updates.

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

[0039] According to this aspect, the machine learning model can be used to perform advanced analysis of patient information, making it easier for medical staff to create evidence-based treatment plans. This not only enables the promotion of personalized medicine and the provision of optimal treatment plans for each patient, but also reduces the burden on medical professionals and improves the accuracy of their decisions, contributing to the overall improvement of medical quality. Note that the information processing device may be equipped with the machine learning model, or an external device may be equipped with the machine learning model and the information processing device may be connected to the external device to perform analysis.

[0040] <Aspect 6> An information processing method in an information processing device (10), comprising the steps of connecting to an electronic medical record database (20) and the databases of multiple customer acquisition media (30), acquiring patient information (50) from the databases of the multiple 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 centrally managing the patient information (50), 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 embodiment realizes an efficient method for centrally managing information obtained from multiple databases and providing appropriate medical services based on the analysis results. This reduces information dispersion and management burden, and allows medical professionals to efficiently refer to patient data, improving the accuracy and satisfaction of medical care by providing optimal treatment plans for patients.

[0042] <Aspect 7> A program for connecting a computer to an electronic medical record database 20 and the databases of multiple customer acquisition media 30, acquiring patient information 50 from the databases of the multiple 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, 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.

[0043] According to this aspect, by executing the program, it becomes possible to efficiently provide medical proposals based on electronic medical records and patient information. In addition, it reduces the burden of complicated administrative work on medical 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 characterized by 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 the multiple customer acquisition media 30, associates the patient information 50 with medical information contained in the electronic medical record database 20 based on a patient ID 51 and centrally manages it, 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] According to this aspect, patient information can be efficiently managed throughout the entire system, enabling faster and more accurate medical proposals. Furthermore, by generating proposals that accurately reflect patient information, it is possible to support the judgment of medical professionals and improve the reliability and convenience of medical care for patients. Furthermore, appropriate access control in conjunction with the electronic medical record database enables the secure management of patient information. Analysis using a machine learning model makes it possible to propose more advanced and precise medical services. Note that the information processing system may be equipped with the machine learning model, or an external device may be equipped with the machine learning model and the information processing system may be connected to the external device to perform analysis. [Explanation of symbols]

[0046] 1. Information Processing Systems 10. Information processing equipment 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 Treatment planning proposal information 64 Next reservation suggestion 110 Reception 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 for connecting to an electronic medical record database and a plurality of customer acquisition media databases; an information unified management unit that associates the patient information acquired from the databases of the plurality of customer acquisition media with the medical information recorded in the electronic medical record database based on a common patient ID and manages them in a unified manner; a prompt generator that generates a prompt based on the patient information and the medical information; a proposal information generation unit that analyzes the medical information and the patient information using a machine learning model based on an instruction of the prompt generated by the prompt generation unit, and generates proposal information for medical services based on the analysis result; Equipped with The prompt generation unit A request section including the patient's desired treatment content, budget, and desired date and time acquired from the customer acquisition media; a medical history section in which past medical information acquired from the electronic medical record database is organized in chronological order; a basic information section including the patient's age, sex, height, and weight; a restrictions section including allergy information and medical history; Generates prompts structured into multiple sections, including converting the information in each section into a structured data format that can be interpreted by the machine learning model; The proposed information generating unit comprehensively analyzes information in each section of the structured prompt to generate proposed information for medical services, including recommended treatment content, treatment duration, expected treatment effect, and next recommended appointment date and time.

1. An information processing device comprising:

2. The information processing apparatus according to claim 1 , wherein the medical information includes treatment information for the patient.

3. The information processing device according to claim 1 , wherein the medical information includes prescription history information for the patient.

4. Further comprising a patient information acquisition unit that acquires the patient information from the databases of the plurality of customer attraction media by scraping, The patient information acquisition unit acquires information including basic information of the patient, desired treatment details, and past inquiry history from the customer acquisition media.

2. The information processing apparatus according to claim 1, wherein:

5. An information processing method in an information processing device, Connecting to an electronic medical record database and a database of a plurality of customer acquisition media; acquiring patient information from the databases of the plurality of customer acquisition media; a step of associating the acquired patient information with the medical information recorded in the electronic medical record database based on a common patient ID and managing them in an integrated manner; generating a prompt based on the patient information and the clinical information; analyzing the patient information and the medical information using a machine learning model based on the prompt, and generating medical service proposal information based on the analysis result; Including, The step of generating a prompt comprises: A request section including the patient's desired treatment content, budget, and desired date and time acquired from the customer acquisition media; a medical history section in which past medical information acquired from the electronic medical record database is organized in chronological order; a basic information section including the patient's age, sex, height, and weight; a restrictions section including allergy information and medical history; Generates prompts structured into multiple sections, including converting the information in each section into a structured data format that is interpretable by the machine learning model; The step of generating the recommendation information includes comprehensively analyzing the information in each section of the structured prompt to generate medical service recommendation information including recommended treatment content, treatment duration, expected treatment effect, and next recommended appointment date and time.

1. An information processing method comprising:

6. On the computer, Connect to the electronic medical record database and multiple customer acquisition media databases, Acquire patient information from the database of the plurality of customer acquisition media; The acquired patient information is associated with medical information recorded in the electronic medical record database based on a common patient ID and managed in a unified manner; generating a prompt based on the patient information and clinical information; Analyzing the prompt using a machine learning model, and generating medical service proposal information based on the analysis result. A program for executing a process, The process of generating the prompt includes: A request section including the patient's desired treatment content, budget, and desired date and time acquired from the customer acquisition media; a medical history section in which past medical information acquired from the electronic medical record database is organized in chronological order; a basic information section including the patient's age, sex, height, and weight; a restrictions section including allergy information and medical history; Generates prompts structured into multiple sections, including converting the information in each section into a structured data format that is interpretable by the machine learning model; The process of generating the recommendation information includes comprehensively analyzing the information in each section of the structured prompt to generate medical service recommendation information including recommended treatment content, treatment duration, expected treatment effect, and next recommended appointment date and time. program.

7. An electronic medical record database; a communication interface connected to the electronic medical record database and a database of a plurality of customer acquisition media; an information unified management unit that acquires patient information from the databases of the plurality of customer acquisition media, associates the patient information with medical information recorded in the electronic medical record database based on a common patient ID, and manages the patient information in a unified manner; a prompt generator that generates a prompt based on the patient information and the medical information; a proposal information generation unit that analyzes the patient information and the medical information using a machine learning model based on the prompt and generates proposal information for medical services based on the analysis result; Equipped with The prompt generation unit A request section including the patient's desired treatment content, budget, and desired date and time acquired from the customer acquisition media; a medical history section in which past medical information acquired from the electronic medical record database is organized in chronological order; a basic information section including the patient's age, sex, height, and weight; a restrictions section including allergy information and medical history; Generates prompts structured into multiple sections, including converting the information in each section into a structured data format that can be interpreted by the machine learning model; The proposed information generating unit comprehensively analyzes information in each section of the structured prompt to generate proposed information for medical services, including recommended treatment content, treatment duration, expected treatment effect, and next recommended appointment date and time. An information processing system comprising:

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