Medical support systems, medical support devices, medical support methods, and programs

Abstract

To provide a technology with which, in a system for assisting medical personal in conducting medical care, it is possible to change prescription for patients having already been medicated.SOLUTION: Provided is a medical care assistance system comprising: guideline selection mean for selecting a guideline pertaining to the medical treatment of a patient on the basis of prescribed input information; patient information acquisition means for acquiring patient information that includes measured value information pertaining to the biological information of a patient and dosage information regarding medicine prescribed to the patient; assessment means for assessing the suitability of the current medical guideline including the prescribed content of medicine to the patient, on the basis of the selected guideline and the patient information; recommended medical treatment information generation means for generating recommended medical treatment information regarding the measures recommended to be taken for the patient, in accordance with the result of assessment by the assessment means; and output means for outputting the recommended medical treatment information.SELECTED DRAWING: Figure 3

Description

Technical Field

[0001] The present invention belongs to the technical field related to healthcare, and relates to a medical support system, a medical support device, a medical support method, and a program.

Background Art

[0002] Conventionally, as a technology for supporting the prescription of drugs by doctors and the like in medical treatment, a device (system) as described in Patent Document 1 is known. Patent Document 1 calculates a recommendation score of a drug to be prescribed to a patient based on a medical guideline, taking into account the patient's past medical history and contraindication information for a first-time patient, and presents a prescription plan (drug administration candidate) based on the recommendation score, thereby proposing a drug administration support device that supports the determination of the drug to be prescribed.

[0003] However, such a conventional system has a problem that it cannot be applied to patients who are already receiving drug administration. For this reason, for example, when a new complication develops in a patient who is receiving drug administration, or when a patient has already been treated by another doctor (hospital) such as a transferred patient, it cannot cope. Conversely, it also cannot cope with cases where the patient's condition improves due to improvement of lifestyle habits or removal of factors that have worsened diseases such as stress.

Prior Art Documents

Patent Documents

[0004]

Patent Document 1

Summary of the Invention

Problems to be Solved by the Invention

[0005] In view of the above problems, the present invention aims to provide a technology that can also change prescriptions for patients who are already receiving drug administration in a medical support system. do

END

[0006] To solve the above problems, the present invention adopts the following configuration. That is, A guideline selection means for selecting a guideline related to the treatment of a patient based on predetermined input information, A patient information acquisition means that acquires patient information including measured value information relating to the patient's biological information and medication information, which is information on the drugs prescribed to the patient. A determination means that determines the appropriateness of the current treatment plan, including the content of drug prescriptions for the patient, based on the selected guidelines and the patient information, A recommended treatment information generation means generates recommended treatment information regarding measures recommended to be taken for the patient, in accordance with the determination result of the determination means, An output means for outputting the aforementioned recommended treatment information, It is a medical support system that has [specific features / abilities].

[0007] Here, "specified input information" includes the patient's medical history, the International Classification of Diseases (ICD) code for the disease, the patient's biochemical test results, and various other test results. "Guidelines" are envisioned to be, for example, clinical guidelines established by various academic societies for specific diseases, but are not necessarily limited to such examples. For instance, they could be unique guidelines established by an individual physician based on their own knowledge. "Prescription details" refer to the amount, type, and combination of medications, and include prescription patterns that summarize these. "Recommended measures for the patient" include not only changes to prescription details but also measures other than medication, such as conducting various tests or changing the applicable guidelines. "Output means" are examples. For example, it could be a display device such as an LCD, or a printing device such as a printer.

[0008] With this structure, it is possible to determine whether the current prescription (medication status) is appropriate based on the guidelines and the patient's current condition, and if it is not appropriate, to suggest appropriate (i.e., recommended) measures. Therefore, even for patients who are already receiving medication, appropriate measures, including changes to the prescription, can be proposed as needed.

[0009] Furthermore, the determination means may at least determine whether the currently adopted prescription is excessive for the patient's medical condition based on the patient information, and the recommended treatment information generation means may generate recommended treatment information recommending a reduction and / or decrease in the dosage of the medication prescribed to the patient if the currently adopted prescription is excessive for the patient's medical condition. With such a configuration, if the prescription is excessive for the patient's current medical condition, a reduction in the dosage of the medication can be recommended.

[0010] Furthermore, the determination means may at least determine whether the drugs related to the currently adopted prescription can be replaced with a combination drug, and the recommended treatment information generation means may generate recommended treatment information recommending a change to the prescription to a combination drug if the drugs related to the currently adopted prescription can be replaced with a combination drug. With such a configuration, even if a prescription is not problematic from the standpoint of pharmacological efficacy, if there is a combination of drugs that can be replaced with a combination drug, it is possible to recommend a prescription change that can reduce the burden on the patient taking medication by presenting the combination drug.

[0011] Furthermore, the guidelines may specify recommended prescriptions according to the patient's condition, and the determination means may at least determine whether the currently used prescription matches the recommended prescription, and the recommended treatment information generation means may generate recommended treatment information recommending a change to the recommended prescription if the currently used prescription does not match the recommended prescription. With such a configuration, if a prescription different from the one recommended by the guidelines is being given, the physician can be presented with information to that effect and a recommendation to prescribe with the recommended prescription.

[0012] Furthermore, the guidelines specify recommended prescriptions according to the patient's condition, the patient information includes predetermined improvement target criteria related to the biological information, the determination means at least determines whether the currently adopted prescription matches the recommended prescription and whether the measured value information has achieved the improvement target criteria, and the recommended treatment information generation means may generate recommended treatment information recommending a prescription change based on the next step in the recommended prescription in the guidelines, or recommended treatment information recommending the implementation of tests for the patient, if the measured value information has not achieved the improvement target criteria and the currently adopted prescription matches the recommended prescription.

[0013] Here, the "improvement target criteria" may be a general normal value for the target biological information, or it may be a value that is determined on a case-by-case basis depending on the patient's condition, prescription, etc.

[0014] With the above structure, it is possible to recommend appropriate measures for patients who have not achieved their improvement target criteria despite being prescribed medication according to the recommended prescription pattern in accordance with the guidelines. In other words, when recommended prescription content (prescription pattern) is specified in the guidelines, it is usually the case that a minimal prescription pattern in terms of the type and amount of medication is recommended in the initial stages of treatment, and a recommended prescription pattern is specified in which the type and amount are increased in stages according to the treatment effect (or disease condition). For this reason, if the treatment goal has not been achieved despite being prescribed medication according to the recommended prescription pattern in accordance with the guidelines, the next recommended measure can be recommended. Medication based on a specific pattern is recommended. On the other hand, it is possible that the guidelines currently applied to the patient may not be appropriate in the first place (due to the onset of complications, etc.), and in such cases, a change to appropriate guidelines will be necessary. For this reason, we recommend conducting tests as appropriate based on patient data, including measured values, and prescription details, and propose considering changes to the guidelines.

[0015] Furthermore, the medical support system further includes a non-recommended drug determination means that determines, based on the patient information, whether or not there are any non-recommended drugs that are not recommended to be prescribed to the patient. The recommended treatment information generation means may also generate recommended treatment information that recommends changing the prescription to one that does not include the non-recommended drug if such non-recommended drug is present.

[0016] Here, "non-recommended drugs" refers to drugs and combinations thereof that are contraindicated or unacceptable (such as those for which patients have reported side effects). With this structure, it is possible to propose a prescription change that excludes the non-recommended drugs that should not be prescribed to the patient.

[0017] Furthermore, the predetermined input information may include the International Classification of Diseases (ICD) code related to the patient's disease. This makes it possible to efficiently select the appropriate guidelines based on the disease-identifying code.

[0018] In addition, the biological information may include at least a blood pressure value, and the disease to be treated in the patient may be hypertension. Since hypertension treatment usually lasts for a long time and there are other diseases related to blood pressure values, the present invention that can recommend a review of guidelines and prescription patterns applied according to regular test results for these is suitable.

[0019] In addition, the present invention has the guideline selection means, the patient information acquisition means, the determination means, and the recommended treatment information generation means, and can also be regarded as a medical support device that constitutes at least a part of the medical support system according to any one of claims 1 to 8.

[0020] In addition, the present invention can also be regarded as a program for causing a computer to function as such a medical support device, and a computer-readable recording medium in which such a program is non-temporarily recorded.

[0021] In addition, the present invention includes a guideline selection step of selecting guidelines related to the treatment of a patient based on predetermined input information, a patient information acquisition step of acquiring patient information including measurement value information related to the biological information of the patient and dosing information which is information on drugs prescribed to the patient, a determination step of determining the appropriateness of the current treatment policy including the prescription details of drugs for the patient based on the selected guidelines and the patient information, a recommended treatment information generation step of generating recommended treatment information about measures recommended to be taken for the patient according to the determination result of the determination step, an output step of outputting the recommended treatment information, and can also be regarded as a medical support method having the above.

[0022] Note that each of the above configurations and processes can be combined with each other to constitute the present invention as long as no technical contradiction occurs.

Effects of the Invention

[0023] According to the present invention, the present invention supports medical professionals in providing medical care. do The system can provide technology that allows for changes to prescriptions for patients who are already receiving medication. [Brief explanation of the drawing]

[0024] [Figure 1] Figure 1 is a schematic diagram showing the configuration of the medical support system 1 according to an embodiment. [Figure 2] Figure 2 is a flowchart schematically showing the general flow of hypertension treatment performed in the example. [Figure 3] Figure 3 is a block diagram showing the functional configuration of a server device according to an embodiment. [Figure 4] Figure 4 is an explanatory diagram showing an example of guidelines and formulation patterns in the embodiment. [Figure 5] Figure 5 is a block diagram showing the functional configuration of the physician's terminal according to the embodiment. [Figure 6] Figure 6 is the first diagram illustrating an example of a screen displayed on the physician's terminal. [Figure 7] Figure 7 is a second diagram illustrating an example of a screen displayed on the physician's terminal. [Figure 8] Figure 8 is the third diagram illustrating an example of a screen displayed on the physician's terminal. [Figure 9] Figure 9 is a flowchart showing an example of the processing performed by the medical support system according to the embodiment. [Figure 10] Figure 10 is a schematic diagram of the medical support system 2 according to a modified example of the embodiment. [Modes for carrying out the invention]

[0025] <Example 1> Hereinafter, an example of a specific embodiment of the present invention will be described with reference to the drawings.

[0026] (System Configuration) Figure 1 is a schematic diagram showing the configuration of the medical support system 1 according to this embodiment. As shown in Figure 1, the medical support system 1 consists of a server device 100, a physician-side terminal 200 used by a physician, a patient-side terminal 300 used by a patient P, and a blood pressure monitor 400, and each of these components can communicate with each other via a communication network N.

[0027] The medical support system 1 according to this embodiment is a system used for telemedicine, and it supports doctors in treating patients by transmitting blood pressure values ​​measured by the patient at home to a server device 100 via a network N, processing various information including the measured values, and providing it to the doctor.

[0028] In this embodiment, we will explain the treatment process for a patient with hypertension using Figure 2 as an example. Figure 2 is a schematic flowchart showing an example of the treatment process for hypertension. As shown in Figure 2, a patient diagnosed with hypertension begins medication treatment according to a doctor's prescription and continuously measures their blood pressure at home. After a predetermined period (for example, 1 to 2 weeks), it is determined whether the measured value has reached a predetermined target value (hereinafter, the measurement reaching the target value will also be expressed as "controlled"). Here, the measurement reaching the target value means, for example, that the blood pressure value is below a predetermined threshold. If the measured value is controlled, treatment with the same prescription is continued, and after another predetermined period (for example, 1 month), it is determined again whether the measured blood pressure is controlled.

[0029] On the other hand, if the target value is not met, the patient's medication adherence is checked to see if they are taking their medication as prescribed. Changes in the measured values ​​over a specified period are also reviewed and used, along with information on medication adherence, to determine the treatment plan.

[0030] If a doctor determines, based on the changes in the measured values, that the medication is having some effect even if the target value has not been achieved, they will decide to continue prescribing the same medication. In that case, a determination will be made again after a predetermined period (for example, 1 to 2 weeks) to see whether the blood pressure measurements are under control.

[0031] Furthermore, if the medication is ineffective, the possibility of other diseases will be considered, and a decision will be made to conduct additional tests or to implement treatment (including prescriptions) that take other diseases into account. In that case, after a predetermined period (e.g., 1-2 weeks), a determination will be made again as to whether the blood pressure measurements are under control.

[0032] Furthermore, if the situation is not due to another disease, but rather to side effects that could lead to improvement by changing the medication, the prescription will be modified. In such cases, a reassessment will be made after a predetermined period (e.g., 1-2 weeks) to determine whether the blood pressure readings are under control.

[0033] The treatment of hypertensive patients is carried out by repeatedly performing the above flow. The medical support system 1 in this embodiment supports the performance of such treatment and reduces the burden on doctors (healthcare professionals). The following describes each component of the system.

[0034] (Server device) Figure 3 is a block diagram showing the functional configuration of the server device 100. The server device 100 is composed of a general-purpose server computer and includes a control unit 110, storage means 120, and communication means 130.

[0035] The control unit 110 is a means for controlling the server device 100 and is composed of a processor such as a CPU (Central Processing Unit) and a DSP (Digital Signal Processor). The control unit 110 also includes the following functional modules related to medical support: a patient information acquisition unit 111, a guideline selection unit 112, an appropriateness determination unit 113, a non-recommended drug determination unit 114, a recommended treatment information generation unit 115, and a status confirmation image generation unit 116. In this embodiment, the server device 100 corresponds to the medical support device.

[0036] The patient information acquisition unit 111 acquires information related to the patient's illness and treatment via the communication network N and stores it in the storage means 120. Here, the patient information includes the patient P's medical history entered by the doctor, the International Classification of Diseases (ICD code) related to the illness, biochemical test results and other test results, information on prescribed medications, blood pressure readings taken by the patient P with the blood pressure monitor 400, and information related to the patient P's medication adherence.

[0037] The guideline selection unit 112 is a functional unit that selects the most suitable guideline for treating a patient's disease based on predetermined information. Generally, the treatment of a patient's disease is determined based on clinical guidelines established for each disease (for example, the hypertension treatment guidelines issued by the Japanese Society of Hypertension in the case of hypertension). However, since other diseases often coexist, it is necessary to select appropriate guidelines (and prescription patterns) that take these complications into account in order to provide appropriate treatment.

[0038] Therefore, the guideline selection unit 112 identifies the patient's disease based on various information such as past medical history, biochemical test results such as HbA1c, NT-proBNP, blood potassium concentration, and serum creatinine, electrocardiogram (ECG) findings, left ventricular ejection fraction (LVEF) by echocardiography, and arteriosclerosis indicators, and selects the optimal guideline (and prescription pattern). Specifically, the guideline and prescription pattern are selected based on the following criteria, for example.

[0039] In other words, if no complications other than hypertension are anticipated, select the standard prescription pattern from the "Hypertension Guidelines." If diabetes is present, or if HbA1c is above a specified value, select the diabetes-complication prescription pattern from the "Hypertension Guidelines." If heart failure is present, or if NT-proBNP is If the value is above a predetermined value, or if LVEF < 40%, select the hypertension-related prescription pattern from the "Heart Failure Guidelines." If renal failure is present, or if eGRF calculated from serum creatinine is above a predetermined value, select the renal failure-related prescription pattern from the "Hypertension Guidelines." This guideline information may be read from storage in the memory device 120 as described later, or it may be obtained from an external database via the communication network N each time.

[0040] Figure 4 shows an example of a guideline and prescription pattern. In Figure 4, the type of drug is indicated by a symbol: A represents ACE inhibitors / ARBs, β represents beta-blockers, C represents CCBs, H represents thiazide diuretics, L represents loop diuretics, N represents ARNI, M represents MRAs, and S represents SLTG2 inhibitors.

[0041] As shown in Figure 4, the hypertension guidelines define four types of prescription patterns, as an example: no complications, complications with diabetes, complications with renal failure, and complications with heart failure. The heart failure guidelines define one type of prescription pattern, as an example. Each of these prescription patterns has stages (Step 1 to 3), and the number of types of medications included in the prescription pattern increases as the stage progresses.

[0042] The appropriateness determination unit 113 makes a determination regarding the appropriateness of the treatment plan for patient P based on the selected guideline / prescription pattern and patient information. The specific details of the determination will be described later. In addition, the non-recommended drug determination unit 114 determines whether there are any non-recommended drugs that are not recommended to be prescribed to patient P, based on patient information and drug information described later. "Non-recommended drugs" refer to drugs and combinations thereof that fall under contraindications or unacceptable drugs (such as those for which the patient has complained of side effects).

[0043] The recommended treatment information generation unit 115 generates recommended treatment information that suggests to healthcare professionals what measures (such as changes in prescriptions or additional tests) are recommended to be taken for patient P, based on the judgment results of the appropriateness judgment unit 113 and the non-recommended drug judgment unit 114. The status confirmation image generation unit 116 generates a treatment status confirmation image that allows users to view information on the changes in measured values ​​measured by patient P with the blood pressure monitor 400 over a predetermined period, as well as information related to the patient's medication adherence. The generated recommended treatment information and treatment status confirmation image are then transmitted to the physician's terminal 200 via the communication network N.

[0044] The storage means 120, although not shown in the figures, includes a main memory unit such as ROM (Read-only memory) or RAM (Random Access Memory), and an auxiliary storage unit such as EPROM, HDD (Hard Disk Drive) or SSD (Solid State Device), or removable media. The auxiliary storage unit stores the operating system (OS), various programs, etc. The stored programs are loaded into the working area of ​​the main memory unit and executed, and through the execution of the programs, each component is controlled, thereby enabling the realization of each functional unit that fulfills a predetermined purpose.

[0045] Furthermore, as shown in Figure 3, the auxiliary storage unit of the storage means 120 includes a patient information storage unit 121, a guideline information storage unit 122, a disease classification information storage unit 123, and a drug information storage unit 124. The patient information storage unit 121 stores various information acquired by the patient information acquisition unit 111. The guideline information storage unit 122 stores the guideline information mentioned above. The disease classification information storage unit 123 stores information on diseases and their associated information. international The disease classification code (ICD code) is stored. The drug information storage unit 124 stores drug information (name, manufacturer, dosage form, effects, side effects, contraindications, etc.) and information related to combination drugs of these drugs.

[0046] The communication means 130 is a communication means for connecting the server device 100 to the communication network N, and is composed of, for example, a communication interface board and a wireless communication circuit for wireless communication.

[0047] (Doctor's terminal) Figure 5 is a block diagram showing the functional configuration of the physician's terminal 200. The physician's terminal 200 is a general-purpose computer, such as a fixed-location personal computer, a portable notebook personal computer, or a tablet terminal, and is equipped with a control unit 210, input means 220, output means 230, storage means 240, and communication means 250.

[0048] The control unit 210 is a means for controlling the physician's terminal 200 and is composed of, for example, a CPU. The input means 220 is a means for receiving information input from external sources, such as a keyboard, mouse, touch panel, camera, and microphone. The output means 230 is composed of, for example, a liquid crystal display and a speaker. The storage means 240 is composed of, similar to a server device, a main memory unit, an auxiliary memory unit, etc., and stores the operating system (OS), various programs, and various data acquired via the communication network N. The communication means 250 is composed of, for example, a communication interface board and a wireless communication circuit for wireless communication.

[0049] Although not shown in the diagram, the physician's terminal may also be able to access the electronic medical record management system. In such a case, the patient's electronic medical record data stored in the electronic medical record management system may be read and this electronic medical record data may be sent to the server device 100, or recommended treatment information, treatment status confirmation images, etc., sent from the server device 100 may be linked with the electronic medical record data. In such a case, it becomes possible for the physician to check the recommended treatment information and treatment status confirmation images via the electronic medical record management system.

[0050] On the physician's terminal 200, recommended treatment information and treatment status confirmation images are acquired from the server device 100 via the communication network N, and this information is output to the output means 230. Figures 6 to 8 show examples of screens displayed on the output means 230 of the physician's terminal 200. Figure 6 is a treatment status confirmation image for an individual patient P, and the screen includes measurement value change information Tr and medication information Me.

[0051] As shown in Figure 6, the measurement value change information Tr in the treatment status confirmation image displays the average values ​​of systolic blood pressure (SYS), diastolic blood pressure (DIA), and heart rate (7 days avg home BP & Pulse) for a one-week period (a set period). More specifically, the weekly average values ​​of SYS and DIA are displayed for each time period, morning (after waking up) and evening (before going to bed). In addition to being written numerically, these values ​​are also presented as a graph with bars filling in the space between SYS and DIA, visually showing the relationship with a threshold line indicating the target value. The lines extending above and below the bars in the graph indicate the variability of the measured values ​​during the one-week measurement period, with the line extending upwards indicating the maximum blood pressure value for that week, and the line extending downwards indicating the minimum blood pressure value. Furthermore, weeks in which the bar portion is hatched suggest that the measurement data is insufficient and therefore the information is not reliable.

[0052] Furthermore, the measurement value change information Tr also shows the amount of change compared to the previous week's value, and the difference from the target value (in this example, SYS is 130 mmHg and DIA is 80 mmHg).

[0053] Furthermore, medication information Me includes the types of medications patient P took that week and the frequency of medication (in this example) The document includes information such as adherence (shown as the drug usage rate), the symptoms and frequency of reported side effects, and other relevant details. It also provides access to prescription information, including the drug brand, dosage form, and dosage.

[0054] Figures 7 and 8 are examples of screens that display recommended treatment information An1 and An2 as pop-ups for images confirming treatment status, respectively. In the example screen in Figure 7, recommended treatment information An1 is displayed, recommending that the patient undergo additional tests because there is insufficient information to select an appropriate guideline. In the example screen in Figure 8, recommended treatment information An2 is displayed, recommending a prescription that matches the appropriate guideline (recommended prescription pattern) because the prescription currently applied to the patient differs from the recommended prescription pattern (recommending a prescription pattern for diabetes).

[0055] By referring to this recommended treatment information, physicians can easily determine what measures (including observation) should be taken for patient P. It should be noted that the recommended treatment information does not necessarily need to be displayed together with the treatment status confirmation image; it may be displayed on a separate screen or displayed independently of the treatment status confirmation image.

[0056] (Patient-side terminal) The patient-side terminal 300 is a portable information processing terminal such as a smartphone, tablet, or smartwatch-type wearable device, and although not shown in the diagram, it includes a control unit such as a CPU, input / output means such as a touch panel display, storage means, and communication means such as a wireless communication circuit.

[0057] The patient terminal 300 transmits to the server device 100 measurement data acquired from the blood pressure monitor 400 (described later), as well as information related to the treatment of the disease, such as medication status and lifestyle habits, which the patient P inputs as needed.

[0058] (Blood pressure monitor) The blood pressure monitor 400 is used by patient P for daily blood pressure measurement and can take any form. For example, it may be a general stationary type, a portable type with a cuff wrapped around the upper arm, or a wearable type worn on the patient's wrist. The blood pressure is measured by the oscillometric method at the operation of patient P (or, in the case of a wearable type, at a pre-set timing or time interval), and the blood pressure data is wirelessly transmitted to the patient terminal 300, for example, by wireless communication. Short-range wireless data communication standards such as Bluetooth® or infrared communication can be used as the communication interface between the blood pressure monitor 400 and the patient terminal 300.

[0059] The blood pressure monitor 400 does not necessarily have a means of communication. In that case, the patient P may manually input measurement data (including blood pressure value and measurement date and time) into the patient terminal 300, and this information may be sent to the server device 100. The measurement data may also include heart rate.

[0060] Furthermore, the patient terminal 300 may also incorporate the functions of a blood pressure monitor 400. For example, if the patient terminal 300 is a wearable device worn on the patient P's wrist, it can also function as a blood pressure monitor 400 if it has a blood pressure measurement function. Conversely, a stationary blood pressure monitor 400 may also function as an information processing terminal and thus serve as the patient terminal 300.

[0061] Furthermore, the blood pressure monitor 400 may use a measurement method that measures blood pressure with each heartbeat, or a trigger measurement method that estimates blood pressure fluctuations based on pulse wave propagation time and uses those fluctuations as a trigger to measure blood pressure at specific points.

[0062] (Flowchart for outputting recommended treatment information) Next, based on Figure 9, the flow of recommended treatment information output processing performed in the medical support system 1 according to this embodiment, which has the configuration described above, will be explained. Figure 9 is a flowchart showing the flow of processing for guideline selection, appropriateness determination, recommended medical information creation, and output performed in the medical support system 1.

[0063] In this embodiment, the recommended treatment information output process is initiated by a request from the physician's terminal 200, the arrival of a predetermined confirmation period, etc., although this is not shown in the diagram. The server device 100 first acquires various information, including patient information (S100). Note that the acquisition of information here also includes reading various information that has been acquired via the communication network N prior to the execution of the process and stored in the storage means 120. Then, the guideline selection unit 112 of the server device 100 selects a guideline / prescription pattern related to the treatment of patient P (S101). Details of this selection process have already been explained in the description of the guideline selection unit 112, so a further description is omitted.

[0064] Next, the appropriateness determination unit 113 uses patient information (measured blood pressure) and a preset lower limit of blood pressure as input information to determine whether the current prescription is excessive for patient P's medical condition (S102). If it is determined that the current prescription is excessive for patient P's medical condition (for example, the measured value is below the lower limit), the recommended treatment information generation unit 115 generates recommended treatment information recommending a reduction and / or decrease in the dosage of the medication (S103), and the process proceeds to step S111.

[0065] On the other hand, in step S102, if it is determined that the current prescription is not excessive for patient P's condition, the appropriateness determination unit 113 then uses patient information, predetermined improvement target reference values, etc., as input information to determine whether the treatment goal has been achieved (S104). If it is determined that the treatment goal has been achieved (the measured value is below the improvement target reference value), the process proceeds to step S105 to determine whether there are any drugs in the current prescription that can be replaced with combination drugs (S105). Specifically, this can be determined, for example, by comparing the prescription content with the combination drug list stored in the drug information storage unit 124. If it is determined in step S105 that there are drugs that can be replaced with combination drugs, the recommended treatment information generation unit 115 generates recommended treatment information recommending that the prescription content be changed to one in which the drug is replaced with the combination drug (S106), and the process proceeds to step S111. On the other hand, if it is determined in step S105 that there are no substitutes for the combination drug, the recommended treatment information generation unit 115 generates recommended treatment information recommending observation (S107), and the process proceeds to step S111.

[0066] If it is determined in step S104 that the treatment goal has not been achieved, the process proceeds to step S108, where the appropriateness determination unit 113 determines whether the current prescription content matches the recommended prescription pattern of the guideline (S108). If it is determined that the prescription content does not match the recommended prescription pattern of the guideline, the recommended treatment information generation unit 115 generates recommended treatment information recommending that the prescription content be changed to match the recommended prescription pattern (S109), and the process proceeds to step S111.

[0067] On the other hand, if step S108 determines that the current prescription content matches the recommended prescription pattern of the guideline, the recommended treatment information generation unit 115 generates recommended treatment information regarding the measures to be taken, using patient information, guideline information, disease classification information, drug information, etc. as input information (S110). Specifically, for example, based on the current prescription content, the recommended treatment information is generated according to the guideline. The current stage is confirmed. If the next stage is set in the guidelines, recommended treatment information is generated to change the prescription content to match the recommended prescription pattern for that next stage (advancing the guideline stage). Alternatively, the non-recommended drug determination unit 114 may be configured to determine whether the recommended prescription pattern for the next stage includes contraindications or unacceptable drugs. If contraindications or unacceptable drugs are included, recommended treatment information is generated that recommends a prescription content that takes this into account.

[0068] Furthermore, if the next stage is not set in the guidelines, it may be possible to generate recommended treatment information that suggests additional testing (suggesting a change in the guidelines), taking into account the possibility that the correct guidelines are not being applied.

[0069] The generated recommended treatment information is then transmitted to the physician's terminal 200, and the output means 230 of the physician's terminal outputs the recommended treatment information (S111), thus completing the series of routines. In this embodiment, step S100 corresponds to the patient information acquisition step, and step S101 corresponds to the guideline selection step. Steps S102, S104, S105, and S108 correspond to the determination steps, and steps S103, S105, S107, S109, and S110 correspond to the recommended treatment information generation steps.

[0070] As described above, the medical support system 1 according to this embodiment can provide recommended treatment information regarding measures that are recommended to be taken for a patient, based on patient information, guideline information, etc. By referring to such recommended treatment information, physicians can easily determine what kind of treatment (measures) should be taken for the patient.

[0071] Furthermore, by re-evaluating the treatment status based on measured biological information and medication information, it becomes possible to recommend changes in prescriptions, including changes in applicable guidelines. This allows for the recommendation of appropriate treatment to physicians, even for patients transferred from other hospitals or patients whose medical condition has changed. In addition, by providing recommended treatment information, it is possible to prevent situations where appropriate treatment intensification is not carried out even though treatment goals have not been achieved (so-called clinical inertia).

[0072] <Variation> The above description of the embodiments is merely illustrative in explaining the present invention, and the present invention is not limited to the specific forms described above. The present invention can be modified and combined in various ways within the scope of its technical concept. For example, in the above embodiments, the invention was described with one physician-side terminal 200 and one patient-side terminal 300 each, but as shown in Figure 10, the present invention can of course also be applied as a medical support system 2 equipped with multiple physician-side terminals 200a to 200n and / or multiple patient-side terminals 300a to 300n.

[0073] Furthermore, in the above embodiment, the guideline selection process in step S101 can be omitted as appropriate in subsequent medical consultations. Also, the above processing flow can be rearranged as appropriate. For example, the determination of whether or not the treatment situation is excessive (S102) may be performed after it has been determined that the treatment goal has been achieved, but before it has been determined whether or not it can be replaced with a combination drug (between steps S104 and S105).

[0074] Furthermore, while the above embodiment described an example of remote treatment for hypertensive patients where the processed biological information is blood pressure (and heart rate), it is obvious that the present invention can be applied to other diseases and biological information, such as blood glucose levels in diabetic patients. Moreover, the present invention does not have to be used in combination with telemedicine; it can also be applied as an offline system or device as long as the necessary input information can be obtained. [Explanation of Symbols]

[0075] 1, 2... Medical support system 100... Server device 110, 210... Control Unit 120, 240...Storage means 130, 250... means of communication 200... Doctor's terminal 220...Input method 230... Output means 300...Patient terminal 400... Blood pressure monitor P...patient N... Communications Network Tr...Measurement value change information Me...Medication Information An1, An2... Recommended treatment information

Claims

1. A guideline selection means for selecting a guideline related to the treatment of a patient based on predetermined input information, A patient information acquisition means that acquires patient information including measured value information relating to the patient's biological information and medication information, which is information on the drugs prescribed to the patient. A determination means that determines the appropriateness of the current treatment plan, including the content of drug prescriptions for the patient, based on the selected guidelines and the patient information, A recommended treatment information generation means generates recommended treatment information regarding measures recommended to be taken for the patient, in accordance with the determination result of the determination means, An output means for outputting the aforementioned recommended treatment information, It has, The measured values ​​related to the aforementioned biological information include the patient's blood pressure value. The determination means at least determines whether the currently used prescription is excessive for the patient's medical condition, based on whether the measured values ​​related to the biological information in the patient information are below a preset lower limit. The recommended treatment information generation means generates recommended treatment information recommending a reduction and / or decrease in the dosage of the medication prescribed to the patient if the currently used prescription is excessive for the patient's medical condition. Medical support system.

2. The predetermined input information includes at least one of the patient's medical history, biochemical test results, electrocardiogram findings, left ventricular ejection fraction by echocardiography, and arteriosclerosis indicators. The guideline selection means identifies the patient's disease based on the predetermined input information and then selects a guideline for the treatment of the patient's disease. A medical support system according to claim 1, characterized in that

3. The determination means at least determines whether the drug related to the currently adopted prescription can be replaced with a combination drug, The recommended treatment information generation means generates recommended treatment information recommending a change in prescription to a combination drug if the drug related to the currently adopted prescription can be replaced with a combination drug. A medical support system according to claim 1 or 2, characterized in that

4. The aforementioned guidelines specify recommended prescriptions according to the patient's condition. The determination means at least determines whether the currently adopted prescription content matches the recommended prescription content, The recommended treatment information generation means generates recommended treatment information recommending a change to the recommended prescription content if the currently used prescription content does not match the recommended prescription content. A medical support system according to any one of claims 1 to 3, characterized in that

5. The aforementioned guidelines specify recommended prescriptions according to the patient's condition. The aforementioned patient information includes predetermined improvement target criteria related to the aforementioned biological information, The determination means at least determines whether the currently adopted prescription content matches the recommended prescription content, and whether the measured value information meets the improvement target criteria. The recommended treatment information generation means generates, if the measured value information does not meet the improvement target criteria and the currently adopted prescription content matches the recommended prescription content, the recommended treatment information recommending a prescription change based on the next step in the recommended prescription content in the guidelines, or the recommended treatment information recommending the implementation of tests for the patient. A medical support system according to any one of claims 1 to 4, characterized in that

6. The system further includes a non-recommended drug determination means for determining whether there are any non-recommended drugs that are not recommended to be prescribed to the patient, based on the aforementioned patient information. The recommended treatment information generation means generates recommended treatment information that recommends changing the prescription to one that does not include the non-recommended drug if such non-recommended drug is present. The medical support system according to claim 5, characterized in that

7. The medical support system according to any one of claims 1 to 6, characterized in that the predetermined input information includes an International Classification of Diseases code relating to the patient's disease.

8. The aforementioned biological information includes at least blood pressure values, and the disease being treated for the patient is hypertension. A medical support system according to any one of claims 1 to 7, characterized in that

9. A medical support device comprising the guideline selection means, the patient information acquisition means, the determination means, and the recommended treatment information generation means, which constitutes at least a part of the medical support system according to any one of claims 1 to 8.

10. A medical support method performed by a computer, The aforementioned computer, A guideline selection step in which a guideline related to the patient's treatment is selected based on the prescribed input information, A patient information acquisition step involves acquiring patient information including measured values ​​related to the patient's biological information and medication information, which is information about the drugs prescribed to the patient. A determination step, in which a determination is made regarding the appropriateness of the current treatment plan, including the content of drug prescriptions for the patient, based on the selected guidelines and the patient information, A recommended treatment information generation step generates recommended treatment information regarding measures recommended to be taken for the patient, based on the determination result of the determination step, An output step that outputs the aforementioned recommended treatment information, It has, The measured values ​​related to the aforementioned biological information include the patient's blood pressure value. In the determination step, it is determined whether the currently used prescription is excessive for the patient's medical condition, based on whether the measured values ​​related to the biological information in the patient information are below a predetermined lower limit. In the recommended treatment information generation step, if the currently used prescription is excessive for the patient's condition, the recommended treatment information is generated that recommends reducing the dosage and / or reducing the amount of medication prescribed to the patient. Medical support methods.

11. A program for causing a computer to function as a medical support device according to claim 9.

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