JP7759066B2 - Support information providing system, support information providing device, support information providing method and program - Google Patents

Description

The present invention relates to a support information provision system, a support information provision device, a support information provision method, and a program.

BACKGROUND ART Conventionally, information processing techniques for supporting the work of pharmacists in pharmacies have been known.
For example, Patent Document 1 describes that data on a patient's medication history is managed in a database, and when dispensing medicine to a patient, the database is referenced to provide medication instructions based on the medication history, etc.

Japanese Patent Application Laid-Open No. 2016-122253

However, even if data such as a patient's medication history is managed in a database, there is a wide range of information that pharmacists must consider when dispensing, and it is not easy for them to appropriately consider this information when providing medication instructions and other services. Furthermore, even if there is no change in the medication prescribed to a patient, it is desirable for pharmacists to provide appropriate instructions based on the information they obtain from meeting the patient face-to-face (conversation content, impressions, etc.), but providing such medication instructions requires a great deal of effort on the part of pharmacists.

The objective of this invention is to provide more appropriate support for pharmacists in their work.

In order to solve the above problems, a support information providing system according to one aspect of the present invention comprises:
A support information providing system including a terminal device and a server configured to be able to communicate via a network,
The terminal device
a support requesting means for transmitting a request to the server for generating support information for pharmaceutical guidance based on target information to be considered in pharmaceutical guidance for a patient;
a support information display means for displaying the support information transmitted from the server in response to a request from the support request means,
The server
a target information acquisition means for acquiring the target information based on a request from the support request means;
an intermediate state generating means for generating information representing an intermediate state expressed using pharmacological judgment factors as indexes when providing medication guidance by performing a first inference based on the target information;
a support information generating means for generating the support information by performing a second inference based on the information representing the intermediate state;
a support information providing means for providing the support information generated by the support information generating means to the terminal device;
Equipped with.

This invention makes it possible to more appropriately support the work of pharmacists.

1 is a diagram showing a system configuration of a support information providing system 1 according to an embodiment of the present invention. FIG. 2 is a schematic diagram showing an overview of a business support function provided in the support information providing server 30. FIG. 8 is a diagram showing the hardware configuration of an information processing device 800 that constitutes each device. FIG. 2 is a block diagram showing the functional configuration of the terminal device 10. FIG. 10 is a schematic diagram showing an example of a patient selection screen. FIG. 10 is a schematic diagram illustrating an example of a questionnaire display screen. FIG. 10 is a schematic diagram showing an example of a medical interview display screen. FIG. 10 is a schematic diagram showing an example of a support information display screen. FIG. 10 is a schematic diagram showing another example of the support information display screen. 2 is a block diagram showing the functional configuration of a pharmacy computer 20. FIG. 10 is a schematic diagram showing data relating to medication instruction statements among data relating to medications stored in a medication DB 176. FIG. FIG. 2 is a block diagram showing the functional configuration of the support information providing server 30. 10 is a flowchart showing the flow of support information display processing executed by the terminal device 10. 10 is a flowchart showing the flow of information management processing executed by the pharmacy computer 20. 10 is a flowchart showing the flow of support information providing processing executed by the support information providing server 30. 10 is a flowchart showing the flow of a reconstruction process executed by the support information providing server 30. FIG. 8 is a block diagram showing the functional configuration of a stand-alone information processing device 800 having a support information providing function. 10 is a schematic diagram showing an example of a display screen that displays patient information and the display contents of a support information display screen together. FIG.

Embodiments of the present invention will be described below with reference to the drawings.

FIG. 1 is a diagram showing the system configuration of a support information providing system 1 according to an embodiment of the present invention.
The support information providing system 1 in this embodiment is used to support the work of pharmacists at dispensing pharmacies, and presents recommended information to pharmacists to convey to patients, for example, when providing medication instructions to patients who have brought in prescriptions.

As shown in FIG. 1, the support information provision system 1 includes a terminal device 10, a pharmacy computer 20, and a support information provision server 30. The terminal device 10, the pharmacy computer 20, the support information provision server 30, and an external server such as a drug information database server that stores drug information including medication instructions are configured to be able to communicate via a network 40 (such as the Internet). The terminal device 10 and the pharmacy computer 20 may also be configured to be able to communicate via a private network such as a VPN (Virtual Private Network).

The terminal device 10 is operated by a pharmacist and is configured as an information processing device such as a tablet terminal or a PC (Personal Computer). The terminal device 10 displays information to support the pharmacist's work when the pharmacist interviews a patient and accepts information input by the pharmacist. For example, the terminal device 10 displays the interview content (interview content) when the pharmacist interviews a patient and accepts input of the interview results. The terminal device 10 also accepts input of the impression the pharmacist receives from the patient when they meet. Furthermore, the terminal device 10 displays support information (here, patient-related problems and recommended medication instructions) acquired by the support information display process described below based on patient information including the interview results (interview results, impressions, etc.). The patient problems are pharmaceutical judgment factors, including observation items, instruction guidelines, and points of focus, when the pharmacist provides medication instructions.

The pharmacy computer 20 is composed of an information processing device such as a server computer that executes processes related to the operations of the dispensing pharmacy. The pharmacy computer 20 also has the functions of a prescription computer (receipt computer function) and a function for managing patient medication histories (medication history management function), and manages various data such as patient attributes for multiple patients, multiple patient prescriptions, the history of prescribed medications (medication history), medical interview results (interview results and impressions, etc.), patient interview content, and information about medications handled at the pharmacy. The medication history managed by the pharmacy computer 20 includes the history of medication instructions (instruction history) given to patients by pharmacists. Furthermore, the pharmacy computer 20 executes the information management process described below to send various pieces of information it manages to the support information providing server 30 and update the various pieces of information it manages with various data sent from the support information providing server 30.

The support information providing server 30 is composed of an information processing device such as a server computer equipped with a function to support the work of pharmacists (work support function). The support information providing server 30 can accept support requests (requests for providing support information) from terminal devices 10 installed in multiple pharmacies, and by executing the support information providing process described below, it makes inferences by referencing patient attributes, medical interview results, and prescription data, and generates patient-related problems and recommended medication instructions (support information). The support information providing server 30 then transmits the generated support information (patient-related problems and recommended medication instructions) to the terminal device 10. The support information providing server 30 also receives various data managed by pharmacy computers 20 installed in multiple pharmacies and manages this data in a database similar to that of the pharmacy computers 20. In other words, the support information providing server 30 acquires information (part or all) held by the pharmacy computers 20 installed in multiple pharmacies and retains it in order to execute the support information providing process.

FIG. 2 is a schematic diagram showing an overview of the business support functions provided in the support information providing server 30. As shown in FIG.
2, the solid line blocks represent processes, and the dashed line blocks represent data. Among the solid line blocks, the thick line blocks are blocks to which computer inference (so-called artificial intelligence) is applied in this embodiment.
As shown in FIG. 2 , the support information providing server 30 extracts features from the prescription, patient attributes, and the results of interviews and impressions, and performs machine learning-based inference based on the extracted features to generate an intermediate state that outputs recommended medication instruction content. In this embodiment, the intermediate state generated at this time is represented using the patient's problem as an index. As described above, the patient's problem is a pharmaceutical judgment factor when a pharmacist provides medication instruction, including observation items, instruction guidelines, or points of focus. The intermediate state corresponds to an informational embodiment of one state of the pharmacist's thought process when providing medication instruction to the patient.

In addition, in FIG. 2, the support information providing server 30 generates recommended medication instruction content (support information) for the patient by performing rule-based inference from the generated intermediate state (i.e., the problem related to the patient).
In this way, an intermediate state is generated using machine learning-based inference from various data about the patient (patient attributes, medical interview results, prescription data, etc.), and recommended medication instructions are then generated from the intermediate state, allowing inference to be made using a procedure that conforms to the thought process of a pharmacist.
Furthermore, when inference is performed using deep learning or the like, it is generally difficult to grasp the inference process, making it difficult to determine the basis for the inference results. However, by performing two-stage inference via an intermediate state, as in this embodiment, it is possible to confirm the basis for the recommended medication instructions.

In this embodiment, the support information providing server 30 extracts features by natural language processing of the obtained interview results and impressions. The extracted features are predefined based on the thought process of the pharmacist when providing medication instructions (e.g., the patient's age, personality, etc.).
Furthermore, in this embodiment, the support information providing server 30 reconstructs the hearing contents (hearing items) by executing a reconstruction process (described later) based on the generated intermediate state (problems related to the patient) and the hearing contents (hearing items) conducted when this intermediate state was generated. This makes it possible, for example, to add hearing contents to the generated intermediate state (problems related to the patient) that enable the importance of each problem to be determined more clearly. Note that the reconstruction performed at this time is realized by using, for example, rule-based inference or machine learning-based inference.

As an example, when rule-based reasoning is used, table data is used that defines specific interview content (listening items) that are desirable to hear when the patient is in an intermediate state of various contents (problems related to the patient).The table data is then referenced to determine whether the specific interview content (listening items) defined for the generated intermediate state (problem related to the patient) was included in the actual interview content.If not, the specific interview content is added to subsequent interviews conducted with patients with similar patient attributes, etc., and the interview content is reconstructed.
Furthermore, when machine learning-based inference is used, the generated intermediate state (patient problem) is used as input, and supervised machine learning is performed using the content (question items) that a pharmacist (especially an experienced pharmacist) thinks should be interviewed with a patient who recalls the problem as training data, and the interview content is reconstructed. However, other machine learning methods (deep learning, etc.) can also be used for reconstruction.

[Hardware configuration]
Next, the hardware configuration of each device in the support information providing system 1 will be described.
In the support information providing system 1, each device is configured by an information processing device such as a PC, a server computer, or a tablet terminal, and the basic configurations thereof are the same.

FIG. 3 is a diagram showing the hardware configuration of the information processing device 800 that constitutes each device.
As shown in FIG. 3 , the information processing device 800 constituting each device includes a CPU (Central Processing Unit) 811, a ROM (Read Only Memory) 812, a RAM (Random Access Memory) 813, a bus 814, an input unit 815, an output unit 816, a storage unit 817, a communication unit 818, a drive 819, and an imaging unit 820.

The CPU 811 executes various processes according to a program recorded in the ROM 812 or a program loaded from the storage unit 817 to the RAM 813 .
The RAM 813 also stores data and the like necessary for the CPU 811 to execute various processes.

The CPU 811, ROM 812, and RAM 813 are interconnected via a bus 814. The input unit 815, output unit 816, memory unit 817, communication unit 818, drive 819, and imaging unit 820 are also connected to the bus 814.

The input unit 815 is made up of various buttons and the like, and various information is input in response to instruction operations.
The output unit 816 is composed of a display, a speaker, etc., and outputs images and sounds.
The storage unit 817 is configured with a hard disk or a DRAM (Dynamic Random Access Memory), and stores various data managed by each server.
The communication unit 818 controls communication with other devices via the network 40 .

Removable media 831, such as a magnetic disk, optical disk, magneto-optical disk, or semiconductor memory, is appropriately loaded into the drive 819. A program read from the removable media 831 by the drive 819 is installed in the storage unit 817 as necessary.
The imaging unit 820 is configured by an imaging device equipped with a lens, an imaging element, etc., and captures a digital image of a subject.
When the information processing device 800 is configured as the pharmacy computer 20 or the support information providing server 30, it is possible to omit the imaging unit 820. When the information processing device 800 is configured as a tablet terminal, it is also possible to configure the input unit 815 using a touch sensor and place it over the display of the output unit 816, thereby providing a touch panel.

[Functional configuration]
Next, the functional configuration of each device in the support information providing system 1 will be described.

[Functional configuration of terminal device 10]
FIG. 4 is a block diagram showing the functional configuration of the terminal device 10. As shown in FIG.
As shown in FIG. 4, a user interface display control unit (UI display control unit) 51, a target information acquisition unit 52, a support request unit 53, and a support information acquisition unit 54 function in the CPU 811 of the terminal device 10.

The UI display control unit 51 controls the display of various input/output screens (hereinafter referred to as "UI screens") in the support information display process based on information for displaying user interface screens (hereinafter referred to as "UI information") received from the support information providing server 30. For example, the UI display control unit 51 displays (outputs to a display) a screen for selecting a patient to whom support information is to be provided in the support information display process (hereinafter referred to as the "patient selection screen"), a screen displaying the contents of a questionnaire administered to the patient at their first visit (hereinafter referred to as the "questionnaire display screen"), a screen displaying the contents of interviews (questionnaire items) conducted by a pharmacist when interviewing the patient (hereinafter referred to as the "interview display screen"), and a screen displaying support information (patient-related problems and medication instructions) provided by the support information provision process (hereinafter referred to as the "support information display screen"). The UI display control unit 51 also transmits various information entered on the UI screens to the support information providing server 30. For example, the UI display control unit 51 transmits information identifying a patient selected on the patient selection screen, questionnaire results entered on the questionnaire display screen, or medical interview results entered on the medical interview display screen to the support information providing server 30. Furthermore, the UI display control unit 51 transmits the results of medication instructions (medication instruction results) provided by a pharmacist on the support information display screen to the support information providing server 30 in response to a confirmation operation by the pharmacist (such as operation of the "Send to medication history" button). The UI display control unit 51 may also transmit various information entered on the UI screen (for example, patient attributes related to a new patient visiting the pharmacy) to the pharmacy computer 20 along with the support information providing server 30.

FIG. 5 is a schematic diagram showing an example of the patient selection screen.
5, the patient selection screen displays a list of patients corresponding to the patient attributes managed by the pharmacy computer 20, and the pharmacist selects a patient to interview from this list. For new patients, new patient attributes are registered on a registration screen (not shown).

FIG. 6 is a schematic diagram showing an example of a questionnaire display screen.
As shown in Figure 6, the questionnaire display screen displays the questionnaire contents, including multiple-choice questions, and the patient enters the answers themselves, or the pharmacist enters the answers based on the patient's answers. The questionnaire contents displayed at this time are a series of questions set in common for all patients, and are used to identify patient attributes such as the patient's name, gender, medical history, and illnesses currently being treated.

FIG. 7 is a schematic diagram showing an example of a medical interview display screen.
As shown in FIG. 7 , the medical interview display screen displays interview content (interview items) including multiple-choice questions, and the pharmacist inputs the interview results (interview results) based on the patient's answers. The displayed interview content is a series of questions selected according to patient attributes, and is determined for each patient, each prescription, or the number of interviews (e.g., whether it is the first interview or the second interview), etc. The medical interview display screen also has a free entry field for the pharmacist, allowing the pharmacist to freely enter any information they noticed when interviewing the patient (e.g., physical impressions such as "lack of energy" or "pale complexion," or personality impressions such as "nervous personality" or "judgmental personality").

FIG. 8 is a schematic diagram showing an example of a support information display screen.
As shown in FIG. 8 , the support information display screen generally displays pharmaceutical decision-making factors (patient problems) when a pharmacist (especially an experienced pharmacist) provides medication instruction. The patient problems displayed at this time include observation items that the pharmacist recalls for the patient to whom the pharmacist provides medication instruction, the guidance guidelines that the pharmacist envisions for medication instruction, and indicators (points of focus) that the pharmacist recalls in the thought process that the pharmacist follows when providing medication instruction. In this embodiment, patient problems (observation items, points of focus, guidance guidelines, etc.) are presented by classifying them into multiple categories, such as "side effects,""adherence,""changes in physical condition,""concomitant medications (drug interactions),""elderly," and "lifestyle guidance." The method of determining the classification when presenting patient problems (e.g., the number of categories, specificity, etc.) can be preset or can be changed depending on the inference results.

Furthermore, in this embodiment, the relevance (here, a percentage indicating the importance) of a patient to each category of these patient-related problems is calculated based on the patient attributes, medication history, questionnaire results, and interview results of the patient who answered the medical interview. By referring to the relevance of the presented patient-related problems, a pharmacist who receives the support information can easily recognize what perspectives to pay attention to when providing medication instructions to the patient who answered the medical interview. Furthermore, the pharmacist can recognize the difference between the pharmacist's own thinking results and the relevance of the patient-related problems presented in the support information, which can be useful for the pharmacist's self-evaluation or self-improvement.
Furthermore, if the pharmacist recorded a problem regarding the patient for whom the next instruction is to be given during the previous instruction given to the patient, the recorded problem regarding the patient will be displayed in an identifiable manner (by using a different background color, surrounding it with a frame, blinking, etc.) on the support information display screen shown in Figure 8.

FIG. 9 is a schematic diagram showing another example of the support information display screen.
As shown in FIG. 9 , the support information display screen displays a list of medication instruction sentences indicating recommended medication instruction contents for the patient who has been interviewed (hereinafter referred to as the “recommended medication instruction sentence list”) and a list of general medication instruction sentences for the prescribed medication (hereinafter referred to as the “general medication instruction sentence list”). The recommended medication instruction sentence list represents a list of medication instruction sentences selected based on the patient problems identified by the support information provision process and their relevance, and reflects the observation items that pharmacists (especially experienced pharmacists) recall for the patients to whom they are providing medication instruction, the guidance guidelines that pharmacists envision in providing medication instruction, and the indicators (points of view) that pharmacists recall in their thought process when providing medication instruction. The general medication instruction sentence list represents results selected in accordance with the medication to be prescribed based on the patient's prescription data. In addition, each medication instruction statement is accompanied by a check box, and once the pharmacist has checked the medication instruction statement, it is confirmed by the pharmacist (by pressing the "Send to medication history" button, etc.) and registered in the patient's medication history as a list of medication instruction statements used for medication instructions (medication instruction results).
In addition, on the support information display screen of Figure 9, the pharmacist can perform an operation to input a problem regarding the patient for whom the next instruction should be given (input operation of the next instruction content), and the input content can be recorded in the medication history by the pharmacist performing a confirmation operation (such as operating the ``Send to medication history'' button).

The target information acquisition unit 52 acquires various pieces of information to be considered about patients for whom medication instructions are to be given (hereinafter referred to as "information to be considered"). In other words, information to be considered is information to be taken into consideration when providing pharmaceutical instructions to patients. For example, the target information acquisition unit 52 acquires questionnaire result data including patient attribute data for identifying patients, such as the name, age, medical history, and illnesses being treated of the patient who brought the prescription; data on the results of the medical interview (interview results, impressions, etc.) entered by the pharmacist on the medical interview display screen; data indicating the contents of the prescription brought by the patient (prescription data); etc. Note that the information acquired by the target information acquisition unit 52 is not limited to this; it is also possible to acquire data on the patient's medication history, data on the contents of medication instructions given to the patient at their previous visit, or data stored in an electronic medication notebook.

The support request unit 53 transmits a request for support information to the support information providing server 30 together with the consideration target information acquired by the target information acquisition unit 52 .
The support information acquisition unit 54 acquires support information transmitted from the support information providing server 30 in response to the support information request transmitted by the support request unit 53. The support information acquired by the support information acquisition unit 54 includes data on the problem relating to the patient, a list of medication instructions indicating the contents of recommended medication instructions (list of recommended medication instructions), and a list of general medication instructions relating to prescribed drugs (list of general medication instructions).

[Functional Configuration of Pharmacy Computer 20]
FIG. 10 is a block diagram showing the functional configuration of the pharmacy computer 20.
10 , a receipt management unit 151, a medication history management unit 152, and a database management unit (DB management unit) 153 function in the CPU 811 of the pharmacy computer 20. In addition, a patient attribute database (patient attribute DB) 171, a prescription database (prescription DB) 172, a medication history database (medication history DB) 173, a medical interview result database (medication result DB) 174, a hearing content database (hearing content DB) 175, and a drug database (drug DB) 176 are formed in the storage unit 817 of the pharmacy computer 20.

The patient attribute DB 171 stores data on patient attributes, such as the patient's address, name, age, sex, and various information that represents the patient's individual characteristics. These patient attributes are composed of information acquired by pharmacists through conversations with patients, information provided by patients in response to questionnaires, etc., and include, for example, the patient's hobbies, work, family structure, favorite foods, etc.
The prescription DB 172 stores data on prescriptions issued to patients in association with information identifying each patient and the date the prescription was brought in.
The medication history DB 173 stores data on the history of medications prescribed to patients (medication history) in association with information identifying each patient. The medication history also stores data on the history of medication instructions (instruction history) given to patients by pharmacists.

The medical interview result DB 174 stores the results of medical interviews conducted with patients in association with information identifying each patient and the date and time of the interview. The medical interview results include the results of interviews entered by pharmacists after interviewing patients, and impressions entered by pharmacists based on the impressions they received from patients they met.
The hearing content DB 175 stores data of a list of hearing content (question items) to be asked of patients, such as "Have you forgotten to take your medicine?" or "Has your physical condition changed since taking your medicine?"
The drug DB 176 stores data on various drugs handled at pharmacies. This drug data includes the drug name (generic name), drug code, and the like, as well as the contents of medication instructions and package inserts.

FIG. 11 is a schematic diagram showing data relating to medication instruction statements among data relating to medications stored in the medication DB 176. As shown in FIG.
As shown in FIG. 11 , each drug identified by a drug code and drug name is associated with multiple medication instruction sentences provided by the drug manufacturer. In FIG. 11 , a serial number (instruction sentence number) is assigned to each medication instruction sentence associated with each drug. Each medication instruction sentence is also associated with a problem related to one patient or problems related to multiple patients. In this embodiment, the relevance of the patient problem to the information to be considered of the patient for which support information is to be provided is calculated using the inference described below. A high relevance of the patient problem to the information to be considered means that the importance of the medication instruction sentence associated with the problem related to the patient is relatively high for the information to be considered.

The medical receipt management unit 151 acquires information necessary for a patient's medical receipt (patient attributes, prescription contents, medical insurance points, etc.) and performs the medical receipt issuance process.
The medication history management unit 152 manages the history of medications prescribed to a patient (medication history). For example, when a new prescription is given to a patient, the medication history management unit 152 stores data on the history of the currently prescribed medication (current medication history) in the medication history DB 173, and when a request to send the patient's medication history data is received from the terminal device 10, the medication history management unit 152 obtains the requested medication history data from the medication history DB 173 and sends it to the terminal device 10.

The DB management unit 153 manages the synchronization of data in the various databases managed by the pharmacy computer 20 with data in the various databases provided in the support information providing server 30. For example, when the DB management unit 153 receives a request from the support information providing server 30 to send a patient's medication history data, it retrieves the requested medication history data from the medication history DB 173 and sends it to the support information providing server 30. The DB management unit 153 also sends updated data in the various databases managed by the pharmacy computer 20 to the support information providing server 30 at a preset time (e.g., 3:00 a.m.), and receives updated data in the various databases in the support information providing server 30 from the support information providing server 30 and updates the various databases it manages.

[Functional configuration of the support information providing server 30]
FIG. 12 is a block diagram showing the functional configuration of the support information providing server 30. As shown in FIG.
12 , the CPU 811 of the support information providing server 30 functions as follows: a DB management unit 251, a user interface information generation unit (UI information generation unit) 252, a support request reception unit 253, a target information acquisition unit 254, a feature extraction unit 255, a problem identification unit 256, a presented information evaluation unit 257, a support information generation unit 258, a support information provision unit 259, and a reconstruction execution unit 260. The storage unit 817 of the support information providing server 30 also stores a patient attribute database (patient attribute DB) 271, a prescription database (prescription DB) 272, a medication history database (medication history DB) 273, a medical interview result database (medication result DB) 274, a hearing content database (hearing content DB) 275, and a drug database (drug DB) 276.
The contents stored in each database and the contents stored in the pharmacy computer 20 are synchronized by the DB management unit 251.

The DB management unit 251 manages the synchronization of data in various databases provided on the support information providing server 30 with data in various databases managed by the pharmacy computer 20. For example, at a preset time (e.g., 3:00 AM), the DB management unit 251 transmits data from various databases updated on the support information providing server 30 to the pharmacy computer 20, and receives updated data from the various databases managed by the pharmacy computer 20 and updates the various databases it manages.

The UI information generation unit 252 generates UI information for the terminal device 10 to display a UI screen and transmits the generated UI information to the terminal device 10. Specifically, the UI information generation unit 252 generates, as UI information, a frame format for displaying the UI screen and substantive content to be inserted into the format. In this embodiment, the substantive content to be inserted into the format includes, for example, patient attributes on the patient selection screen, questionnaire content on the questionnaire display screen, hearing content on the medical interview display screen, and support information on the support information display screen. In addition, in response to transmitting UI information to the terminal device 10, the UI information generation unit 252 receives various information (information identifying the patient, questionnaire result data, prescription data, medical interview result data, etc.) transmitted from the terminal device 10. Furthermore, the UI information generation unit 252 infers hearing content appropriate for the patient based on the information to be considered that has been grasped up to the current medical interview, and generates the substantive content (hearing content) to be inserted into the medical interview display screen. The interview content displayed on the medical interview display screen will be reconstructed as described below.

The support request receiving unit 253 receives a request for support information from the terminal device 10 together with the currently input consideration subject information.
The target information acquisition unit 254 acquires the consideration subject information transmitted from the terminal device 10 and the consideration subject information stored in each database. Note that the consideration subject information stored in each database is acquired when necessary, and for example, when information identifying a patient is transmitted from the terminal device 10, data on the patient attributes of that patient is acquired as one of the consideration subject information.

The feature extraction unit 255 references the consideration information received by the support request reception unit 253 and the consideration information acquired from each database, and extracts pre-defined features. At this time, the feature extraction unit 255 performs natural language processing to extract words representing features included in the consideration information, or extract features calculated or estimated from the consideration information. For example, if "patient's age" is defined as a feature, the feature extraction unit 255 extracts words representing the patient's age included in the consideration information. Furthermore, if "visit interval" is defined as a feature, the feature extraction unit 255 calculates the visit interval (i.e., the difference between the date of the previous visit and the date of the current visit) from the visit date included in the consideration information.

The problem identification unit 256 performs machine learning-based inference using the feature quantities extracted by the feature extraction unit 255 as input, and generates an intermediate state represented using the patient problem as an index. In this embodiment, the problem identification unit 256 is equipped with an inference engine built by machine learning to determine what pharmaceutical decision factors (patient problems) a pharmacist (especially an experienced pharmacist) would associate with a patient when recognizing the feature quantities. Therefore, the intermediate state generated by the problem identification unit 256 represents the result of inferring the pharmaceutical decision factors that a pharmacist would associate with a patient when the target patient's information of interest is given.
Furthermore, in this embodiment, when the problem identification unit 256 generates a patient-related problem as an index of an intermediate state, it also generates the relevance of the patient-related problem to the information under consideration. That is, the inference engine provided in the problem identification unit 256 has been machine-learned to learn what pharmaceutical judgment factors (patient-related problems) are associated with a patient when a pharmacist (especially an experienced pharmacist) recognizes a feature, including the relevance of the patient-related problem.

The presented information evaluation unit 257 evaluates each medication instruction sentence related to the patient problem by performing rule-based inference based on the patient problem identified by the problem identification unit 256 and the relevance of the patient problem. For example, the presented information evaluation unit 257 weights each medication instruction sentence with a numerical value indicating the relevance of the patient problem to which the medication instruction sentence is related, and determines an evaluation value for the medication instruction sentence associated with the patient problem. Note that a weight for the medication instruction sentence may be set for each drug, and the evaluation value for the medication instruction sentence may be determined by further reflecting the numerical value indicating the relevance of the patient problem to this weight.
The evaluation value is determined in this way, and medication instruction sentences that are assigned an evaluation value equal to or greater than a preset threshold value belong to the list of recommended medication instruction sentences. On the other hand, medication instruction sentences that are assigned an evaluation value less than the preset threshold value belong to the list of general medication instruction sentences.

The support information generation unit 258 acquires data on the patient's problem identified by the presented information evaluation unit 257. Furthermore, the support information generation unit 258 acquires medication instruction sentences from the drug DB 276 as medication instruction content (support information) recommended for the patient based on the evaluation value of the medication instruction sentence determined by the presented information evaluation unit 257. That is, the support information generation unit 258 acquires medication instruction sentences evaluated based on the relevance of the patient's problem, and generates data on a list of recommended medication instruction sentences by sorting medication instruction sentences that have been assigned an evaluation value equal to or greater than a predetermined threshold in descending order of evaluation value. Furthermore, the support information generation unit 258 acquires medication instruction sentences that have been assigned an evaluation value by the presented information evaluation unit 257 and have an evaluation value below a predetermined threshold, and sorts them in a predetermined order to generate data on a list of general medication instruction sentences. The predetermined order can take various forms, but one example is to order them by frequency of reference. The support information generation unit 258 then generates support information including data on patient-related problems and the relationships between patient-related problems, data on a list of recommended medication instructions, and data on a list of general medication instructions, and outputs this to the support information provision unit 259.

The support information providing unit 259 transmits the support information input from the support information generating unit 258 (information including data on problems related to the patient and the relevance of problems related to the patient, data on a list of recommended medication instructions, and data on a list of general medication instructions) to the terminal device 10 (output to the terminal device 10 via the network 40).
The reconstruction executing unit 260 corrects the hearing contents (listening items) by performing reconstruction based on the data of the hearing contents in the consideration target information received by the support request receiving unit 253 and the intermediate state (problem related to the patient) generated by the problem identifying unit 256. For example, the reconstruction executing unit 260 reconstructs the hearing contents (listening items) by using rule-based inference or machine learning-based inference.

[Operation]
Next, the operation of the support information providing system 1 will be described.

[Support information display process]
FIG. 13 is a flowchart showing the flow of the support information display process executed by the terminal device 10.
The support information display process is started in response to an instruction to execute the support information display process being input via the input unit 815 of the terminal device 10 .
In step S1, the UI display control unit 51 receives UI information from the support information providing server 30 and displays a patient selection screen.
In step S2, the UI display control unit 51 receives a selection of a patient to be interviewed, thereby specifying information for identifying the patient.

In step S3, the UI display control unit 51 receives input of prescription data issued to the selected patient. The patient identification information and prescription data are sent to the support information providing server 30.
In step S4, the UI display control unit 51 receives UI information from the support information providing server 30 and displays a medical interview display screen corresponding to the selected patient. If the patient to be interviewed is visiting the clinic for the first time, the UI display control unit 51 receives UI information from the support information providing server 30, displays a questionnaire display screen, and accepts input on the questionnaire display screen. After transmitting the questionnaire results entered on the questionnaire display screen to the support information providing server 30, the UI display control unit 51 again receives UI information for the medical interview display screen and displays a medical interview display screen corresponding to the patient.

In step S5, the UI display control unit 51 receives an answer to the medical interview display screen. The answer data to the medical interview display screen (medical interview result) is sent to the support information providing server 30.
In step S6, the target information acquisition unit 52 acquires various pieces of information to be considered (information to be considered) from the information input to the UI screen regarding the patient for whom medication instruction is to be given.
In step S7, the support request unit 53 transmits a request for providing support information to the support information providing server 30 together with the consideration target information acquired by the target information acquisition unit 52.
In step S<b>8 , the support information acquisition unit 54 acquires UI information including support information transmitted from the support information providing server 30 in response to the support information request transmitted by the support request unit 53 .

In step S9, the UI display control unit 51 displays a support information display screen showing a problem related to the patient based on the acquired UI information.
In step S10, the UI display control unit 51 determines whether or not an operation to display recommended medication instruction contents (such as an operation of the "Instruction" button) has been performed.
If the operation to display the recommended medication instruction contents has not been performed, the result of step S10 is determined to be NO, and the process proceeds to step S9.
On the other hand, if an operation to display recommended medication instruction contents has been performed, a determination of YES is made in step S10, and the process proceeds to step S11.

In step S11, the UI display control unit 51 displays a support information display screen showing recommended medication instruction content based on the UI information acquired in step S9.
In step S12, the UI display control unit 51 determines whether or not an operation has been performed on the support information display screen showing the recommended medication instruction content.
At this time, the UI display control unit 51 accepts operations such as checking the checkbox of the medication instruction message and inputting the next instruction content.
If an operation is performed on the support information display screen showing the recommended medication instruction content, a determination of YES is made in step S12, and the process proceeds to step S11.
On the other hand, if no operation has been performed on the support information display screen, the result of the determination in step S12 is NO, and the process proceeds to step S13.

In step S13, the UI display control unit 51 determines whether or not an operation to end the display of the support information display screen has been performed.
If an operation to terminate the display of the support information display screen has not been performed, the result of the determination in step S13 is NO, and the process proceeds to step S11.
On the other hand, if an operation to terminate the display of the support information display screen has been performed, the result of the determination in step S13 is YES, and the support information display process is terminated.

[Information management processing]
FIG. 14 is a flowchart showing the flow of the information management process executed by the pharmacy computer 20.
The information management process is started in response to an instruction to execute the information management process being input via the input unit 815 of the pharmacy computer 20 .

In step S21, the DB management unit 153 determines whether or not a prescription for a patient has been received.
If the patient's prescription has not been received, the determination in step S21 is NO, and the process proceeds to step S23.
On the other hand, if the patient's prescription has been received, the determination in step S21 is YES, and the process proceeds to step S22.
In step S22, the DB management unit 153 updates the patient attribute DB 171 and the prescription DB 172 with the data of the currently accepted prescription.

In step S23, the DB management unit 153 determines whether or not a request to transmit the patient's medication history data has been received from the support information providing server 30.
If a request to transmit the patient's medication history data has not been received from the support information providing server 30, the result of step S23 is determined to be NO, and the process proceeds to step S25.
On the other hand, if a request to transmit the patient's medication history data is received from the support information providing server 30, the answer in step S23 is YES, and the process proceeds to step S24.
In step S24, the DB management unit 153 transmits the requested medication history data of the patient to the support information providing server 30.

In step S25, the DB management unit 153 determines whether or not the current medication history data (such as data on the medication instruction content explained to the patient) has been received from the support information providing server 30.
If the current medication history data has not been received from the support information providing server 30, the determination in step S25 is NO, and the process proceeds to step S27.
On the other hand, if the current medication history data has been received from the support information providing server 30, the determination in step S25 is YES, and the process proceeds to step S26.
In step S26, the DB management unit 153 updates the medication history DB 173 with the received medication history data.

In step S27, the DB management unit 153 determines whether it is the predetermined timing for synchronizing the data of the various databases managed by the pharmacy computer 20 with the data of the various databases provided on the support information providing server 30.
If the predetermined timing for synchronizing the data of the various databases managed by the pharmacy computer 20 with the data of the various databases provided on the support information providing server 30 has not arrived, step S27 is judged as NO and the information management process is repeated.
On the other hand, if the timing has arrived at a predetermined time for synchronizing the data in the various databases managed by the pharmacy computer 20 with the data in the various databases provided on the support information providing server 30, the answer in step S27 is YES, and processing proceeds to step S28.

In step S28, the DB management unit 153 updates each database by sending and receiving data with the support information providing server 30, and synchronizes the data in the various databases managed by the pharmacy computer 20 with the data in the various databases provided on the support information providing server 30.
After step S28, the information management process is repeated.

[Support information provision processing]
FIG. 15 is a flowchart showing the flow of the support information providing process executed by the support information providing server 30.
The support information providing process is started in response to an instruction to execute the support information providing process being input via the input unit 815 of the support information providing server 30 .

In step S41, the support request receiving unit 253 receives a request to provide support information together with consideration subject information from the terminal device 10.
In step S42, the feature extraction unit 255 performs natural language processing on the received information to be considered (hearing results and impressions).
In step S43, the feature extraction unit 255 extracts feature amounts from the consideration object information.
In step S44, the problem identification unit 256 performs machine learning-based inference using the feature quantities extracted by the feature extraction unit 255 as input, and generates an intermediate state represented by an index of the problem related to the patient. At this time, the relevance of the problem related to the patient to the information under consideration is also generated.

In step S45, the presented information evaluation unit 257 performs rule-based inference based on the patient-related problems identified by the problem identification unit 256 and the relevance of the patient-related problems, thereby evaluating each medication instruction statement related to the patient-related problems.

In step S46, the support information generation unit 258 acquires medication instruction sentences from the drug DB 176 as medication instruction content (support information) recommended for the patient based on the evaluation value of the medication instruction sentence determined by the presented information evaluation unit 257. That is, the support information generation unit 258 acquires medication instruction sentences evaluated based on the relevance of the medication instruction sentence to the patient's problem, and generates data on a list of recommended medication instruction sentences by sorting medication instruction sentences that have been assigned an evaluation value equal to or greater than a predetermined threshold in descending order of evaluation value. In addition, the support information generation unit 258 acquires medication instruction sentences that have been assigned an evaluation value by the presented information evaluation unit 257 and have an evaluation value below a predetermined threshold, and sorts them in a predetermined order to generate data on a list of general medication instruction sentences. As a result, support information including data on a list of recommended medication instruction sentences and data on a list of general medication instruction sentences is generated.

In step S47, the support information providing unit 259 transmits the support information input from the support information generating unit 258 (information including data on problems related to the patient and the relevance of problems related to the patient, data on a list of recommended medication instructions, and data on a list of general medication instructions) to the terminal device 10 (output to the terminal device 10 via the network 40).
After step S47, the support information providing process is repeated.

[Reconstruction process]
FIG. 16 is a flowchart showing the flow of the reconstruction process executed by the support information providing server 30.
The reconstruction process is started in response to an instruction to execute the reconstruction process being input via the input unit 815 of the support information providing server 30. Note that the reconstruction process may be executed every time the support information providing process is executed, or at a preset time (for example, 3:00 a.m.).

In step S51, the reconstruction executing unit 260 acquires data on the interview contents in the consideration information acquired in the provision of support information for a plurality of patients, and the generated intermediate state (problem related to the patient).
In step S52, the reconstruction execution unit 260 reconstructs the hearing content based on the data of the hearing content in the consideration information received by the support request receiving unit 253 and the intermediate state (problem related to the patient) generated by the problem identification unit 256.
After step S52, the reconstruction process ends.

As described above, the support information provision system 1 according to this embodiment acquires various information to be considered for a patient for whom medication instructions are to be provided, such as patient attribute data for the patient who brought a prescription, medical interview result data entered on the medical interview display screen, and prescription data indicating the contents of the prescription brought by the patient. Features are then extracted from the information to be considered, and machine learning-based inference is performed using the features as input to generate an intermediate state represented by an index of the patient's problem. At this time, the relevance of the patient's problem to the information to be considered is also generated. Furthermore, rule-based inference is performed based on the patient's problem and the relevance of the patient's problem to evaluate each medication instruction statement related to the patient's problem, and support information including recommended medication instruction statements is provided based on the evaluation results.

Therefore, by performing a first inference (here, machine learning-based inference) from the information to be considered, an intermediate state (patient problem) can be generated that embodies as information one state of the thought process in which the pharmacist provides medication instructions to the patient. Furthermore, by performing a second inference (here, rule-based inference) from the intermediate state (patient problem), support information including recommended medication instructions is generated.
Therefore, it becomes possible to support medication instruction using computer-based inference, thereby more appropriately supporting the work of pharmacists.
Furthermore, when medication instruction is assisted by a computer, appropriate medication instruction statements can be inferred using a procedure that conforms to the thought process of a pharmacist.
Furthermore, when inference is performed using deep learning or the like, it is generally difficult to grasp the inference process, making it difficult to determine the basis for the inference results. However, by performing two-stage inference via an intermediate state, as in this embodiment, it is possible to confirm the basis for the recommended medication instructions.

[Modification 1]
In the above embodiment, a client-server type support information providing system 1 is constructed, and a request for support information is made from the terminal device 10 to the support information providing server 30 to obtain the support information.
In contrast, by providing the support information provision function of the support information provision server 30 in a single device (e.g., a terminal device 10 or a pharmacy computer 20, etc.), the functions of the support information provision system 1 can be realized in a single information processing device 800 (i.e., as a stand-alone system).

FIG. 17 is a block diagram showing the functional configuration of a stand-alone information processing device 800 having a support information providing function.
As shown in FIG. 17 , when configured as a standalone type, in a single information processing device 800, the functions of the UI display control unit 51 of the terminal device 10, the UI information generation unit 252 of the support information providing server 30, the support request reception unit 253, the target information acquisition unit 254, the feature extraction unit 255, the problem identification unit 256, the presented information evaluation unit 257, the support information generation unit 258, the support information provision unit 259, and the reconstruction execution unit 260 are provided in a CPU 811, and each database managed by the support information providing server 30 (or the pharmacy computer 20) is provided in a memory unit 817.

Furthermore, when the support information providing system 1 is configured as a client-server system, the combination of information processing devices that configure the system is not limited to the examples shown in the above-described embodiments.
For example, it is possible to distribute the functions of the pharmacy computer 20 or the support information providing server 30 across more servers, or to integrate the functions of the pharmacy computer 20 and the support information providing server 30 into a single server.

[Modification 2]
In the above embodiment, an example has been described in which six types of problems shown in FIG. 6 are displayed as problems relating to patients.
In contrast, it is possible to display problems relating to a wider variety of patients.
It is also possible to sequentially set the number of problems related to the patient according to the patient attributes and prescription data, and display intermediate states.
Furthermore, when generating a problem relating to a patient, it is possible to provide a range of content for the problem relating to the patient, such as making the content more specific or more abstract.
This makes it possible to more appropriately represent the thought process that pharmacists use when providing medication instructions to patients.

[Modification 3]
In the above-described embodiment, a first stage of inference is performed from the information under consideration to generate an intermediate state (a problem relating to the patient) that embodies as information one state of the thought process in which a pharmacist provides medication instructions to a patient, and a second stage of inference is performed from the intermediate state (the problem relating to the patient) to generate support information including recommended medication instructions.
In contrast to this, by performing inference at more stages, it is possible to generate intermediate states at multiple stages and display them appropriately.

For example, one state of the thought process for providing medication instructions to a patient can be set to n stages (n is an integer of 2 or greater) according to the level of abstraction, and n intermediate stages that embody these can be generated. In this case, from the information to be considered, a first intermediate stage is generated by a first inference, a second intermediate stage is generated from the first intermediate stage by a second inference, and sequentially an n-th intermediate stage is generated by an n-th inference. Then, support information including a recommended medication instruction sentence can be generated from the n-th intermediate stage by an n+1-th inference.
As an example, when generating an intermediate state, machine learning-based inference can be performed, and when generating support information including recommended medication instructions, rule-based inference can be performed.
This makes it possible to more specifically trace the thought process of pharmacists (especially experienced pharmacists) when providing medication instructions to patients, while dividing the pharmacist's thought process into more appropriate stages and showing intermediate states (problems related to the patient).
Therefore, it becomes possible to more appropriately support the work of pharmacists.

[Modification 4]
In the above-described embodiment, the display format of the screen displayed after selecting a patient on the patient selection screen (see Figure 5) can be various display formats in addition to the example described in the above-described embodiment.
For example, after selecting a specific patient on the patient selection screen, the patient information of that patient may be displayed together with some or all of the display contents of the support information display screen (see Figures 8 and 9).
FIG. 18 is a schematic diagram showing an example of a display screen that displays patient information and the display contents of the support information display screen together.
As shown in Figure 18, after a specific patient (here, patient A) is selected on the patient selection screen, the patient information, prescription contents, and part of the contents of the support information display screen for the specific patient can be displayed on one screen.
In FIG. 18, icons for various operations, the patient's name, age, sex, name of the pharmacist in charge, the patient's problem, prescription contents, recommended medication instructions, etc. are displayed on one screen.
Icons for various operations can include, for example, a "history" icon for displaying prescription details, a "medication instructions" icon for displaying a screen for selecting medication instructions, and a "side effects" icon for displaying side effects related to the prescribed drug. Furthermore, recommended medication instructions can be displayed by default, for example, instructions related to high-risk drugs, instructions related to side effects reported by patients, and a predetermined number of instructions inferred to be of higher importance.
When the display screen shown in Fig. 18 is displayed, in response to an operation of an icon for various operations, another display screen (e.g., the support information display screens of Fig. 8 and Fig. 9 ) corresponding to the operated icon can be displayed by switching to the display screen shown in Fig. 18 or in addition to the display screen shown in Fig. 18. Contents input on the other display screens (e.g., parameter values related to inference, etc.) can be sequentially reflected and displayed on the display screen shown in Fig. 18.
By using such a display format, it is possible to display multiple pieces of information about a patient in a clear and easy-to-read format, thereby more appropriately supporting the work of pharmacists.
The display contents of the display screen shown in FIG. 18 are an example, and various information about the patient (questionnaire results, medical interview results, etc.) may also be displayed.

As described above, the support information providing system 1 according to this embodiment includes the terminal device 10 and the support information providing server 30 .
The terminal device 10 and the support information providing server 30 are configured to be able to communicate with each other via a network 40 .
The terminal device 10 includes a UI display control unit 51 and a support request unit 53, and the support information providing server 30 includes a target information acquisition unit 254, a problem identification unit 256, a support information generation unit 258, and a support information providing unit 259.
In the terminal device 10, the support request unit 53 sends a request to the support information providing server 30 to generate support information for pharmaceutical guidance based on information to be considered in providing pharmaceutical guidance to a patient.
The UI display control unit 51 displays the support information transmitted from the support information providing server 30 in response to a request from the support request unit 53 .
In the support information providing server 30 , the target information acquisition unit 254 acquires the consideration target information based on the request from the support request unit 53 .
The problem identifying unit 256 generates information representing an intermediate state expressed using pharmacological judgment factors as indicators when providing medication instruction by performing a first inference based on the information to be considered.
The support information generating unit 258 generates support information by performing a second inference based on the information representing the intermediate state.
The support information providing unit 259 provides the support information generated by the support information generating unit 258 to the terminal device 10 .
As a result, by performing a first inference from the information to be considered, an intermediate state can be generated that embodies as information one state of the thought process of a pharmacist providing medication instructions to a patient. Furthermore, by performing a second inference (here, rule-based inference) from the intermediate state, support information for pharmaceutical instruction can be generated.
Therefore, it becomes possible to support medication instruction using computer-based inference, thereby more appropriately supporting the work of pharmacists.

The support information providing unit 259 of the support information providing server 30 transmits the support information and information representing the intermediate state corresponding to the support information to the terminal device 10 .
The UI display control unit 51 of the terminal device 10 displays the support information and information representing an intermediate state corresponding to the support information.
This allows the pharmacist to check the support information along with its basis.

The support information providing server 30 includes a feature extraction unit 255 .
The feature extraction unit 255 extracts a preset feature amount from the consideration object information acquired by the object information acquisition unit 254 .
The support information generating unit 258 generates information representing an intermediate state by performing a first inference based on the feature amount extracted from the consideration object information.
This makes it possible to generate an intermediate state that more accurately reflects the content expressed by the consideration target information.

The support information providing server 30 includes a reconstruction executing unit 260 .
The reconstruction execution unit 260 reconstructs the interview content for obtaining the patient's information on the subjects of consideration based on the information representing the intermediate state generated by the problem identification unit 256 and the information on the subjects of consideration used to generate the intermediate state.
This allows the contents of the hearing for acquiring the information to be considered to be changed to more appropriate contents, and the information representing the intermediate state and the support information to be corrected to more appropriate contents.

The information representing the intermediate state corresponding to the support information includes a classification representing a category of the intermediate state and an association between the classification and the patient.
This makes it possible to display the intermediate state in a more easily comprehensible manner.

The problem identifying unit 256 generates information representing one or more stages of intermediate states with different levels of abstraction by performing a third inference including one or more stages of inference based on the information representing the intermediate state.
The support information generating unit 258 generates support information by performing a second inference based on the information representing the intermediate state generated by the third inference.
This makes it possible to generate intermediate states at multiple stages with different levels of abstraction, making it easier to understand what the intermediate states represent.

The first inference involves machine learning-based inference that uses the information to be considered as input and is constructed using as training data pharmaceutical decision-making factors that come to mind regarding the patient when a pharmacist recognizes the information to be considered.
This allows intermediate states to be generated that reflect the pharmacist's thinking.

The second inference includes rule-based inference based on association of preset support information with information representing an intermediate state.
This allows support information to be generated from an intermediate state by simple and clear processing.

The terminal device 10 or the support information providing server 30 according to this embodiment also includes a problem identifying unit 256 , a support information generating unit 258 , and a support information providing unit 259 .
The problem identification unit 256 performs a first inference based on the target information to be considered in providing pharmaceutical guidance to the patient, and generates information representing an intermediate state represented using pharmaceutical judgment factors as indicators when providing medication guidance.
The support information generating unit 258 generates support information for pharmaceutical guidance by performing a second inference based on the information representing the intermediate state.
The support information providing unit 259 outputs the support information generated by the support information generating unit 258 .
As a result, by performing a first inference from the information to be considered, an intermediate state can be generated that embodies as information one state of the thought process of a pharmacist providing medication instructions to a patient. Furthermore, by performing a second inference (here, rule-based inference) from the intermediate state, support information for pharmaceutical instruction can be generated.
Therefore, it becomes possible to support medication instruction using computer-based inference, thereby more appropriately supporting the work of pharmacists.

The present invention is not limited to the above-described embodiment, and any modifications and improvements that can achieve the object of the present invention are included in the present invention.
For example, in the above embodiment, a list of medication instructions is presented as support information, but the present invention is not limited to this. That is, the objects presented as support information in the present invention include various types of medical information.

Furthermore, in the above-described embodiment, after the patient has been interviewed, the patient waits while the pharmacist dispenses the medication. During this waiting time, simple lifestyle guidance information identified from the interview results may be presented to the patient (for example, displayed on the patient's smartphone, etc.).
Furthermore, in the above-described embodiment, a display screen for conducting a medical interview with the patient and a display screen for listing medication instructions (a list of recommended medication instructions for patients and a list of general medication instructions) after the contents have been confirmed by the pharmacist may be displayed on a device carried by the patient (for example, the patient's smartphone, etc.). Furthermore, problems related to the patient after the contents have been confirmed by the pharmacist may also be displayed on a device carried by the patient (for example, the patient's smartphone, etc.).

In addition, in the above embodiment, the patient-related problems are shown as a circular graph as shown in Figure 8, but the output format of the patient-related problems is not limited to this. For example, it is possible to output numerical values representing the relevance of the patient-related problems as a radar chart. In this case, it becomes easy to display changes in the patient-related problems from previous medication instructions.

In addition, in the above-described embodiment, recommended medication instructions are selected based on the patient's problem and its relevance. However, in this case, instructions that represent medication instructions given in the past may be lowered in rank in the list of recommended medication instructions by, for example, reducing their relevance. Furthermore, instructions that have been lowered in rank in the list of recommended medication instructions may have their rank restored after a predetermined period of time (e.g., three months) has elapsed.

The above-described series of processes can be executed by hardware or software.
In other words, the functional configuration in the above-described embodiment is merely an example and is not particularly limited. That is, it is sufficient that any of the computers constituting the support information providing system 1 has a function capable of executing the above-described series of processes as a whole, and the type of functional block used to realize this function is not particularly limited to the example shown.
Furthermore, one functional block may be configured as a single piece of hardware, a single piece of software, or a combination thereof.

In addition, the recording medium containing the program for executing the series of processes described above may consist not only of removable media distributed separately from the device itself in order to provide the program to the user, but also of a recording medium provided to the user in a state where it is pre-installed in the device itself.

Although the embodiments of the present invention have been described above, the present invention is not limited to the above-described embodiments. Furthermore, the effects described in these embodiments are merely a list of the most favorable effects resulting from the present invention, and the effects of the present invention are not limited to those described in these embodiments.

1 Support information providing system, 10 Terminal device, 20 Pharmacy computer, 30 Support information providing server, 40 Network, 51 User interface display control unit (UI display control unit), 52, 254 Target information acquisition unit, 53 Support request unit, 54 Support information acquisition unit, 151 Receipt management unit, 152 Medication history management unit, 153, 251 DB management unit, 171, 271 Patient attribute database (patient attribute DB), 172, 272 Prescription database (prescription DB), 173, 273 Medication history database (medication history DB), 174, 274 Interview result database (interview result DB), 175, 275 Hearing content database (hearing content DB), 176, 276 Drug database (drug DB), 252 User interface information generation unit (UI information generation unit), 253 Support request reception unit, 255 Feature extraction unit, 256 Problem identification unit, 257: Presentation information evaluation unit, 258: Support information generation unit, 259: Support information provision unit, 260: Reconstruction execution unit, 800: Information processing device, 811: CPU, 812: ROM, 813: RAM, 814: Bus, 815: Input unit, 816: Output unit, 817: Storage unit, 818: Communication unit, 819: Drive, 820: Image capture unit, 831: Removable media

Claims (12)

A support information providing system including a terminal device and a server configured to be able to communicate via a network,
The terminal device
a support requesting means for transmitting to the server a request to generate support information for pharmaceutical guidance based on target information to be considered in providing pharmaceutical guidance to the patient, the support information including interview content representing questions selected according to the attributes of the patient, questions for confirming the current state of the patient pharmacologically, the patient's answers to the interview content, and an impression input by the pharmacist of the impression he or she received from the patient when they met; and
a support information display means for displaying the support information transmitted from the server in response to a request from the support request means,
The server
a target information acquisition means for acquiring the target information based on a request from the support request means;
an intermediate state generating means for generating information representing an intermediate state expressed using a plurality of pharmaceutical judgment factors as indexes when providing medication guidance by performing a first inference based on the target information;
a support information providing means for providing information representing the intermediate state generated by the intermediate state generating means to the terminal device as the support information;
a reconstruction means for reconstructing the interview content of the patient based on information representing the intermediate state generated by the intermediate state generation means and the target information used to generate the intermediate state;
A support information providing system comprising: A support information providing system including a terminal device and a server configured to be able to communicate via a network,
The terminal device
a support requesting means for transmitting to the server a request to generate support information for pharmaceutical guidance based on target information to be considered in providing pharmaceutical guidance to the patient, the support information including interview content representing questions selected according to the attributes of the patient, questions for confirming the current state of the patient pharmacologically, the patient's answers to the interview content, and an impression input by the pharmacist of the impression he or she received from the patient when they met; and
a support information display means for displaying the support information transmitted from the server in response to a request from the support request means,
The server
a target information acquisition means for acquiring the target information based on a request from the support request means;
an intermediate state generating means for generating information representing an intermediate state expressed using a plurality of pharmaceutical judgment factors as indexes when providing medication instruction by performing a first inference based on the target information;
a support information providing means for providing information representing the intermediate state generated by the intermediate state generating means to the terminal device as the support information;
and a support information generating means for generating information representing medication instruction content for the patient by performing a second inference based on the pharmaceutical judgment factors,
the support information providing means provides information representing medication instruction content for the patient generated by the support information generating means to the terminal device as the support information;
the intermediate state generating means generates information representing the intermediate state at one or more stages of different abstraction levels by performing a third inference including one or more stages of inference based on the information representing the intermediate state;
the support information generating means generates the support information by performing the second inference based on information representing the intermediate state generated by the third inference;
The support information providing system is characterized in that the support information display means of the terminal device displays information representing the content of medication instructions for the patient in accordance with operations performed on a screen on which information representing the intermediate state is displayed . 3. The support information providing system according to claim 1, wherein the information representing the intermediate state includes a classification representing a plurality of the pharmaceutical decision factors and information representing the association between the classification and the patient. The server
a feature extraction means for extracting a predetermined feature from the target information acquired by the target information acquisition means,
The support information providing system according to any one of claims 1 to 3, characterized in that the intermediate state generating means generates information representing the intermediate state by performing the first inference based on the feature extracted from the target information. The support information providing system according to any one of claims 1 to 4, characterized in that the first inference includes a machine learning-based inference constructed using the target information as input and pharmaceutical judgment factors that come to mind regarding the patient when a pharmacist recognizes the target information as training data. 3. The support information providing system according to claim 2 , wherein the second inference includes rule-based inference based on a correspondence between the support information and the information representing the intermediate state that is set in advance. an intermediate state generating means for generating information representing an intermediate state represented by indexes of a plurality of pharmaceutical judgment factors when providing medication guidance to the patient by performing a first inference based on target information to be considered in providing pharmaceutical guidance to the patient, the intermediate state generating means including interview content representing questions selected according to the attributes of the patient, which questions are for confirming the current state of the patient from a pharmacological perspective, the patient's answers to the interview content, and an impression input by the pharmacist of the impression the pharmacist received from the patient when they met;
a support information output means for outputting information representing the intermediate state generated by the intermediate state generation means as support information for pharmaceutical guidance;
a reconstruction means for reconstructing the interview content of the patient based on information representing the intermediate state generated by the intermediate state generation means and the target information used to generate the intermediate state;
A support information providing device comprising: an intermediate state generating means for generating information representing an intermediate state represented by indexes of a plurality of pharmaceutical judgment factors when providing medication guidance to the patient by performing a first inference based on target information to be considered in providing pharmaceutical guidance to the patient, the intermediate state generating means including interview content representing questions selected according to the attributes of the patient, which questions are for confirming the current state of the patient from a pharmacological perspective, the patient's answers to the interview content, and an impression input by the pharmacist of the impression the pharmacist received from the patient when they met;
a support information output means for outputting information representing the intermediate state generated by the intermediate state generation means as support information for pharmaceutical guidance;
and a support information generating means for generating information representing medication instruction content for the patient by performing a second inference based on the pharmaceutical judgment factors,
the support information output means outputs, as the support information, information representing medication instruction content for the patient generated by the support information generation means;
the intermediate state generating means generates information representing the intermediate state at one or more stages of different abstraction levels by performing a third inference including one or more stages of inference based on the information representing the intermediate state;
the support information generating means generates the support information by performing the second inference based on information representing the intermediate state generated by the third inference;
The support information providing device is characterized in that the support information output means displays information representing the content of medication instructions for the patient in accordance with an operation performed on a screen on which information representing the intermediate state is displayed . A support information providing method executed by an information processing device, comprising:
an intermediate state generation step for generating information representing an intermediate state represented by indexes of a plurality of pharmaceutical judgment factors when providing medication guidance to the patient by performing a first inference based on target information to be considered in providing pharmaceutical guidance to the patient, the information including interview content representing questions selected according to the attributes of the patient and representing questions to confirm the current state of the patient pharmacologically, the patient's answers to the interview content, and an impression input by the pharmacist of the impression the pharmacist received from the patient when they met;
a support information output step of outputting information representing the intermediate state generated in the intermediate state generation step as support information for pharmaceutical guidance;
a reconstruction step of reconstructing the interview content of the patient based on information representing the intermediate state generated in the intermediate state generation step and the target information used to generate the intermediate state;
A support information providing method comprising: A support information providing method executed by an information processing device, comprising:
an intermediate state generation step for generating information representing an intermediate state represented by indexes of a plurality of pharmaceutical judgment factors when providing medication guidance to the patient by performing a first inference based on target information to be considered in providing pharmaceutical guidance to the patient, the information including interview content representing questions selected according to the attributes of the patient and representing questions to confirm the current state of the patient pharmacologically, the patient's answers to the interview content, and an impression input by the pharmacist of the impression the pharmacist received from the patient when they met;
a support information output step of outputting information representing the intermediate state generated in the intermediate state generation step as support information for pharmaceutical guidance;
a support information generating step of generating information representing medication instruction content for the patient by performing a second inference based on the pharmaceutical judgment factors,
In the support information output step, information representing medication instruction content for the patient generated in the support information generation step is output as the support information;
In the intermediate state generating step, a third inference including one or more stages of inference is performed based on the information representing the intermediate state to generate information representing one or more stages of the intermediate state having different levels of abstraction;
In the support information generating step, the support information is generated by performing the second inference based on information representing the intermediate state generated by the third inference;
The support information providing method is characterized in that , in the support information output step, information representing the content of medication instructions for the patient is displayed in accordance with an operation performed on a screen on which information representing the intermediate state is displayed . On the computer,
an intermediate state generation function that generates information representing an intermediate state expressed as indexes of a plurality of pharmaceutical judgment factors when providing medication guidance by performing a first inference based on target information to be considered in providing pharmaceutical guidance to the patient, the information including interview content representing questions selected according to the attributes of the patient, which questions are for confirming the current state of the patient pharmacologically, the patient's answers to the interview content, and an impression input by the pharmacist of the impression the pharmacist received from the patient when they met;
a support information output function that outputs information representing the intermediate state generated by the intermediate state generation function as support information for pharmaceutical guidance;
a reconstruction function that reconstructs the interview content of the patient based on information representing the intermediate state generated by the intermediate state generation function and the target information used to generate the intermediate state;
A program characterized by realizing the above. On the computer,
an intermediate state generation function that generates information representing an intermediate state expressed as indexes of a plurality of pharmaceutical judgment factors when providing medication guidance by performing a first inference based on target information to be considered in providing pharmaceutical guidance to the patient, the information including interview content representing questions selected according to the attributes of the patient, which questions are for confirming the current state of the patient pharmacologically, the patient's answers to the interview content, and an impression input by the pharmacist of the impression the pharmacist received from the patient when they met;
a support information output function that outputs information representing the intermediate state generated by the intermediate state generation function as support information for pharmaceutical guidance;
and a support information generating function for generating information representing medication instruction content for the patient by performing a second inference based on the pharmaceutical judgment factors,
the support information output function outputs, as the support information, information representing medication instruction content for the patient generated by the support information generation function;
the intermediate state generation function generates information representing the intermediate state at one or more stages with different levels of abstraction by performing a third inference including one or more stages of inference based on the information representing the intermediate state;
the support information generation function generates the support information by performing the second inference based on information representing the intermediate state generated by the third inference;
The support information output function is a program characterized by displaying information representing medication instructions for the patient in response to operations performed on a screen on which information representing the intermediate state is displayed .