Support device, support system, support method, and program

Abstract

To more appropriately support pharmacists in their business.SOLUTION: A support server 30 includes a target information acquisition section 254, a guidance content inference section 256, and a candidate information generation section 257. The target information acquisition section 254 acquires target information to be considered in pharmaceutical guidance to a patient. The guidance content inference section 256 infers guidance content of the pharmaceutical guidance to the patient on the basis of the target information acquired by the target information acquisition section 254. The candidate information generation section 257 generates candidate information that is a candidate to be included in a pharmaceutical history of the pharmaceutical guidance to the patient on the basis of the guidance content inferred by the guidance content inference section 256.SELECTED DRAWING: Figure 2

Description

[Technical field]

[0001] The present invention relates to an assistance device, an assistance system, an assistance method, and a program. [Background technology]

[0002] Conventionally, information processing techniques are known that support the work of pharmacists in pharmacies. For example, Patent Document 1 describes that data on a patient's medical history is managed in a database, and when dispensing medicine to a patient, the database is referred to to provide medication instructions based on the medical history, etc. [Prior art documents] [Patent documents]

[0003] [Patent Document 1] JP 2016-122253 A Summary of the Invention [Problem to be solved by the invention]

[0004] However, in order to operate the database appropriately, it is necessary for the pharmacist to sequentially input data on the medication history based on the content of the medication instruction that was actually given to the patient into the database. The inputting of data on the medication history is cumbersome and requires a great deal of effort from the pharmacist. Therefore, in order to reduce such effort, it is desirable to more appropriately support the work of pharmacists.

[0005] An object of the present invention is to more appropriately support the work of pharmacists. [Means for solving the problem]

[0006] In order to solve the above problems, an assistance device according to one aspect of the present invention comprises: A target information acquisition means for acquiring target information to be taken into consideration in pharmaceutical guidance for a patient; an instruction content inference means for inferring instruction content of pharmaceutical instruction for the patient based on the object information acquired by the object information acquisition means; a candidate information generating means for generating candidate information to be included in a medical history of pharmaceutical guidance for the patient based on the guidance content inferred by the guidance content inferring means; Equipped with. Effect of the Invention

[0007] According to the present invention, it is possible to more appropriately support the work of pharmacists. [Brief description of the drawings]

[0008] [Figure 1] 1 is a schematic diagram showing an overview of a process in which a support system according to the present embodiment supports data registration in a medication history (medication instruction history) in pharmaceutical instruction (medication instruction) for a patient. FIG. [Diagram 2] 1 is a diagram showing a system configuration of a support system 1 according to an embodiment of the present invention. [Diagram 3] FIG. 8 is a diagram showing a hardware configuration of an information processing device 800 constituting each device. [Figure 4] 2 is a block diagram showing a functional configuration of a terminal device 10. FIG. [Diagram 5] FIG. 13 is a schematic diagram showing an example of a medication instruction selection screen. [Figure 6] FIG. 13 is a schematic diagram showing an example of a questionnaire display screen. [Figure 7] FIG. 13 is a schematic diagram showing an example of a medical interview display screen. [Figure 8] FIG. 13 is a schematic diagram showing an example of a medication instruction selection screen. [Figure 9] FIG. 13 is a schematic diagram showing an example of an approval receiving screen. [Figure 10] FIG. 13 is a schematic diagram showing another example of the approval receiving screen. [Figure 11] FIG. 2 is a block diagram showing the functional configuration of a pharmacy computer 20. [Figure 12] FIG. 2 is a block diagram showing a functional configuration of the support server 30. [Figure 13] 13 is a schematic diagram showing data on medication instruction statements among data on candidate information stored in candidate information DB 277. FIG. [Figure 14] 13 is a flowchart showing the flow of target information acquisition processing executed by the terminal device 10. [Figure 15] 13 is a flowchart showing the flow of information management processing executed by the pharmacy computer 20. [Figure 16] 13 is a flowchart showing the flow of a medication history registration support process executed by the support server 30. [Figure 17] FIG. 8 is a block diagram showing the functional configuration of a stand-alone information processing device 800 having a medical history registration support function. [Figure 18] 13 is a flowchart showing the flow of a modified example of the medication history registration support process executed by the support server 30. [Figure 19] 1 is a schematic diagram showing an example of a medication instruction selection screen 60 displayed on the terminal device 10 or the support server 30. FIG. [Figure 20] 1 is a schematic diagram showing an example of a training home screen 70 displayed on the terminal device 10 or the support server 30. FIG. DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0009] Hereinafter, an embodiment of the present invention will be described with reference to the drawings.

[0010] [Processing overview] FIG. 1 is a schematic diagram showing an overview of a process in which a support system according to an embodiment of the present invention supports data registration in a medical history (medication instruction history) in pharmaceutical instruction (medication instruction) for a patient. As shown in FIG. 1, the support system uses AI (Artificial Intelligence) to infer the contents of medication instructions based on information to be considered in medication instructions (hereinafter referred to as "target information"), such as data on prescriptions issued to patients who visit the pharmacy and data on the results of questionnaires answered by patients. The support system also generates candidate information to be included in the medication history (e.g., medication instruction text corresponding to the inferred medication instruction content) based on the inferred medication instruction content. Furthermore, the support system presents (e.g., displays or outputs sound) the generated candidate information to a pharmacist who is the manager of medication instructions. The support system then receives approval for registering the candidate information from the pharmacist, and registers the approved candidate information in the medication history.

[0011] In this way, the support system generates candidate information by performing inference based on target information such as prescription data, and presents this candidate information to the pharmacist. Therefore, the pharmacist only needs to confirm the contents of the candidate information and determine whether or not to approve the registration of all or at least a part of the data related to the medication history (e.g., medication instructions) in the medication history. In other words, the support system can reduce the work of the pharmacist in inputting data related to the medication history. Therefore, according to the support system according to the embodiment of the present invention, it is possible to more appropriately support the work of pharmacists.

[0012] As shown by the dashed line in Fig. 1, the support system can also use data other than the prescription data and the questionnaire result data as target information. For example, the support system can infer the content of medication instruction using the data of the prescription issued to the patient and the questionnaire result data, as well as the data of the interview results (interview results and the pharmacist's impressions from the patient, etc.) as target information. Furthermore, when providing pharmaceutical instruction to a patient at a second or subsequent visit, the support system can infer the content of this medication instruction using the data of the previous medication instruction and the data of the current interview results as target information in addition to the data of the prescription issued to the patient and the questionnaire result data.

[0013] The support system may infer the contents of the medication instruction while the medication instruction is being given, but it can also infer the contents of the medication instruction even after the medication instruction has been completed and a medical fee statement (receipt) has been issued. In this case, as shown by the dashed line in Fig. 1, the support system can infer the contents of the medication instruction by further referring to the data of the medical fee statement (receipt) issued in response to the medication instruction, in addition to the above-mentioned target information. Furthermore, in any of the above cases, the support system can also infer the content of medication instructions on a rule-based basis instead of (or in addition to) inferring the content of medication instructions using AI. The above is an overview of the processing performed by the support system. Next, more specific details of the support system for realizing such processing will be described below.

[0014] [System Configuration] FIG. 2 is a diagram showing a system configuration of the support system 1 according to an embodiment of the present invention. The support system 1 in this embodiment is used to support the work of a pharmacist in a dispensing pharmacy. For example, as described above with reference to Fig. 1, the support system 1 is used to reduce the work of a pharmacist inputting data into a medical history by inferring the contents of medication instructions given to a patient who brings in a prescription.

[0015] As shown in FIG. 2, the support system 1 includes a terminal device 10, a pharmacy computer 20, and a support server 30. The terminal device 10, the pharmacy computer 20, the support server 30, and an external server such as a drug information database server that stores drug information including drug administration instructions are configured to be able to communicate with each other via a network 40 (such as the Internet). The terminal device 10 and the pharmacy computer 20 may be configured to be able to communicate with each other via a private network such as a Virtual Private Network (VPN). Although each device is illustrated one by one in the figure, this is not limited to this. For example, a plurality of pharmacy computers 20 may exist corresponding to each of a plurality of pharmacies. Alternatively, a plurality of terminal devices 10 may exist corresponding to each of a plurality of pharmacists working at each of a plurality of pharmacies.

[0016] The terminal device 10 is operated by a pharmacist and is configured with an information processing device such as a tablet terminal or a PC (Personal Computer). When the pharmacist interviews a patient, the terminal device 10 displays various information to support the pharmacist's work and accepts input of various information by the pharmacist. For example, the terminal device 10 displays the contents of a questionnaire that the pharmacist conducts with the patient and accepts input of the patient's answer to the questionnaire (questionnaire result) from the pharmacist. The terminal device 10 also displays the contents of the interview (interview contents) when the pharmacist interviews the patient and accepts input of the interview result (interview result) from the pharmacist. Furthermore, the terminal device 10 accepts input of the impression (impression) that the pharmacist receives from the patient who met the pharmacist from the pharmacist. Furthermore, the terminal device 10 displays candidate information generated in a medical history registration support process described later. Furthermore, the terminal device 10 accepts an input of an approval result for the registration of the displayed candidate information in the medical history (including a request for registration of the approved candidate information in the medical history) from the pharmacist.

[0017] The pharmacy computer 20 is composed of an information processing device such as a server computer that executes processing related to the business of the dispensing pharmacy. The pharmacy computer 20 also has a function of a receipt computer (receipt computer function) and a function of managing a patient's medical history (medical history management function). In relation to these functions, the pharmacy computer 20 also manages various data. For example, the pharmacy computer 20 manages various data such as patient attributes related to multiple patients, prescriptions of multiple patients, medical history which is a history of the drug-taking instruction contents and prescribed drugs that pharmacists have given to patients, interview results (interview results and impressions, etc.), contents of interviews with patients, and information on drugs handled at the pharmacy. It is assumed that the medical history managed by the pharmacy computer 20 includes information used as a drug-taking history management record for insurance dispensing. However, without being limited to this, the medical history may further include other information used at the pharmacy, etc. The pharmacy computer 20 then executes the information management process described below to transmit various pieces of information it manages to the support server 30 and update the various pieces of information it manages using various data transmitted from the support server 30.

[0018] The support server 30 is composed of an information processing device such as a server computer having a function to support the work of pharmacists (work support function). The support server 30 receives various data managed by pharmacy computers 20 installed in multiple pharmacies in order to support the work of pharmacists. The support server 30 also manages the received various data using a database group (including a medication history database) similar to that of the pharmacy computer 20. In other words, the support 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 medication history registration support process.

[0019] The support server 30 also executes a medication history registration support process. In this medication history registration support process, the support server 30 accepts support requests for medication history registration (such as requests to provide candidate information and requests to register candidate information approved by a pharmacist in a medication history) from the terminal devices 10 installed in multiple pharmacies. In response to the support request, the support server 30 infers the medication instruction content by referring to target information such as prescription data, questionnaire result data answered by the patient, and interview results (interview results and impressions of the pharmacist from the patient, etc.), and medical fee statement (receipt) data, and generates candidate information based on the inferred medication instruction content. Furthermore, the support server 30 transmits the generated candidate information to the terminal device 10. When the support server 30 receives approval of the candidate information from the pharmacist who referred to the candidate information from the terminal device 10, it registers the candidate information in the medication history database managed by itself. By such a medical history registration support process, the medical history database managed by the support server 30 is updated to the latest contents, and in synchronization therewith, the medical history database managed by the pharmacy computer 20 is also updated to the latest contents. That is, the support server 30 and the pharmacy computers 20 (if there are multiple computers, each of them) can share various data including the medical history.

[0020] The sharing of various data can be realized by any method, but in the following, as an example, it is assumed that the support server 30 and the pharmacy computer 20 are performed in compliance with a common specification. The common specification is not particularly limited, but may be, for example, a specification such as NSIPS (New Standard Interface of Pharmacy-system Specifications) (registered trademark). In this way, by complying with the common specification (for example, NSIPS), it is possible to easily realize the sharing of data between the support server 30 and the existing pharmacy computer 20. In addition, it is possible to realize the sharing of data without relying on a specific specification (for example, a specific specification formulated by a certain manufacturer). In addition, in a case where a medical history database is also present in the external server, the medical history database managed by the external server may be updated to the latest content in synchronization with the medical history database managed by the support server 30 and the medical history database managed by the pharmacy computer 20. In other words, various data may be shared with the external server as well. In this case, it is assumed that the sharing of various data is performed in compliance with a common specification, similar to the pharmacy computer 20.

[0021] [Hardware configuration] Next, the hardware configuration of each device in the support system 1 will be described. As described above, each device included in the support system 1 is configured by an information processing device such as a PC, a server computer, or a tablet terminal, and has the same basic configuration.

[0022] FIG. 3 is a diagram showing a hardware configuration of an information processing device 800 constituting 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 memory unit 817, a communication unit 818, a drive 819, and an imaging unit 820.

[0023] The CPU 811 executes various processes according to a program recorded in a ROM 812 or a program loaded from a storage unit 817 to a RAM 813 . The RAM 813 also stores data and the like necessary for the CPU 811 to execute various processes.

[0024] The CPU 811, the ROM 812, and the RAM 813 are connected to one another via a bus 814. To the 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 are connected.

[0025] The input unit 815 is made up of various buttons and the like, and is used to input various information 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 composed of a hard disk or a dynamic random access memory (DRAM) or the like, and stores various data managed by each server. The communication unit 818 controls communications with other devices via the network 40 .

[0026] Removable media 831, such as a magnetic disk, an optical disk, a magneto-optical disk, or a 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 section 820 is configured with an imaging device including 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 server 30, it is also 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 with a touch sensor and place it on top of the display of the output unit 816, thereby providing a touch panel.

[0027] [Functional configuration] Next, the functional configuration of each device in the support system 1 will be described.

[0028] [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, in the CPU 811 of the terminal device 10, a user interface display control unit (UI display control unit) 51, a target information acquisition unit 52, a support request unit 53, a candidate information acquisition unit 54, and an approval receiving unit 55 function.

[0029] The UI display control unit 51 controls the display of various input / output screens (hereinafter referred to as "UI screens") in various processes described later, based on information for displaying a user interface screen (hereinafter referred to as "UI information") received from the support server 30. For example, the UI display control unit 51 presents (for example, outputs and displays on a display) a screen for selecting a patient from whom target information is to be acquired in a target information acquisition process described later (hereinafter referred to as a "patient selection screen"), a screen for displaying the contents of a questionnaire that a pharmacist conducts with a patient in the target information acquisition process (hereinafter referred to as a "questionnaire display screen"), a screen for displaying the contents of a hearing (listening items) when a pharmacist interviews a patient in the target information acquisition process (hereinafter referred to as a "medication interview display screen"), a screen for selecting a medication instruction for which data such as a medication instruction statement is to be registered in a medication history registration support process (hereinafter referred to as a "medication instruction selection screen"), and a screen for displaying candidate information for accepting approval by a pharmacist in a medication history registration support process (hereinafter referred to as an "approval acceptance screen"), and the like. Furthermore, the UI display control unit 51 transmits various pieces of information input on the UI screen to the support server 30. For example, the UI display control unit 51 transmits information identifying a patient selected on the patient selection screen, questionnaire results input on the questionnaire display screen, medical interview results input on the medical interview display screen, information identifying medication instruction selected on the medication instruction selection screen, and approval results input on the approval reception screen to the support server 30. The UI display control unit 51 may transmit the various pieces of information input on the UI screen (for example, approved candidate information, etc.) to the support server 30 and also to the pharmacy computer 20.

[0030] 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).

[0031] 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 intended to identify the patient's attributes, such as the patient's name, sex, medical history, and illnesses being treated.

[0032] Furthermore, FIG. 7 is a schematic diagram showing an example of a medical interview display screen. As shown in FIG. 7, the interview display screen displays interview contents (interview items) including multiple-choice questions, and the pharmacist inputs the interview results (interview results) according to the patient's answers. The interview contents displayed at this time are a series of questions selected in response to the patient's attributes, and are determined for each patient, each prescription content, or the number of interviews (for example, whether it is the first interview or the second interview), etc. In addition, the interview display screen has a free entry field for the pharmacist, and it is possible for the pharmacist to arbitrarily enter the contents that he or she noticed when interviewing the patient (for example, physical impressions such as "lack of energy" or "pale complexion," or impressions expressing personality impressions such as "nervous personality" or "judgment-prone personality"). In addition, the pharmacist can also register data such as a medication instruction statement corresponding to the medication instruction statement in the medication history without using the medication history registration support process. In this case, the data such as the medication instruction statement is registered in the medication history by a registration screen not shown.

[0033] Furthermore, FIG. 8 is a schematic diagram showing an example of a medication instruction selection screen. As shown in Figure 8, the medication instruction selection screen displays a list of each medication instruction included in the medication history managed by the pharmacy computer 20, and the pharmacist selects from this list the medication instruction for which he or she wishes to request the generation of candidate information to be registered in the medication history.

[0034] Furthermore, FIG. 9 is a schematic diagram showing an example of an approval receiving screen. As shown in FIG. 9, the approval reception screen displays a list of medication instruction sentences (hereinafter referred to as a "list of inferred medication instruction candidates") indicating the medication instruction contents when a pharmacist (particularly an experienced pharmacist) generally provides medication instruction, and a list of medication instruction sentences (hereinafter referred to as a "list of general medication instruction candidates") indicating the general medication instruction contents regarding prescribed drugs. Each of these medication instruction sentences included in the inferred medication instruction candidate list and the general medication instruction candidate list corresponds to candidate information generated corresponding to the medication instruction contents estimated by the medication history registration support process. For example, each of the medication instruction sentences included in the inferred medication instruction candidate list represents a result reflecting the action and side effects of the dispensed drug and drug interactions (contraindications for combined use) that a pharmacist (particularly an experienced pharmacist) should explain to a patient to whom the pharmacist provides medication instruction, observation items that the pharmacist recalls for the patient to whom the pharmacist provides medication instruction, the instruction policy that the pharmacist assumes in medication instruction, and indicators (points of view) that the pharmacist recalls in the thought process when providing medication instruction. Each of the medication instruction sentences included in the general medication instruction candidate list represents a general explanation selected corresponding to the drug prescribed according to the patient's prescription data.

[0035] In addition, a check box is displayed for each medication instruction sentence, and the medication instruction sentence with the check mark by the pharmacist is registered in the patient's medication history as a list of medication instruction sentences used for medication instruction (medication instruction results) after the pharmacist approves the registration in the medication history (for example, by pressing the "Approve registration in medication history" button shown in the figure). That is, in this embodiment, the candidate information includes at least medication instruction sentences corresponding to pharmaceutical instructions for the patient. Then, the approval of the registration in the medication history by the pharmacist involves the selection of the medication instruction sentence to be approved from the medication instruction sentences included in the candidate information. In this case, the check box corresponding to the medication instruction sentence that is assumed to be likely to be checked by the pharmacist based on the likelihood output by inference may be set to a state where a check mark is added in advance. Then, the pharmacist may remove the check mark from the medication instruction sentence that he / she does not think needs to be registered. In this manner, in this embodiment, by being based on the pharmacist's approval operation, registration to the medical history can be realized by appropriately reflecting the judgment of the pharmacist who has the authority to register to the medical history.

[0036] FIG. 10 is a schematic diagram showing another example of the approval receiving screen. As shown in FIG. 10, if the candidate information includes a content that the pharmacist should pay attention to when approving, a predetermined warning message is displayed on the approval reception screen as shown in FIG. 9. The content to be considered when approving is, for example, a medicine that requires the involvement of a specialist in pharmaceutical management for safety management (so-called high-risk medicine) is prescribed, or the patient has a special chronic disease. When such a content to be considered is included in the candidate information, a warning message corresponding to the content to be considered is displayed. The timing of displaying the predetermined warning message is not particularly limited, but, for example, when the pharmacist performs an approval operation for registration in the medical history (for example, a pressing operation on the "Approve registration in medical history" button shown in the figure), the warning message is displayed to reconfirm whether or not the approval is really acceptable. By displaying such a predetermined warning message, the pharmacist can be prompted to pay attention to the content to be considered when approving. That is, the work of the pharmacist can be more appropriately supported. In addition to displaying the warning message, for example, the "Approve registration in medical history" button, the background display color, the font of the characters, etc. may be made special to prompt attention. Alternatively, the attention may be prompted by outputting a warning sound or a voice corresponding to the warning message. In other words, if the candidate information contains content that the pharmacist should take note of when approving, it is advisable to present the candidate information to the pharmacist in various ways (e.g., by displaying or outputting a sound) that differ from when such content is not contained.

[0037] Returning to FIG. 4, the target information acquisition unit 52 acquires various target information to be considered in providing medication instruction to a patient. As described above, the target information is information to be considered in providing pharmaceutical instruction to a patient. For example, the target information acquisition unit 52 acquires data representing the contents of a prescription brought by a patient (prescription data), data of a questionnaire result including data of patient attributes for identifying a patient, such as the name, age, medical history, and disease under treatment of the patient who brought the prescription, and data of a medical interview result (interview result, impression, etc.) input by a pharmacist to a medical interview display screen, as the target information. Note that the information acquired by the target information acquisition unit 52 is not limited to these, and it is also possible to acquire data of a patient's medical history, data of the contents of medication instruction given to a patient at a previous visit to the pharmacy, data related to medical fees such as a medical fee statement, or data stored in an electronic medicine notebook.

[0038] The support request unit 53 sends a request for candidate information to the support server 30 together with information identifying the medication instructions for the subject for which the pharmacist is requesting the generation of candidate information, selected by the pharmacist from the list as described above with reference to Figure 8. The candidate information acquisition unit 54 acquires candidate information transmitted from the support server 30 in response to a request for candidate information transmitted by the support request unit 53. The candidate information acquired by the candidate information acquisition unit 54 includes data of a list of medication instruction sentences indicating the medication instruction contents (list of inferred medication instruction candidates) and data of a list of general medication instruction sentences regarding the prescribed drug (list of general medication instruction candidates), as described above with reference to Fig. 9. In addition, if there is content that the pharmacist should take note of when approving, the candidate information includes the content to take note of in order to display a warning message as described above with reference to Fig. 10.

[0039] The approval receiving unit 55 receives an approval result (including a request to register the approved candidate information in the medical history) from the pharmacist who received the candidate information, and transmits the received approval result to the support server 30.

[0040] [Functional configuration of pharmacy computer 20] FIG. 11 is a block diagram showing the functional configuration of the pharmacy computer 20. As shown in FIG. 11, a receipt management unit 151, a medical history management unit 152, and a database management unit (DB management unit) 153 function in a CPU 811 of the pharmacy computer 20. In addition, a patient attribute database (patient attribute DB) 171, a prescription database (prescription DB) 172, a medical history database (medical history DB) 173, a medical interview result database (medical interview result DB) 174, a hearing content database (hearing content DB) 175, and a medical fee database (medical fee DB) 176 are formed in a storage unit 817 of the pharmacy computer 20.

[0041] The patient attribute DB 171 stores data on patient attributes such as the address, name, age, sex, and various information that represents the characteristics of each patient. The patient attributes are composed of information acquired by the pharmacist in conversation with the patient, information provided by the patient in response to a questionnaire, etc., and include, for example, the patient's hobbies, work, family structure, favorite foods, etc. 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. In the medical history DB 173, data on the history of drugs prescribed to patients (medicinal history) is stored in association with information identifying each patient and information identifying each pharmacist who prescribed the drug. In addition, data on the history of the drug administration instructions given to patients by pharmacists (medicinal administration instruction statements, etc.) is also stored in the medical history. As described above, the registration of these drug administration instruction statements, etc. can be performed after reducing the work of the pharmacist inputting data into the medical history by the medical history registration support process.

[0042] 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 results of the medical interview include the results of the interviews that the pharmacist has conducted with the patient and input, and the impressions that the pharmacist has received from the patient he or she met. The interview content DB 175 stores data of a list of interview contents (listening items) to patients, such as "Have you forgotten to take your medicine?" or "Have you experienced any changes in your physical condition after taking your medicine?".

[0043] The medical fee DB 176 stores data of medical fee statements (receipts) issued by the receipt computer function realized by the receipt management unit 151 so that the pharmacy can bill the health insurance association or the like for medical expenses.

[0044] 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 process of issuing the medical receipt. The medical history management unit 152 manages the history (medicinal history) of medicines prescribed to a patient. For example, when a new prescription is given to a patient, the medical history management unit 152 stores data of the medicine prescribed this time in the medical history DB 173, when a request to transmit target information or data of a medical fee statement is received from the terminal device 10 in the medical history registration support process, the medical history management unit 152 acquires the requested target information or data of a medical fee statement from each database formed in the storage unit 817 and transmits it to the terminal device 10, and when a request to register candidate information is made by the support server 30, the medical history management unit 152 stores data such as a medication instruction statement included in the candidate information in the medical history DB 173.

[0045] The DB management unit 153 performs management to synchronize data in various databases managed by the pharmacy computer 20 with data in various databases provided in the support server 30. For example, the DB management unit 153 transmits updated data in various databases managed by the pharmacy computer 20 to the support server 30 at a preset time (e.g., 3:00 a.m.), and receives data in various databases updated in the support server 30 from the support server 30 to update the various databases it manages.

[0046] [Functional configuration of support server 30] FIG. 12 is a block diagram showing the functional configuration of the support server 30. As shown in FIG. 12, in the CPU 811 of the support server 30, 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 teaching content inference unit 256, a candidate information generation unit 257, a presentation control unit 258, and a medication history registration unit 259 function. In addition, in the storage unit 817 of the support server 30, a patient attribute database (patient attribute DB) 271, a prescription database (prescription DB) 272, a medication history database (medical history DB) 273, an interview result database (interview result DB) 274, an interview content database (interview content DB) 275, a medical fee database (medical fee DB) 276, and a candidate information database (candidate information DB) 277 are formed. Among these databases, the stored contents of each database other than candidate information DB 277 are synchronized with the stored contents of each corresponding database in pharmacy computer 20 by DB management unit 251.

[0047] The candidate information DB 277 stores data for a candidate information generating unit 257, which will be described later, to generate candidate information in the medical history registration support process. FIG. 13 is a schematic diagram showing data related to a medication instruction sentence, which is data for generating candidate information stored in the candidate information DB 277. As shown in FIG. 13, a plurality of medication instruction sentences provided by a medication manufacturer or a pharmacist are associated with each medication specified by a medication code and a medication name. Also, as shown in FIG. 13, a category corresponding to the medication instruction content is also attached to each medication instruction sentence so that the pharmacist can easily confirm the content when approving. Furthermore, as shown in FIG. 13, a medication instruction content ID is attached as information for identifying the medication instruction content corresponding to each medication instruction sentence. In this embodiment, the medication instruction content is inferred in the medication history registration support process, and a medication instruction content ID indicating the inferred medication instruction content is output as an inference result. The candidate information generating unit 257 can generate candidate information by extracting a medication instruction sentence corresponding to the medication instruction content ID output as the inference result from the candidate information DB 277. Also, the candidate information DB 277 stores data of the predetermined warning sentence described above with reference to FIG. 10. Then, when the candidate information generating unit 257 infers that there is something that the pharmacist should take note of when approving, it extracts a predetermined warning message corresponding to the something that the pharmacist should take note of from the candidate information DB 277 and includes it in the candidate information.

[0048] Since candidate information DB277 is a database used mainly by candidate information generating unit 257, it is assumed that it is formed only in supporting server 30 and not particularly formed in pharmacy computer 20. However, this is not limiting, and a database equivalent to candidate information DB277 may also be formed in pharmacy computer 20. The database in pharmacy computer 20 and candidate information DB277 may also be synchronized. This makes it possible, for example, when a pharmacist adds or modifies the contents of a medication instruction statement using pharmacy computer 20, to reflect the added or modified contents of the medication instruction statement in candidate information DB277 of supporting server 30.

[0049] 12, the DB management unit 251 performs management to synchronize data of various databases provided in the support server 30 with data of various databases managed by the pharmacy computer 20. For example, the DB management unit 251 transmits data of various databases updated in the support server 30 to the pharmacy computer 20 at a preset time (e.g., 3:00 a.m.), and receives data updated in the various databases managed by the pharmacy computer 20 from the pharmacy computer 20 to update the various databases it manages.

[0050] The UI information generating 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. In this case, the UI information generating unit 252 generates, as UI information, a frame format for displaying the UI screen and substantial contents to be inserted into the format. In this embodiment, the substantial contents to be inserted into the format include, for example, patient attributes of the medication instruction selection screen, questionnaire contents of the questionnaire display screen, hearing contents of the interview display screen, a list of medication instructions to be selected on the medication instruction selection screen, candidate information of the approval reception screen, and the like. In addition, the UI information generating unit 252 receives various information (information to identify the patient, questionnaire result data, prescription data, interview result data, information to identify the prescribing pharmacist, information to identify the selected medication instruction, approval result, and the like) transmitted from the terminal device 10 in response to transmitting the UI information to the terminal device 10.

[0051] The support request receiving unit 253 receives a request for providing candidate information from the terminal device 10 together with information for identifying the medication instruction for the subject for which generation of candidate information is requested. The target information acquisition unit 254 acquires, from the pharmacy computer 20, target information and a medical fee statement that correspond to the information identifying the medication instruction transmitted from the terminal device 10.

[0052] The feature extraction unit 255 refers to the target information and medical fee statement acquired by the target information acquisition unit 254, and extracts predefined features. At this time, the feature extraction unit 255 performs natural language processing to extract phrases representing features included in the target information and medical fee statement, or extracts features calculated or estimated from the target information and medical fee statement. For the features extracted at this time, contents (e.g., the patient's age, personality, etc.) that are determined to be features in the thought process of the pharmacist providing medication instruction are predefined. For example, when "patient's age" is defined as a feature, the feature extraction unit 255 extracts phrases representing the patient's age included in the target information. In addition, when "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 date of visit included in the target information. Furthermore, when "dispensing fee points" is defined as a feature, the feature extraction unit 255 extracts the content and points of each item, such as the drug administration history management instruction fee, contained in the medical care statement. In the inference described below, by using both the feature extracted from the target information in this way and the feature extracted from the medical care fee statement, more accurate inference can be achieved than when only one of them is used.

[0053] In addition, in this embodiment, for example, features can also be extracted from text data expressing a patient's complaint (text data obtained by voice recognition of the patient's speech, text data entered by a pharmacist, or text data expressing an option selected by a pharmacist, etc.). Therefore, for example, colloquial expressions including onomatopoeia such as "my stomach hurts" or "my stomach feels queasy" are permitted in text data expressing a patient's complaint. That is, in this embodiment, the expression expressed by the patient in the interview can be directly converted into data to produce text data expressing the patient's complaint. However, the expression expressed by the patient may also be interpreted by a pharmacist and converted into text data as a pharmaceutical expression expressing the patient's condition.

[0054] The instruction content inference unit 256 uses the feature values ​​extracted by the feature extraction unit 255 as input and infers the medication instruction content of the medication instruction given to the patient based on machine learning. In this embodiment, the instruction content inference unit 256 is provided with an inference engine constructed by machine learning for what medication instruction a pharmacist (especially an experienced pharmacist) will give to a patient when he recognizes the feature values. Therefore, the medication instruction content inferred by the instruction content inference unit 256 represents the medication instruction content that the pharmacist will give when the target information of the target patient is given. In addition, as described above, in this embodiment, the feature extraction unit 255 also extracts feature values ​​from the medical fee statement. Therefore, the inference engine provided in the instruction content inference unit 256 is machine-learned including information such as the content and points of each item of the medication history management instruction fee included in the medical fee statement. Therefore, the medication instruction content inferred by the instruction content inference unit 256 takes into consideration information such as the content and points of each item, such as the drug administration history management instruction fee, included in the medical fee statement (i.e., does not contradict the content and points of each item).

[0055] To realize such machine learning-based inference, a learning model constructed by a neural network may be created by performing supervised machine learning using teacher data in which the feature amount extracted by the feature extraction unit 255 is used as input data and the medication instruction content given by a pharmacist (especially an experienced pharmacist) in the medication instruction is used as a label (correct answer) for the input data. However, other methods (deep learning, etc.) may also be used as machine learning for realizing machine learning-based inference.

[0056] Also, instead of inferring the contents of medication instruction by such machine learning (or together with inferring the contents of medication instruction by machine learning), it is also possible to infer the contents of medication instruction on a rule basis. As an example, when using rule-based inference, table data is used in which the contents of medication instruction that are desirable to be given when various features are extracted are defined for each feature. When inference is made, the table data is referenced, and the contents of medication instruction defined for the extracted amount are output as an inference result. Note that the relationship between the features and the definition of the contents of medication instruction may be any of a one-to-one relationship, a one-to-many relationship, a many-to-one relationship, and a many-to-many relationship, or a mixture of these relationships may be defined.

[0057] The instruction content inference unit 256 outputs the inference result of the inference thus executed as a medication instruction content ID corresponding to the inferred medication instruction content. If there are multiple medication instruction sentences corresponding to the inferred medication instruction content, the instruction content inference unit 256 may output multiple medication instruction content IDs corresponding to each of them. In this case, if the instruction content inference unit 256 can infer the likelihood of each of the multiple medication instruction contents, it may also output the likelihood. Alternatively, the instruction content inference unit 256 may output only the medication instruction content with the highest likelihood.

[0058] The candidate information generating unit 257 extracts a medication instruction sentence corresponding to the medication instruction content ID output by the instruction content inference unit 256 as an inference result from the candidate information DB 277. The candidate information generating unit 257 generates the candidate information by including the extracted medication instruction sentence in the candidate information as data of the inferred medication instruction candidate list and data of the general medication instruction candidate list. The candidate information DB 277 also stores data of the predetermined warning sentence described above with reference to FIG. 10. When the candidate information generating unit 257 infers that there is a content that the pharmacist should pay attention to when approving, it extracts a predetermined warning sentence corresponding to the content to be paid attention from the candidate information DB 277 and includes it in the candidate information. In this case, the candidate information generating unit 257 may acquire data such as a patient questionnaire result, a patient interview result such as a patient interview result or an impression from each database and include it in the candidate information so that the data can be used as a basis for the pharmacist to decide whether to approve or not. In addition, the candidate information generating unit 257 may generate candidate information so that, for example, when the likelihood of each of a plurality of medication instruction contents is also inferred, a medication instruction sentence corresponding to a medication instruction content with a high likelihood is presented so that it is more likely to be selected by a pharmacist (for example, so that those with a high likelihood are displayed at the top of the inferred medication instruction candidate list, or so that those with a high likelihood are displayed with a check mark attached in advance). This allows a pharmacist to easily recognize and select a medication instruction sentence inferred to have a high likelihood compared to other medication instruction sentences.

[0059] The presentation control unit 258 transmits a request for acceptance of approval from the pharmacist together with the candidate information generated by the candidate information generating unit 257 to the terminal device 10. That is, the presentation control unit 258 performs control for presenting the candidate information to the pharmacist. The presentation control unit 258 may perform control to present the candidate information to the pharmacist other than when approval is received from the pharmacist. For example, in order to support the pharmacist in taking medication instruction, the candidate information may be controlled to be presented to the pharmacist during, before, or after taking medication instruction. This allows the pharmacist to take the medication instruction statement included in the candidate information as a recommended medication instruction content and use it as a reference when actually giving medication instruction. For example, by reading out the medication instruction statement included in the candidate information, it is possible to realize medication instruction based on the recommended medication instruction content. In this embodiment, by using the candidate information in this way, it is possible to more appropriately support the work of the pharmacist.

[0060] The medical history registration unit 259 receives, from the terminal device 10, an approval result (including a request to register the approved candidate information in the medical history) from the pharmacist who has received the candidate information. Furthermore, the medical history registration unit 259 registers the candidate information approved by the pharmacist as a registration target in the medical history included in the medical history DB 273 based on the received approval result. Furthermore, the medical history registration unit 259 transmits, to the pharmacy computer 20, a request to register the candidate information approved by the pharmacist as a registration target in the medical history included in the medical history DB 173.

[0061] [Operation] Next, the operation of the support system 1 will be described.

[0062] [Target information acquisition process] FIG. 14 is a flowchart showing the flow of the target information acquisition process executed by the terminal device 10. The target information acquisition process is started in response to an instruction to execute the target information acquisition 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 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, whereby information for identifying the patient is specified.

[0063] In step S3, the UI display control unit 51 receives input of data on a prescription issued to the selected patient. The information for identifying the patient and the data on the prescription are transmitted to the support server 30. In step S4, the UI display control unit 51 receives UI information from the support 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 server 30, displays a questionnaire display screen, and accepts input to the questionnaire display screen. After transmitting the questionnaire results entered on the questionnaire display screen to the support server 30, the UI display control unit 51 again receives UI information for the medical interview display screen and displays the medical interview display screen corresponding to the patient.

[0064] In step S5, the UI display control unit 51 receives an input of a response to the medical interview display screen. The data of the response to the medical interview display screen (medical interview result) is transmitted to the pharmacy computer 20.

[0065] In step S6, the UI display control unit 51 determines whether or not a medication instruction statement has been input from the pharmacist together with the answer to the medical interview display screen. As described above, the medication instruction statement may be input by the pharmacist one by one during medication instruction without using the medical history registration support process. If medication instructions have been input, the result of the determination in step S6 is YES, and the target information acquisition process ends. On the other hand, if no medication instruction has been input, the result of the determination in step S6 is YES, and the process proceeds to step S7. In step S7, UI display control unit 51 accepts input of medication instructions from the pharmacist. Data of the medication instructions from the pharmacist is transmitted to pharmacy computer 20. After step S7, the target information acquisition process ends.

[0066] [Information management processing] FIG. 15 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.

[0067] In step S11, the DB management unit 153 determines whether or not a prescription for a patient has been accepted. If the patient's prescription has not been received, the result of step S11 is NO, and the process proceeds to step S13. On the other hand, if the patient's prescription has been accepted, the result of the determination in step S11 is YES, and the process proceeds to step S12. In step S12, the DB management unit 153 updates the patient attribute DB 171 and the prescription DB 172 with the data of the currently accepted prescription.

[0068] In step S13, the DB management unit 153 determines whether or not data of the target information has been received from the terminal device 10. If the target information data has not been received, the result of step S13 is NO, and the process proceeds to step S15. On the other hand, if the target information has been received, the result of the determination in step S13 is YES, and the process proceeds to step S14. In step S14, the DB management unit 153 updates the medical interview result DB 174 and the hearing content DB 175 with the currently received target information data.

[0069] In step S15, the DB management unit 153 determines whether or not a medical fee statement has been issued. If a medical fee statement has not been issued, the result of step S15 is NO, and the process proceeds to step S17. On the other hand, if a medical fee statement has been issued, the result of the determination in step S15 is YES, and the process proceeds to step S16. In step S16, the DB management unit 153 updates the medical fee DB 176 with the data of the currently issued medical fee statement.

[0070] In step S17, the DB management unit 153 determines whether or not a request to transmit the target information and medical fee statement data has been received from the support server 30. If a request to transmit the target information and medical fee statement data has not been received from the support server 30, the result of step S17 is determined to be NO, and the process proceeds to step S19. On the other hand, if a request to transmit the target information and medical fee statement data has been received from the support server 30, the result of step S17 is determined to be YES, and the process proceeds to step S18. In step S18, the DB management unit 153 acquires the requested target information and medical fee statement data from each database, and transmits them to the support server 30.

[0071] In step S19, the DB management unit 153 determines whether or not data on the medical history (data on the medication instruction statement, etc.) has been received from the support server 30 or the terminal device 10. If the medication history data has not been received from the support server 30 or the terminal device 10, the result of step S19 is determined to be NO, and the process proceeds to step S21. On the other hand, if the medication history data has been received from the support server 30 or the terminal device 10, the result of the determination in step S19 is YES, and the process proceeds to step S20. In step S20, DB management section 153 updates medication history DB 173 with the received medication history data.

[0072] In step S22, 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 in the support 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 in the support server 30 has not arrived, step S21 is judged as NO and the information management process is repeated. On the other hand, if 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 in the support server 30, the result of step S21 is judged as YES, and the processing proceeds to step S22.

[0073] In step S22, the DB management unit 153 updates each database by transmitting and receiving data to and from the support server 30, and synchronizes the data of the various databases managed by the pharmacy computer 20 with the data of the various databases provided in the support server 30. After step S22, the information management process is repeated.

[0074] [Medical history registration support processing] FIG. 16 is a flowchart showing the flow of the medication history registration support process executed by the support server 30. The medical history registration support process is started when the support server 30 receives a request for providing candidate information from the terminal device 10.

[0075] In step S31, the support request receiving unit 253 receives a request to provide candidate information from the terminal device 10 together with information for identifying the medication instruction for the subject for which generation of candidate information is requested. In step S32, the target information acquisition unit 254 transmits a request to the pharmacy computer 20 to transmit target information and data of a medical fee statement corresponding to the information for identifying the medication instruction transmitted from the terminal device 10. In step S33, the target information acquisition unit 254 receives the target information and medical fee statement data from the pharmacy computer 20.

[0076] In step S34, the feature extraction unit 255 performs natural language processing on the received target information and medical fee statement data. In step S35, the feature extraction unit 255 extracts features from the target information and the medical fee statement. In step S36, the instruction content inference section 256 infers the medication instruction content using the feature amount extracted by the feature extraction section 255 as an input.

[0077] In step S37, the candidate information generating section 257 generates candidate information by extracting, from the candidate information DB 277, a medication instruction sentence corresponding to the medication instruction content ID output by the instruction content inferring section 256 as an inference result. In step S38, the presentation control unit 258 transmits a request for acceptance of approval from the pharmacist together with the candidate information generated by the candidate information generating unit 257 to the terminal device 10 (outputs to the terminal device 10 via the network 40). In step S39, the medical history registration unit 259 receives from the terminal device 10, from the pharmacist who received the candidate information, an approval result regarding the registration of the candidate information in the medical history (including a request to register the approved candidate information in the medical history).

[0078] In step S40, the medication history registration section 259 determines whether or not the registration of the candidate information has been approved by the pharmacist, based on the received approval result. If the registration of the candidate information has not been approved by the pharmacist, a NO determination is made in step S40, and the medication history registration support process ends. On the other hand, if the registration of the candidate information is approved by the pharmacist, a determination of YES is made in step S40, and the process proceeds to step S41.

[0079] In step S41, the medical history registration unit 259 updates the medical history database. Specifically, the medical history registration unit 259 registers the candidate information approved by the pharmacist as a registration target in the medical history included in the medical history DB 273. In addition, the medical history registration unit 259 transmits a registration request to the pharmacy computer 20 to register the candidate information approved by the pharmacist as a registration target in the medical history included in the medical history DB 173. After step S41, the medical history registration support process ends.

[0080] As described above, the support system 1 according to this embodiment generates candidate information by performing inference based on target information such as prescription data, and presents this candidate information to the pharmacist. Therefore, the pharmacist only needs to confirm the contents of the candidate information with respect to input of all or at least a part of the data related to the medical history (e.g., medication instruction text), and then decide whether or not to approve the registration of the data in the medical history. In other words, the support system can reduce the work of the pharmacist in inputting data related to the medical history. Therefore, according to the support system 1 according to the embodiment of the present invention, it is possible to more appropriately support the work of pharmacists.

[0081] [Variation 1] In the above embodiment, a client-server type support system 1 is constructed, and a request for candidate information is made from the terminal device 10 to the support server 30 to obtain support information. In contrast, by providing the support functions of the support server 30 in a single device (e.g., a terminal device 10 or a pharmacy computer 20, etc.), the functions of the support system 1 can be realized in a single information processing device 800 (i.e., as a stand-alone system).

[0082] FIG. 17 is a block diagram showing the functional configuration of a stand-alone information processing device 800 having an assistance 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 server 30, the support request reception unit 253, the target information acquisition unit 254, the feature extraction unit 255, the instruction content inference unit 256, the candidate information generation unit 257, the presentation control unit 258, and the medication history registration unit 259 are provided in the CPU 811, and each database managed by the support server 30 (or the pharmacy computer 20) is provided in the memory unit 817.

[0083] Furthermore, when the support 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 server 30 among more servers (e.g., cloud servers), or to integrate the functions of the pharmacy computer 20 and the support server 30 into one server. In addition, it is possible to integrate the functions of the terminal device 10 and the pharmacy computer 20 into one client.

[0084] [Variation 2] In the above embodiment, the candidate information mainly includes the medication instruction text, and in the medication history registration support process, it is assumed that the medication instruction text is registered in the medication history. Not limited to this, the candidate information may further include other information, and the medication history registration support process may be configured to register the other information as well. For example, in the medication history registration support process, various information such as bibliographical information about the patient (name, date of birth, sex, insured person's certificate number, address, emergency contact information, etc.), information included in the prescription (name of the insured medical institution and insured doctor who prescribed the prescription, prescription date, prescription content, etc.), and information that can be obtained from the past medication history or medication notebook (prescription history, information on medical history including complications, whether or not the patient has visited other departments, etc.) may also be registered.

[0085] In this case, the candidate information generating unit 257 extracts information stored in each database based on, for example, a patient ID and performs processing such as name matching and matching. This allows the candidate information generating unit 257 to include various information of the patient corresponding to the medication instruction targeted for the medication history registration support processing in the candidate information. Then, the medication history registration unit 259 registers the various information in the medication history based on the approval of the pharmacist. This will further reduce the workload of pharmacists when entering data related to medication histories. Therefore, the support system 1 according to this modification can more appropriately support the work of pharmacists.

[0086] [Variation 3] In the medication history registration support process of the above embodiment, it is assumed that the pharmacist first selects the medication instruction for which he / she requests the generation of candidate information. Then, for the selected medication instruction, the process performs a series of processes including the generation of candidate information, approval of the candidate information, and updating of the medication history database based on the approval result.

[0087] Alternatively, the system may be configured to perform a series of processes, including generating multiple candidate information items corresponding to multiple medication instructions, collectively approving each of the multiple candidate information items, and updating the medication history database based on the results of the collectively approving the information items. This allows the pharmacist to confirm the contents of the multiple candidate information items at once and collectively approve the registration of the information items in the medication history. In other words, the work of the pharmacist in inputting data related to the medication history can be further reduced.

[0088] The medical history registration support process in this modified example for realizing such collective approval will be described with reference to Fig. 18. Fig. 18 is a flowchart showing the flow of the medical history registration support process executed by the support server 30 in this modified example. The medical history registration support process is started when the support server 30 receives a request for providing candidate information from the terminal device 10.

[0089] In step S51, the support request receiving unit 253 receives a request for collective provision of candidate information from the terminal device 10. Here, in the step corresponding to step S51 in the above-described embodiment (i.e., step S31 in FIG. 16), information identifying the medication instruction of the subject for whom the generation of candidate information is requested is received together with the request for provision of candidate information. In this modified example, instead, information identifying the pharmacist who is requested to generate the candidate information is received together with the request for collective provision of candidate information.

[0090] In step S52, the support request receiving unit 253 refers to the medication history database 273 to identify all information identifying medication instructions corresponding to the information identifying the pharmacist received in step S51 as the target of this process. That is, all medication instructions given by this pharmacist are identified as the target of this process. Note that medication instructions for which candidate information (here, medication instruction text) has already been registered are excluded from the target of this process. Then, the processing from step S32 to step S37 is performed on any of the medication instructions that are the target of this process. The contents of these processes are the same as those of the processes described above with reference to FIG. 16, and therefore repeated explanations will be omitted here.

[0091] In step S53, the candidate information generating section 257 determines whether or not candidate information has been generated for all medication instructions that are the subject of this process and that were identified in step S52. If candidate information has been generated for all medication instructions, the result of determination in step S53 is YES, and the process proceeds to step S54. On the other hand, if candidate information has not been generated for all medication instructions, the result of step S53 is NO, and the process returns to step S32. Then, the process is repeated from step S32 for medication instructions for which candidate information has not yet been generated.

[0092] In step S54, the presentation control unit 258 transmits, together with all the candidate information generated by the candidate information generating unit 257, a request for accepting collective approval from the pharmacist to the terminal device 10 (outputs to the terminal device 10 via the network 40). In step S55, the medication history registration unit 259 receives from the terminal device 10 the approval result of the collective approval for the registration of the candidate information into the medication history from the pharmacist who has been presented with all the candidate information generated by the candidate information generation unit 257 (including a request to register the approved candidate information into the medication history).

[0093] In step S56, the medication history registration unit 259 determines whether or not there is any candidate information approved by the pharmacist based on the received batch approval result. That is, it determines whether or not at least one piece of candidate information has been approved by the pharmacist in the batch approval. If there is no candidate information approved by the pharmacist, the result of step S56 is NO, and the medical history registration support process ends. On the other hand, if there is candidate information approved by the pharmacist, a determination of YES is made in step S56, and the process proceeds to step S57.

[0094] In step S57, the medical history registration unit 259 updates the medical history database. Specifically, the medical history registration unit 259 registers all candidate information approved by the pharmacist as registration targets in the medical history included in the medical history DB 273. In addition, the medical history registration unit 259 transmits a registration request to the pharmacy computer 20 for registering all candidate information approved by the pharmacist as registration targets in the medical history included in the medical history DB 173. After step S57, the medical history registration support process in this modified example ends.

[0095] The medical history registration support process in this modification enables a pharmacist to confirm the contents of multiple candidate information at once and then approve the registration in the medical history at once. In other words, the work of inputting data related to the medical history by the pharmacist can be further reduced.

[0096] In this modified example, the manner in which the pharmacist accepts collective approval of registration to the medication history (for example, the user interface of the approval reception screen, etc.) is not particularly limited, and collective approval can be accepted in various manners. For example, the approval reception screen for each medication instruction as shown in FIG. 9 may be scrolled sequentially in response to a scroll operation by the pharmacist, and approval operations may be accepted sequentially from the pharmacist for each medication instruction. Also, instead of scrolling sequentially, the approval reception screen for each of the multiple medication instructions may be displayed in a list by, for example, displaying thumbnails. In this case, the pharmacist may approve the registration of each medication instruction to the medical history individually for each medication instruction (for example, pressing a button that says "Approve registration to medical history"), or the pharmacist may approve the registration of each medication instruction to the medical history all at once (for example, pressing a button that says "Approve registration to medical history all at once").

[0097] Also, approval may not be accepted in the same manner for all medication instructions, but may be accepted in different manners depending on the medication instructions. For example, if there is no change in the prescription content and the candidate information again contains a medication instruction statement that overlaps with the previous medication instruction statement, it is considered that there is no problem with this candidate information (i.e., this medication instruction statement). Therefore, it is preferable to accept approval operations for such candidate information in a simple manner. For example, it is preferable to automatically switch the scroll display for such candidate information in a short time without requiring the pharmacist to perform a scroll operation, and then accept approval operations all at once. Alternatively, it is preferable to display such candidate information in a small list, and then accept approval operations all at once.

[0098] In contrast, for example, when a drug that requires the involvement of a specialist in pharmaceutical management for safety management (so-called high-risk drug) is prescribed, or when the patient has a special chronic illness, it is considered that attention should be paid to whether or not there is a problem with this candidate information (i.e., this medication instruction). Therefore, it is preferable to accept approval operations for such candidate information in a non-simplified manner. For example, it is preferable to not switch the scroll display for such candidate information unless there is an operation by the pharmacist, and to accept approval operations individually. Alternatively, it is preferable to display such candidate information large on the entire screen, and then accept approval operations individually.

[0099] For this purpose, when controlling the presentation of candidate information to a pharmacist, the presentation control unit 258 may perform control so as to accept collective approval in various modes as described above. In this way, by using various modes for accepting collective approval of registration to the medication history from the pharmacist, it is possible to appropriately support collective approval by the pharmacist.

[0100] [Variation 4] In the medication history registration support process of the above embodiment, the instruction content inference unit 256 infers medication instruction contents by machine learning or a rule base using the feature amount extracted by the feature extraction unit 255 as an input. Then, the candidate information generation unit 257 generates candidate information by extracting medication instruction sentences corresponding to the medication instruction content IDs output by the instruction content inference unit 256 as inference results from the candidate information DB 277. That is, the medication instruction contents are inferred one by one, and medication instruction sentences are extracted one by one corresponding to each of these medication instruction contents. That is, the correspondence between the medication instruction contents and the medication instruction sentences is one-to-one.

[0101] However, one medication instruction sentence may be extracted corresponding to a plurality of medication instruction contents. To this end, for example, a plurality of medication instruction sentences corresponding to a plurality of instruction contents may be extracted as one medication instruction sentence.

[0102] As a specific example, assume that multiple side effects (e.g., lower back pain, lower abdominal pain, and diarrhea) are inferred individually as medication instruction contents by machine learning or rule base. In this case, in the above-mentioned embodiment, three medication instruction sentences corresponding to the medication instruction content IDs of these three side effects are extracted individually one by one. For example, three medication instruction sentences are extracted, such as "Since lower back pain may occur as a side effect, instruct the patient to stop taking the drug and consult a doctor in that case," "Since lower abdominal pain may occur as a side effect, instruct the patient to stop taking the drug and consult a doctor in that case," and "Since diarrhea may occur as a side effect, instruct the patient to stop taking the drug and consult a doctor in that case." However, if all three medication instruction sentences with similar expressions are included in the candidate information and registered in the medication history, the expressions may become redundant and the contents of the medication history may become unclear.

[0103] In such a case, these three medication instruction sentences are extracted as one medication instruction sentence. For example, expressions that have the same or similar content in each medication instruction sentence are extracted as one medication instruction sentence, for example, "Since side effects such as lower back pain, lower abdominal pain, and diarrhea may occur, instruct the patient to stop taking the drug and consult a doctor if this occurs." In this way, the number of characters can be reduced while maintaining the content of the medication instruction sentence, so that the expression when registered in the medication history becomes concise and the content of the medication history becomes clear. In other words, the work of pharmacists inputting data related to the medication history can be further reduced.

[0104] As a method for extracting a plurality of medication instruction sentences as one medication instruction sentence, for example, one medication instruction sentence may be prepared for each combination of a plurality of medication instruction contents. That is, when a first medication instruction content and a second medication instruction content are inferred in the same category such as side effects, one medication instruction sentence to be extracted may be prepared for each of various combinations of medication instruction contents. Alternatively, a rule for combining a plurality of medication instruction sentences (for example, as described above, a rule for combining expressions with common or similar contents) may be established, and one medication instruction sentence may be created on a rule basis based on this rule.

[0105] [Variation 5] Functions applicable to the above-mentioned embodiment and their user interfaces will be described with reference to Figs. 19 and 20. This function can be applied to various situations where candidate information (here, medication instruction sentences) based on inference by the instruction content inference unit 256 is presented. For example, it can be applied to a situation where the candidate information is presented as a candidate medication instruction content to be registered in a medical history. In addition, it can be applied to a situation where the candidate information is presented as medication instruction content recommended in medication instruction.

[0106] Fig. 19 is a schematic diagram showing an example of a medication instruction selection screen 60 displayed in various situations on the terminal device 10 or the support server 30. As shown in Fig. 19, the medication instruction selection screen 60 includes an information display area 61 and a selection operation area 62 as display areas.

[0107] The information display area 61 displays bibliographic information such as the patient's name, buttons for transitioning to other display screens, etc. In addition, the information display area 61 displays information about drugs such as the name and dosage of the drug prescribed (or prescribed) for this patient. For example, information such as "Lipitor Tablets 5 mg" and "Bezatol SR Tablets 200 mg" is displayed.

[0108] In the selection operation area 62, a list of medication instruction contents that may be the subject of medication instruction when these drugs are prescribed is displayed. The display order of each medication instruction content in this list can be determined arbitrarily. In order to determine this display order, a predetermined score is given to highly reliable medication instruction contents, such as medication instruction contents with a high likelihood inference by the instruction content inference unit 256 and medication instruction contents that have been selected by pharmacists multiple times in the past. Then, the medication instruction contents with a high score value are displayed at the top of the list so that they are more likely to be selected by pharmacists. This makes it possible to display each medication instruction content in an order that takes into account the inference results and past selection results.

[0109] Furthermore, medication instruction statements corresponding to each of these medication instruction contents are displayed in the selection operation area 62. Furthermore, a "slide button", a "redisplay next time button", and a "not recommended button" are displayed in the selection operation area 62 corresponding to each of these medication instruction contents. The pharmacist can use these buttons to select the medication instruction content. Each of these buttons will be described below.

[0110] The slide button is a button for switching the selection state of the medication instruction contents. Each time the pharmacist operates the slide button, the state switches between a state in which the medication instruction contents are selected and a state in which the medication instruction contents are not selected. As an initial setting of this slide button, the medication instruction contents inferred by the instruction content inference unit 256 are set to a state in which they are selected before the pharmacist operates the slide button. On the other hand, other medication instruction contents are set to a state in which they are not selected. As a result, at the initial setting stage before the pharmacist operates the slide button, the result of inference by the instruction content inference unit 256 (i.e., AI or rule-based inference) is already reflected. Then, from this state, the pharmacist operates the slide button based on his / her own judgment to correct the selection state of each medication instruction content to a more appropriate one. In other words, the pharmacist does not need to select medication instruction contents from a state in which he / she has no clues, but only needs to select medication instruction contents from a state in which the inference is reflected. In this way, by initializing the slide button, the selection of medication instruction contents by the pharmacist can be semi-automated, reducing the pharmacist's efforts.

[0111] The redisplay next time button is a button for setting the medication instruction contents to be displayed next time as well. When making a selection using the slide button described above, if the pharmacist thinks that the medication instruction contents must be displayed next time as well, the pharmacist operates the redisplay next time button. This causes the medication instruction contents to be displayed in the list next time as well. Note that the medication instruction contents may be displayed continuously not only next time but also the time after that. This prevents a situation in which the pharmacist does not notice the existence of the medication instruction contents next time.

[0112] The "not recommended" button is a button for setting the medication instruction content not to be displayed next time. When making a selection using the slide button described above, if the pharmacist thinks that the medication instruction content does not need to be displayed next time, the pharmacist operates the "not recommended" button. This will prevent the medication instruction content from being displayed in the list next time either. Note that the medication instruction content may be prevented from being displayed not only next time, but also the time after that. This can prevent a situation in which the pharmacist mistakenly selects the medication instruction content next time.

[0113] The scope to which the settings of the redisplay next time button and the not recommended button are applied can be determined as appropriate. For example, they may be applied on a patient-by-patient basis. In this case, the settings of each button are applied to the next medication instruction for that patient, but are not applied to medication instructions for other patients. Similarly, they may be applied on a pharmacy-by-pharmacy or pharmacist-by-pharmacist basis. This allows each pharmacist's judgment to be applied to an appropriate scope.

[0114] In addition to the settings of the Redisplay next time button and the Not recommended button, for example, medication instruction contents whose predetermined score is below a threshold value may not be displayed in the list, and medication instruction contents whose predetermined score is above a threshold value may be displayed in the list. Even in this case, the settings of the Redisplay next time button and the Not recommended button may be applied with priority. Furthermore, when the Not recommended button is set, instead of always not being displayed next time, the score may be reduced to make it less likely to be displayed from the next time.

[0115] In addition, the operation contents of such various buttons (i.e., the pharmacist's judgment after checking the inference result) may be reflected in the criteria for inferring future medication instruction contents by the instruction content inference unit 256. For example, the inference criteria are changed so that the medication instruction contents selected by the slide button and the medication instruction contents for which the redisplay next time button is set are more likely to be inferred thereafter. On the other hand, the inference criteria are changed so that the medication instruction contents not selected by the slide button and the medication instruction contents for which the not recommended button is set are less likely to be inferred thereafter. Such a change in the inference criteria can be realized, for example, by changing the parameters used by the AI ​​for inference or adding a rule that does not output even if inferred. As a result, in the future inference, the instruction content inference unit 256 can make inferences after adding the pharmacist's judgment criteria. Therefore, it is possible to realize highly accurate inferences based on criteria that are more in line with the pharmacist's work.

[0116] Fig. 20 is a schematic diagram showing an example of an instruction home screen 70 displayed in various scenes on the terminal device 10 or the support server 30. As shown in Fig. 20, the instruction home screen 70 includes, as display areas, an information display area 71, a prescription content confirmation area 72, and a medication instruction confirmation area 73. Fig. 20 also conceptually illustrates a pharmacist's finger 80 to show an operation example.

[0117] The information display area 71 displays bibliographic information such as the patient's name, buttons for transitioning to other display screens, etc. In addition, the information display area 71 displays pharmaceutical judgment factors (problems related to the patient) when inference is made by the instruction content inference unit 256. In this example, for problems related to the patient, the relevance (here, percentages indicating the importance) of the inference to each problem is displayed based on the patient attributes, medical history, questionnaire results, and interview results of the patient who answered the interview.

[0118] The prescription content confirmation area 72 displays information about the drug, such as the name and dosage of the drug to be prescribed (or that has been prescribed) for this patient. Note that information such as the name and dosage may be displayed not only for the drug currently prescribed, but also for the drug previously prescribed.

[0119] In the medication instruction confirmation area 73, when these drugs are prescribed, the medication instruction contents selected by the pharmacist as the subject of medication instruction are displayed in a list. For example, the medication instruction contents selected by the pharmacist are displayed in a list as described above with reference to FIG. 19. The display order of each medication instruction content in this list can be determined based on a predetermined score, for example, similar to the display order in FIG. 19. In this case, if medication instruction has been given to this patient before about a certain medication instruction content, the medication instruction about this certain medication instruction content may be postponed, and the content may be displayed lower even if the predetermined score is high. In addition, for example, if medication instruction has been given to this certain medication instruction content before, the certain medication instruction content may be temporarily paused (i.e., snooze) and hidden. Then, when the medication instruction progresses and the number of medication instruction contents displayed in the list decreases, or when a certain time has passed since it was hidden, the content may be displayed again.

[0120] Also, a "slide button" is displayed in medication instruction confirmation area 73. This slide button, like the slide button shown in Fig. 19, is a button for switching the selection state of medication instruction contents. For example, when medication instruction for a certain medication instruction content has been completed or when the pharmacist has determined that medication instruction for this medication instruction content is not necessary after all, the pharmacist may operate this slide button to switch this medication instruction content to an unselected state so that it is not displayed in the list.

[0121] Furthermore, the medication instruction confirmation area 73 accepts a predetermined operation from the pharmacist (for example, a flick operation using the pharmacist's finger 80 or a touch pen). For example, when a flick operation is performed off the screen on a certain medication instruction content, a predetermined process is performed on this certain medication instruction content. For example, the medication instruction on this certain medication instruction content may be postponed, and even if the predetermined score is high, it may be displayed lower. In addition, for example, when a flick operation is performed off the screen, this certain medication instruction content may be temporarily paused and hidden. Then, when the medication instruction progresses and the number of medication instruction contents displayed in the list decreases, or when a certain time has passed since it was hidden, it may be displayed again.

[0122] In this way, the display state in the list can be changed by the pharmacist's operation according to the progress of the medication instruction, etc. For example, medication instruction contents for which medication instruction has been completed can be hidden from the list, medication instruction contents to be postponed can be moved to a lower display order in the list, or medication instruction contents to be postponed can be temporarily suspended from the list and hidden. This allows the pharmacist to easily set the display state to the display state he or she intends, simply by performing an intuitive operation. As described above, the functions and user interface provided by this modified example make it possible to more appropriately support the work of pharmacists from various perspectives.

[0123] As described above, the support server 30 according to this embodiment includes the target information acquisition unit 254, the teaching content inference unit 256, and the candidate information generation unit 257. The target information acquisition unit 254 acquires target information that is to be considered in pharmaceutical instruction to a patient. The instruction content inferring section 256 infers the instruction content of pharmaceutical instruction for the patient based on the object information acquired by the object information acquiring section 254. The candidate information generating unit 257 generates candidate information to be included in the medical history of pharmaceutical instruction to the patient, based on the instruction content inferred by the instruction content inferring unit 256. In this way, the support server 30 can generate candidate information by performing inference based on target information such as prescription data. By using this candidate information, for example, it is possible to reduce the work of a pharmacist inputting data related to a medication history. Therefore, the support server 30 according to the embodiment of the present invention can more appropriately support the work of pharmacists.

[0124] The support server 30 further includes a presentation control unit 258 and a medication history registration unit 259. The presentation control unit 258 performs control for presenting the candidate information generated by the candidate information generating unit 257 to a manager of pharmaceutical guidance for patients. The medical history registration unit 259 registers the candidate information that has been approved by the manager who has received the candidate information as a medical history of pharmaceutical guidance for the patient. This allows the pharmacist to simply check the contents of the candidate information for all or at least a part of the data related to the medication history (e.g., medication instructions) and determine whether or not to approve the registration of the data in the medication history. In other words, the work of the pharmacist in inputting data related to the medication history can be reduced.

[0125] The candidate information includes at least a medication instruction statement corresponding to pharmaceutical instructions for the patient. Approval by the administrator involves selection of a medication instruction sentence to be approved from among the medication instruction sentences included in the candidate information. This allows the pharmacist to simply select a medication instruction message included in the candidate information generated by the support server 30, thereby reducing the effort required to create a medication instruction message.

[0126] When the control for presenting candidate information includes content that an administrator should take note of when approving the candidate information, the presentation control unit 258 performs control for presenting the candidate information in a manner different from other candidate information. This will encourage pharmacists to pay attention to important points.

[0127] In the control for presenting the candidate information, the presentation control unit 258 performs control for presenting each of a plurality of pieces of candidate information corresponding to each of pharmaceutical instructions for a plurality of patients. The medical history registration unit 259 registers each of the plurality of pieces of candidate information that have been presented and approved collectively by the manager as a medical history of pharmaceutical guidance for the patient. This allows the pharmacist to confirm the contents of multiple candidate information items at once and then approve their registration in the medication history all at once. In other words, the work of the pharmacist inputting data related to the medication history can be further reduced.

[0128] The teaching content inferring unit 256 changes the criteria for inferring teaching content based on an instruction from the manager who has received the candidate information. This allows the instruction content inference unit 256 to perform inference after adding the pharmacist's judgment criteria. Therefore, it is possible to realize highly accurate inference based on criteria more in line with the pharmacist's practice.

[0129] The target information acquisition unit 254 further acquires information regarding medical fees for pharmaceutical guidance to the patient. The instruction content inference unit 256 infers instruction contents for pharmaceutical instruction to a patient based on the information related to medical fees acquired by the object information acquisition unit 254 in addition to the object information acquired by the object information acquisition unit 254. This allows for more accurate inference of guidance content by taking into account information related to medical fees (for example, information on a medical fee statement).

[0130] The support server 30 further includes a feature extraction unit 255 . The feature extraction unit 255 extracts feature amounts from the target information acquired by the target information acquisition unit 254 based on preset extraction conditions. The instruction content inference unit 256 infers instruction contents in pharmacological instruction for the patient based on at least the feature amount extracted from the target information. This makes it possible to infer teaching content based on at least a clear indicator, namely, the feature amount.

[0131] As described above, the support system 1 according to this embodiment includes the support server 30 and a plurality of pharmacy computers 20 corresponding to a plurality of pharmacies, respectively. The support server 30 and the multiple pharmacy computers 20 share information including at least the medical history of the pharmaceutical instructions for the patient in accordance with a common specification. This enables the support server 30 to more appropriately support the work of pharmacists at each of the multiple pharmacies based on the information shared with the multiple pharmacy computers 20.

[0132] The present invention is not limited to the above-described embodiment, and modifications and improvements within the scope of the present invention 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 candidate information, but the present invention is not limited to this. In other words, the candidate information presented in the present invention includes various types of medical information.

[0133] In the above embodiment, after the patient is interviewed, the patient waits while the pharmacist prepares the medicine. During this waiting time, simple lifestyle advice information, etc., identified from the interview result may be presented to the patient (for example, displayed on the patient's smartphone, etc.). Furthermore, in the above-mentioned embodiment, a display screen for conducting an interview with a patient and a display screen for a list of medication instruction sentences after approval by a pharmacist (a list of inferential medication instruction candidates and a list of general medication instruction candidates) may be displayed on a device carried by the patient himself (e.g., a smartphone of the patient, etc.).In this case, medication instruction sentences that are easier to understand for patients (e.g., medication instruction sentences in simple expressions without using technical terms) may be prepared in the form of a database, etc., and a display screen of the list of easier-to-understand medication instruction sentences for patients in this database may be displayed on a device carried by the patient himself.

[0134] The above-described series of processes can be executed by hardware or software. In other words, the functional configurations in the above-mentioned embodiments are merely examples and are not particularly limited. That is, it is sufficient that any of the computers constituting the support system 1 has a function capable of executing the above-mentioned series of processes as a whole, and the type of functional block used to realize this function is not particularly limited to the examples shown. Furthermore, one functional block may be configured as a single piece of hardware, a single piece of software, or a combination of both.

[0135] In addition, the recording medium containing the program for executing the series of processes described above may be composed not only of a removable medium distributed separately from the device body in order to provide the program to the user, but also of a recording medium etc. provided to the user in a state in which it is pre-installed in the device body.

[0136] Although the embodiment of the present invention has been described above, the present invention is not limited to the above-described embodiment. Furthermore, the effects described in the present embodiment are merely a list of the most preferable effects resulting from the present invention, and the effects of the present invention are not limited to those described in the present embodiment. [Explanation of symbols]

[0137] 1 Support system, 10 Terminal device, 20 Pharmacy computer, 30 Support server, 40 Network, 51 User interface display control unit (UI display control unit), 52, 254 Target information acquisition unit, 53 Support request unit, 54 Candidate information acquisition unit, 55 Approval reception 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 Medical fee database (Medical fee DB), 277 Candidate information database (Candidate information DB), 252 User interface information generation unit (UI information generation unit), 253 Support request reception unit, 255 feature extraction unit, 256 instruction content inference unit, 257 candidate information generation unit, 258 presentation control unit, 259 medication history registration 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 imaging unit, 831 removable media

Claims

1. an instruction content inference means for inferring instruction content of pharmaceutical instruction to a patient based on target information to be considered in the pharmaceutical instruction to the patient; a candidate information generating means for generating a plurality of pieces of candidate information to be included in a medical history of pharmaceutical guidance for the patient based on the guidance content inferred by the guidance content inferring means; a presentation control means for controlling presentation of the generated plurality of pieces of candidate information to an instructor who provides pharmaceutical guidance to the patient; a medical history registration means for registering the candidate information selected by the instructor after receiving the plurality of candidate information in the medical history of the pharmaceutical instruction for the patient; Equipped with The presentation control means includes: In the pharmaceutical instruction to the patient, the candidate information which has not yet been set as the subject of instruction by the instructor is displayed preferentially over the candidate information which has been set as the subject of instruction.

13. An assistance device comprising:

2. The presentation control means Displaying the plurality of candidate information in a list, by subsequently hiding the candidate information that has been the subject of instruction from the list, temporarily hiding the candidate information that has been the subject of instruction from the list, or lowering the display order of the candidate information that has been the subject of instruction in the list, the candidate information that has not yet been the subject of instruction by the instructor is displayed preferentially over the candidate information that has been the subject of instruction.

2. The support device according to claim 1 .

3. A guidance content inference means for inferring guidance content of pharmaceutical guidance for a patient based on target information to be considered in the pharmaceutical guidance for the patient; a candidate information generating means for generating a plurality of pieces of candidate information to be included in a medical history of pharmaceutical guidance for the patient based on the guidance content inferred by the guidance content inferring means; a presentation control means for controlling presentation of the generated plurality of pieces of candidate information to an instructor who provides pharmaceutical guidance to the patient; a medical history registration means for registering the candidate information selected by the instructor after receiving the plurality of candidate information in the medical history of the pharmaceutical instruction for the patient; Equipped with The presentation control means includes: performing control for presenting both first candidate information based on an inference by the teaching content inference means and second candidate information not based on an inference by the teaching content inference means; The first candidate information is treated as a state selected by the instructor at a stage before the instructor performs an operation.

13. An assistance device comprising:

4. A guidance content inference means for inferring guidance content of pharmaceutical guidance for a patient based on target information to be considered in the pharmaceutical guidance for the patient; a candidate information generating means for generating a plurality of pieces of candidate information to be included in a medical history of pharmaceutical guidance for the patient based on the guidance content inferred by the guidance content inferring means; a presentation control means for controlling presentation of the generated plurality of pieces of candidate information to an instructor who provides pharmaceutical guidance to the patient; a medical history registration means for registering the candidate information selected by the instructor after receiving the plurality of candidate information in the medical history of the pharmaceutical instruction for the patient; Equipped with The teaching content inference means changing a criterion for inferring the instruction content based on an operation by the instructor regarding selection of the candidate information to be registered in the medical history; 13. An assistance device comprising:

5. An assistance method executed by an information processing device, an instruction content inference step of inferring instruction content of pharmaceutical instruction for the patient based on target information to be considered in the pharmaceutical instruction for the patient; a candidate information generating step of generating a plurality of pieces of candidate information to be included in a medical history of pharmaceutical guidance for the patient based on the guidance content inferred in the guidance content inference step; a presentation control step of controlling presentation of the generated plurality of pieces of candidate information to an instructor who provides pharmaceutical guidance to the patient; a medical history registration step of registering the candidate information selected by the instructor who has been presented with the plurality of candidate information as a medical history of pharmaceutical instruction for the patient; Including, In the presentation control step, In the pharmaceutical instruction to the patient, the candidate information which has not yet been set as the subject of instruction by the instructor is displayed preferentially over the candidate information which has been set as the subject of instruction. A support method comprising:

6. On the computer, A guidance content inference function that infers guidance content of pharmaceutical guidance for a patient based on target information to be considered in the pharmaceutical guidance for the patient; a candidate information generating function that generates a plurality of pieces of candidate information to be included in a medical history of pharmaceutical guidance for the patient based on the guidance content inferred by the guidance content inference function; a presentation control function for controlling presentation of the plurality of pieces of generated candidate information to an instructor who provides pharmaceutical guidance to the patient; a medical history registration function for registering the candidate information selected by the instructor after receiving the plurality of candidate information pieces as a medical history of pharmaceutical instruction for the patient; Realize this, The presentation control function includes: In the pharmaceutical instruction to the patient, the candidate information which has not yet been set as the subject of instruction by the instructor is displayed preferentially over the candidate information which has been set as the subject of instruction. A program characterized by:

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