Treatment evaluation method, treatment evaluation device, and treatment evaluation program

Abstract

A treatment evaluation method, a treatment evaluation device, and a treatment evaluation program are provided that can automatically determine the effect of a treatment. [Solution] The treatment evaluation method executed by an information processing device includes a quantification step of quantifying a patient's health condition as a clinical score, a previous score acquisition step of acquiring a previous score which is the patient's previous clinical score, a determination step of determining the improvement status of the patient's symptoms based on the difference between the clinical score and the previous score and a predetermined threshold value, and an improvement rate calculation step of calculating the improvement rate of the patient's symptoms from the clinical score and the previous score.

Description

[Technical field]

[0001] The present disclosure relates to a treatment evaluation method, a treatment evaluation device, and a treatment evaluation program. [Background technology]

[0002] In the field of regenerative medicine, medical institutions are required to regularly report information, including the therapeutic effects of regenerative medicine, to the Ministry of Health, Labor and Welfare, etc. When making regular reports, medical professionals are required to calculate clinical scores based on patient-reported outcome measures (PROMs).

[0003] Conventionally, the general method of collecting information using patient-reported outcome measures was for patients to fill in their answers on a designated form and for medical professionals to collect information based on the patient's answers. Patent Document 1 discloses a method of collecting higher quality information by having patients enter the patient-reported outcome measures electronically. [Prior art documents] [Patent documents]

[0004] [Patent Document 1] Patent No. 6929426 Summary of the Invention [Problem to be solved by the invention]

[0005] Analysis of patient-reported outcome measures and output of treatment evaluations are still performed manually by medical professionals. This clerical work is one of the factors that imposes an excessive burden on medical professionals. In addition, many medical professionals are in busy environments and can only perform the minimum necessary analysis and output, which often makes it difficult to fully utilize the information collected from patients.

[0006] An object of the present disclosure is to provide a treatment evaluation method, a treatment evaluation device, and a treatment evaluation program that can automatically determine the effect of treatment. [Means for solving the problem]

[0007] [1] A treatment evaluation method executed by an information processing device, comprising: A quantification step of quantifying the patient's health condition as a clinical score; A previous score acquisition step of acquiring a previous score, which is the previous clinical score of the patient; an improvement rate calculation step of calculating an improvement rate of the patient's symptoms from the clinical score and the previous score; a determining step of determining an improvement state of the patient's symptoms based on a difference between the clinical score and the previous score and a predetermined threshold value; A method for evaluating a treatment, comprising:

[0008] [2] The method for evaluating a treatment according to the above [1], In the digitizing step, A method for evaluating treatment, wherein the clinical score is quantified based on a patient-reported outcome scale.

[0009] [3] The method for evaluating a treatment according to [1] or [2] above, In the determining step, A method for evaluating treatment, comprising determining that the patient's symptoms have improved or worsened when the difference between the previous score and the clinical score exceeds a predetermined threshold.

[0010] [4] The method for evaluating a treatment according to any one of [1] to [3], In the determining step, When the difference is within a predetermined threshold range, the patient's condition is determined to be stable.

[0011] [5] The method for evaluating a treatment according to any one of [1] to [4], The method for evaluating a treatment further comprises: A method for evaluating a treatment, comprising an output step of outputting the assessment result of the treatment effect on the patient.

[0012] [6] The method for evaluating a treatment according to any one of [1] to [5], storing the improvement rate calculated in the improvement rate calculation step; In the output step, retrieving one or more of the stored past improvement rates of said patient; The treatment evaluation method further outputs a transition between the retrieved past improvement rate and the improvement rate calculated in the improvement rate calculation step.

[0013] [7] The method for evaluating a treatment according to any one of [1] to [6], In the output step, a preset character string corresponding to the determination result is output.

[0014] [8] The method for evaluating a treatment according to any one of [1] to [7], In the output step, The treatment evaluation method includes outputting the assessment result in a preset format.

[0015] [9] The method for evaluating a treatment according to any one of [1] to [8], The information output in the output step includes: A method for evaluating a treatment, comprising information on the progression of the patient's clinical scores.

[0016]

[10] The method for evaluating a treatment according to any one of [1] to [9], The treatment evaluation method further includes a treatment suggestion step of proposing at least one of a treatment method for the patient or a medication content for the patient based on the improvement rate.

[0017]

[11] The method for evaluating a treatment according to any one of [1] to

[10] , a case receiving step of receiving input of information regarding the case of the patient; The method for evaluating a treatment further includes an evaluation method determination step of determining or proposing an evaluation method to be used based on the received case.

[0018]

[12] The method for evaluating a treatment according to

[11] , In the case reception step, A method for evaluating treatment, comprising accepting input of information relating to the case of the patient by accepting selection of one or more options suited to the condition of the patient from a plurality of preset options.

[0019]

[13] The method for evaluating a treatment according to

[11] or

[12] above, In the case reception step, A method of evaluating treatment, comprising obtaining information regarding the patient's case from the patient's medical record.

[0020]

[14] An information processing device including a control unit, The control unit is The patient's health status is quantified as a clinical score, Obtain a previous score, which is the patient's previous clinical score; determining an improvement status of the patient's symptoms based on a difference between the clinical score and the previous score and a predetermined threshold value; Calculating an improvement rate of the patient's symptoms from the clinical score and the previous score. Treatment evaluation device.

[0021]

[15] To the computer, To quantify a patient's health status as a clinical score; obtaining a previous score, the previous clinical score for the patient; determining an improvement status of the patient's symptoms based on a difference between the clinical score and the previous score and a predetermined threshold; Calculating an improvement rate of the patient's symptoms from the clinical score and the previous score; A treatment evaluation program to implement Effect of the Invention

[0022] According to the treatment evaluation method, treatment evaluation device, and treatment evaluation program disclosed herein, the effect of treatment can be automatically determined. [Brief description of the drawings]

[0023] [Figure 1] 1 is a block diagram showing a configuration of a treatment evaluation system according to an embodiment of the present disclosure. [Diagram 2] FIG. 2 is a block diagram showing a configuration of a server device according to an embodiment of the present disclosure. [Diagram 3] FIG. 2 is a block diagram showing a configuration of a patient terminal according to an embodiment of the present disclosure. [Figure 4] FIG. 2 is a block diagram showing a configuration of a medical staff terminal according to an embodiment of the present disclosure. [Diagram 5] 1 is a block diagram showing a configuration of a printing device according to an embodiment of the present disclosure. [Figure 6] 11 is a flowchart illustrating an example of the operation of the treatment evaluation system according to an embodiment of the present disclosure. [Figure 7] 11 is a flowchart illustrating an example of the operation of the treatment evaluation system according to an embodiment of the present disclosure. [Figure 8] FIG. 13 is a diagram showing an example of effect assessment information output by a treatment evaluation system according to an embodiment of the present disclosure. [Figure 9] FIG. 13 is a diagram showing an example of effect assessment information output by a treatment evaluation system according to an embodiment of the present disclosure. [Figure 10] FIG. 13 is a diagram showing an example of effect assessment information output by a treatment evaluation system according to an embodiment of the present disclosure. [Figure 11] 13 is a flowchart showing an operation example of a treatment evaluation system according to a first modified example of the present disclosure. DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0024] Hereinafter, an embodiment of the present disclosure will be described with reference to the drawings. In each drawing, parts having the same configuration or function are denoted by the same reference numerals. In the description of this embodiment, duplicated descriptions of the same parts may be omitted or simplified as appropriate.

[0025] FIG. 1 is a diagram showing an example of a treatment evaluation system 1 according to an embodiment of the present disclosure.

[0026] The treatment evaluation system 1 includes a server device 10, a patient terminal 20, a medical staff terminal 30, and a printing device 40, which are capable of communicating with each other via a network 2. The network 2 is, for example, the Internet, but also includes an ad-hoc network, a LAN (Local Area Network), a MAN (Metropolitan Area Network), or other networks, or any combination of these.

[0027] The server device 10 judges the effectiveness of the treatment. The patient terminal 20 accepts a patient-reported outcome measure from the patient and transmits it to the server device 10. When the server device 10 receives the patient-reported outcome measure from the patient terminal 20, it calculates a clinical score for the patient based on the received patient-reported outcome measure. The server device 10 compares the calculated clinical score with past clinical scores of the same patient to judge the improvement status of the patient's symptoms. The server device 10 transmits the judgment result to the medical staff terminal 30. The medical staff terminal 30 outputs the received judgment result in any format.

[0028] 2 shows a configuration example of the server device 10. The server device 10 includes a control unit 11, a storage unit 12, and a communication unit 13. The server device 10 is, for example, a server that belongs to a cloud computing system or other computing system and implements various functions.

[0029] The control unit 11 includes one or more processors, one or more dedicated circuits, or a combination of these. The processor is a general-purpose processor such as a CPU (Central Processing Unit) or a GPU (Graphics Processing Unit), or a dedicated processor specialized for a specific process. The dedicated circuit is, for example, an FPGA (Field-Programmable Gate Array) or an ASIC (Application Specific Integrated Circuit). The control unit 11 executes information processing related to the operation of the server device 10 while controlling each part of the server device 10.

[0030] The storage unit 12 includes one or more semiconductor memories, one or more magnetic memories, one or more optical memories, or a combination of at least two of these. The semiconductor memory is, for example, a random access memory (RAM) or a read only memory (ROM). The RAM is, for example, a static RAM (SRAM) or a dynamic RAM (DRAM). The ROM is, for example, an electrically erasable programmable ROM (EEPROM). The storage unit 12 functions as, for example, a main storage device, an auxiliary storage device, or a cache memory. The storage unit 12 stores information used in the operation of the server device 10 and information obtained by the operation of the server device 10.

[0031] The memory unit 12 further stores an evaluation method and a judgment standard for calculating a clinical score of a patient. The evaluation method includes questions, options, and scores corresponding to the options. The evaluation methods stored in the memory unit 12 include, but are not limited to, KOOS (Knee injury and Osteoarthritis Outcome Score), JOABPEQ (JOA Back Pain Evaluation Questionnaire), DASH / Quick DASH (Disabilities of the Arm, Shoulder and Hand questionnaire), Shoulder 36, and EQ-5D-5L (EuroQol-5 dimensions 5 Level).

[0032] The memory unit 12 further stores clinical score information of the patient. The clinical score information includes patient information, clinical scores calculated in the past, the date of assessment, the date of administration, the therapeutic effect, and the evaluation method used as the basis for assessing the therapeutic effect. The patient information may include the patient's age, sex, physical information such as height, weight, and muscle mass, the name of the clinic the patient visits, the name of the disease, medical history, sports history, details of treatment, number of treatments, treatment period, severity of the disease, classification of image findings, duration of illness, physical findings, blood and biochemical test findings, physiological test findings, and social situation.

[0033] The communication unit 13 includes one or more communication interfaces. The communication interface is, for example, a LAN interface. The communication unit 13 receives information used in the operation of the server device 10, and transmits information obtained by the operation of the server device 10. The server device 10 is connected to the network 2 by the communication unit 13, and communicates information with other devices via the network 2.

[0034] The operation of the server device 10 is realized by a processor included in the control unit 11 executing a program. The program can be recorded on a computer-readable recording medium. The computer-readable recording medium is, for example, a magnetic recording device, an optical disc, a magneto-optical recording medium, or a semiconductor memory. The program is distributed in a state recorded on a portable recording medium such as a DVD (Digital Versatile Disc) or a CD (Compact Disc)-ROM on which the program is recorded. Some or all of the operations of the server device 10 may be executed by a dedicated circuit included in the control unit 11.

[0035] 3 shows an example of the configuration of the patient terminal 20. The patient terminal 20 includes a control unit 21, a storage unit 22, a communication unit 23, an input unit 24, and an output unit 25. The patient terminal 20 is any electronic terminal used by a patient. The patient terminal 20 may be, but is not limited to, a portable information terminal. For example, a general-purpose electronic device such as a smartphone, a tablet terminal, or a PC, or a dedicated electronic device, can be used as the patient terminal 20. The patient terminal 20 may be a smartphone or the like owned by the patient, or may be a tablet terminal or PC owned by a medical institution.

[0036] The control unit 21 includes one or more processors, one or more dedicated circuits, or a combination of these. The processor is a general-purpose processor such as a CPU or a GPU, or a dedicated processor specialized for a specific process. The dedicated circuit is, for example, an FPGA or an ASIC. The control unit 21 executes information processing related to the operation of the patient terminal 20 while controlling each part of the patient terminal 20.

[0037] The storage unit 22 includes one or more semiconductor memories, one or more magnetic memories, one or more optical memories, or a combination of at least two of these. The semiconductor memories are, for example, RAM or ROM. The RAM is, for example, SRAM or DRAM. The ROM is, for example, EEPROM. The storage unit 22 functions, for example, as a main storage device, an auxiliary storage device, or a cache memory. The storage unit 22 stores information used in the operation of the patient terminal 20 and information obtained by the operation of the patient terminal 20.

[0038] The communication unit 23 includes one or more communication interfaces. The communication interface is, for example, an interface compatible with a mobile communication standard such as LTE (Long Term Evolution), 4G (4th Generation), or 5G (5th Generation), or a LAN interface. The communication unit 23 receives information used in the operation of the patient terminal 20, and transmits information obtained by the operation of the patient terminal 20. The patient terminal 20 is connected to the network 2 by the communication unit 23 via a nearby router device or a mobile communication base station, and communicates information with other devices via the network 2.

[0039] The input unit 24 includes one or more input interfaces. The input interface is, for example, a physical key, a capacitive key, a pointing device, a touch screen integrated with a display, or a microphone that accepts voice input. The input interface may further include a camera that captures a captured image or an image code, or an IC card reader. The input unit 24 accepts an operation to input information used for the operation of the patient terminal 20, and sends the input information to the control unit 21.

[0040] The output unit 25 includes one or more output interfaces. The output interface is, for example, an external or built-in display that outputs information as an image or video, a speaker that outputs information as sound, or an interface for connecting to an external output device. The display is, for example, an LCD (Liquid Crystal Display) or an organic EL (Electro Luminescence) display. The output unit 25 outputs information obtained by the operation of the patient terminal 20.

[0041] The operation of the patient terminal 20 is realized by a processor included in the control unit 21 executing a program. The program can be recorded on a computer-readable recording medium. The computer-readable recording medium is, for example, a magnetic recording device, an optical disk, a magneto-optical recording medium, or a semiconductor memory. The program is distributed in a state recorded on a portable recording medium such as a DVD or CD-ROM on which the program is recorded. The program may be distributed by storing the program in the storage of the server device 10 and transferring the program from the server device 10 to another computer. Some or all of the operations of the patient terminal 20 may be executed by a dedicated circuit included in the control unit 21.

[0042] 4 shows an example of the configuration of the medical staff terminal 30. The medical staff terminal 30 includes a control unit 31, a storage unit 32, a communication unit 33, an input unit 34, and an output unit 35. The medical staff terminal 30 is, for example, a general-purpose electronic device such as a smartphone, a tablet terminal, or a PC, or a dedicated electronic device.

[0043] The control unit 31 includes one or more processors, one or more dedicated circuits, or a combination of these. The processor is a general-purpose processor such as a CPU or GPU, or a dedicated processor specialized for a specific process. The dedicated circuit is, for example, an FPGA or ASIC. The control unit 31 executes information processing related to the operation of the medical staff terminal 30 while controlling each part of the medical staff terminal 30.

[0044] The storage unit 32 includes one or more semiconductor memories, one or more magnetic memories, one or more optical memories, or a combination of at least two of these. The semiconductor memories are, for example, RAM or ROM. The RAM is, for example, SRAM or DRAM. The ROM is, for example, EEPROM. The storage unit 32 functions as, for example, a main storage device, an auxiliary storage device, or a cache memory. The storage unit 32 stores information used in the operation of the medical staff terminal 30 and information obtained by the operation of the medical staff terminal 30.

[0045] The communication unit 33 includes one or more communication interfaces. The communication interface is, for example, an interface compatible with a mobile communication standard such as LTE, 4G, or 5G, or a LAN interface. The communication unit 33 receives information used in the operation of the medical staff terminal 30, and transmits information obtained by the operation of the medical staff terminal 30. The medical staff terminal 30 is connected to the network 2 by the communication unit 33 via a nearby router device or a mobile communication base station, and communicates information with other devices via the network 2.

[0046] The input unit 34 includes one or more input interfaces. The input interface is, for example, a physical key, a capacitive key, a pointing device, a touch screen integrated with a display, or a microphone that accepts voice input. The input interface may further include a camera that captures a captured image or an image code, or an IC card reader. The input unit 34 accepts an operation to input information used in the operation of the medical staff terminal 30, and sends the input information to the control unit 31.

[0047] The output unit 35 includes one or more output interfaces. The output interface is, for example, an external or built-in display that outputs information as an image or video, a speaker that outputs information as sound, or an interface for connecting to an external output device. The display is, for example, an LCD or an organic EL display. The output unit 35 outputs information obtained by the operation of the medical staff terminal 30.

[0048] The operation of the medical staff terminal 30 is realized by a processor included in the control unit 31 executing a program. The program can be recorded on a computer-readable recording medium. The computer-readable recording medium is, for example, a magnetic recording device, an optical disk, a magneto-optical recording medium, or a semiconductor memory. The program is distributed in a state recorded on a portable recording medium such as a DVD or a CD-ROM on which the program is recorded. The program may be distributed by storing the program in the storage of the server device 10 and transferring the program from the server device 10 to another computer. Some or all of the operations of the medical staff terminal 30 may be executed by a dedicated circuit included in the control unit 31.

[0049] 5 shows an example of the configuration of the printing device 40. The printing device 40 includes a communication unit 41 and a printing unit 42. The printing device 40 receives printing information from other devices via the network 2 and performs printing. The printing device 40 is configured, for example, as a facsimile machine, a copier, or the like.

[0050] The communication unit 41 includes one or more communication interfaces. The communication interface is, for example, an interface compatible with a mobile communication standard such as LTE, 4G, or 5G, or a LAN interface. The communication unit 41 receives print information from other devices. The printing device 40 is connected to the network 2 by the communication unit 41 via a nearby router device or a mobile communication base station, and communicates information with other devices via the network 2.

[0051] The printing unit 42 generates a printed matter based on the printing information received by the communication unit 41. Specifically, the printing unit 42 generates a printed matter by printing based on the printing information on a print medium such as paper arranged. The printing unit 42 may include a display device such as a digital photo frame, and generate an electronic printed matter as a printed matter by displaying information based on the printing information on the display device.

[0052] Next, the process by which the treatment evaluation system 1 judges the effect of treatment on a patient will be described with reference to Figs. 6 to 7. Fig. 6 is a flowchart showing the process by which the treatment evaluation system 1 judges the effect of treatment. Fig. 7 is a flowchart showing, more specifically, the process by which the server device 10 judges the effect of treatment. In the following description, "assessment methods arbitrarily selected by medical professionals" all refer to the same evaluation method. Examples of evaluation methods arbitrarily selected by medical professionals include, but are not limited to, KOOS, JOABPEQ, DASH / Quick DASH, and EQ-5D-5L.

[0053] The patient terminal 20 receives a patient-reported outcome scale from the patient via the input unit 24 (step S101). The questions in the patient-reported outcome scale differ depending on the evaluation method. For example, in the KOOS, which is an evaluation method for knee treatment, 42 questions about the knee are set, and the patient inputs answers on a five-point scale based on the condition of his or her knee. When the control unit 21 of the patient terminal 20 receives the patient-reported outcome scale from the patient, it transmits the patient-reported outcome scale information to the server device 10 via the communication unit 23.

[0054] When the control unit 11 of the server device 10 receives the patient-reported outcome scale information from the patient terminal 20, it calculates a clinical score (step S102). The clinical score is calculated based on an evaluation method arbitrarily selected by a medical professional. The control unit 11 of the server device 10 stores the calculated clinical score in the memory unit 12. The control unit 11 of the server device 10 may call up patient information from the memory unit 12 in addition to the patient-reported outcome scale information, and calculate the clinical score taking the patient information into consideration.

[0055] After calculating the clinical score, the control unit 11 of the server device 10 judges the effect of the treatment on the patient (step S103). The judgment is performed by calculating the difference between the previous score, which is the clinical score calculated previously for the patient, and the clinical score calculated in step S102. The evaluation method used to calculate the clinical score calculated in step S102 and the previous score is the same.

[0056] More specifically, the control unit 11 of the server device 10 acquires the previous score of the patient (step S201). The previous score of the patient may be stored in the storage unit 12 of the server device 10. In this case, the control unit 11 of the server device 10 acquires the previous score of the patient from the storage unit 12.

[0057] When the control unit 11 of the server device 10 acquires the previous score of the patient, the control unit 11 calculates the difference between the previous score and the clinical score calculated in step S102 (step S202).

[0058] When the control unit 11 of the server device 10 calculates the difference between the two scores, it judges the effect of the treatment on the patient based on the calculation result and a predetermined judgment criterion (step S203). The predetermined judgment criterion is, for example, but not limited to, MCID (Minimal Clinically Important Difference). MCID is the minimum change value that can be interpreted as a beneficial change in the patient. A threshold value is set for MCID for each evaluation method and each disease. When the difference between the patient's clinical score and the previous score exceeds the threshold value, the control unit 11 of the server device 10 judges that there has been some change in the patient's symptoms. When MCID is used, the value judged as the threshold value differs depending on the evaluation method and the disease, but is generally a value that changes by 3.0% to 52.0% of the total score. The control unit 11 of the server device 10 judges the patient's symptoms as either improving, worsening, or stable, based on the difference between the two scores and the threshold value of the predetermined judgment criterion. In addition, the control unit 11 of the server device 10 may determine the status as “under observation” if there is only data from before the patient's treatment, or as “other” if the treatment has been interrupted or the patient has died.

[0059] The judgment of the tendency to improve, the tendency to worsen, and the stability will be described by taking the case where KOOS is used as the evaluation method and MCID is used as the judgment criterion. KOOS is an evaluation method in which 100 points is the maximum score for each of five categories, and the higher the score, the better the symptoms. The MCID of KOOS is 6 to 20. In this example, the threshold is 10 points. The control unit 11 of the server device 10 judges that the patient's symptoms are tending to improve when the clinical score of the patient is 10 points or more higher than the previous score in any of the five categories. Conversely, when the clinical score is 10 points or more lower, it judges that the symptoms are tending to worsen. When the difference is less than 10 points in any category, it judges that the patient's symptoms are stable. Note that some evaluation methods judge that the lower the clinical score, the better the patient's symptoms are. In this case, conversely to the above, when the clinical score is lower than the previous score by more than a predetermined threshold, it judges that the patient's symptoms are tending to improve. When the clinical score is higher than a predetermined threshold, it judges that the symptoms are tending to worsen. When the difference is within the threshold, it judges that the patient's symptoms are stable.

[0060] The predetermined criteria may be those established by OMERACT (Outcome Measures in Rheumatology). The criteria established by OMERACT are criteria that can be adopted when WOMAC (Western Ontario and McMaster Universities Arthritis Index) is used as the evaluation method. The criteria established by OMERACT can also be adopted when KOOS, which has similar questions to WOMAC, is used as the evaluation method.

[0061] If the difference between the two scores exceeds a threshold derived from a predetermined criterion and indicates a tendency toward improvement (step S203: improvement), the control unit 11 of the server device 10 determines that the patient's condition has improved (step S204).

[0062] If the difference between the two scores exceeds a threshold derived from a predetermined criterion and indicates a worsening tendency (step S203: worsening), the control unit 11 of the server device 10 determines that the patient's condition has worsened (step S205).

[0063] If the difference between the two scores does not exceed a threshold derived from a predetermined criterion (step S203: stable), the control unit 11 of the server device 10 determines that the patient's condition is stable (step S206).

[0064] When the control unit 11 of the server device 10 judges the symptoms of the patient, the control unit 11 stores the judgment result in the storage unit 12 (step S207).

[0065] A medical worker can refer to the judgment result of the therapeutic effect on the patient stored in the storage unit 12 of the server device 10 by the above process from the medical worker terminal 30. When the control unit 31 of the medical worker terminal 30 receives an instruction to refer to the judgment result from the medical worker via the input unit 34, it acquires the judgment result information from the server device 10. The judgment result information includes, for example, information to identify the patient, the name of the disease or the condition before administration, the result of the effectiveness judgment, the scientific basis of the effectiveness judgment, the administration date, the judgment date, and the diagnosis content. The result of the effectiveness judgment is selected from, for example, "improved," "stable," "worsened," "under observation," or "other." "Under observation" is selected when there is no visit after administration or when the telephone consultation has been completed and the situation has only been grasped. "Other" is selected when the patient has died of another disease or when the details are unknown due to being unable to be contacted. The scientific basis of the effectiveness judgment may include information on the evaluation method used for the effectiveness judgment. The diagnosis content may include an explanation of the therapeutic effect and each clinical score before and after administration. The description of the therapeutic effect is a character string corresponding to the result of the effect assessment, and may be preset. When the control unit 31 of the medical staff terminal 30 acquires the assessment result information, it outputs the assessment result information to the output unit 35. At this time, the control unit 31 of the medical staff terminal 30 may store the assessment result information in the storage unit 32.

[0066] The medical staff can also print and output the determination result information that the medical staff terminal 30 acquires from the server device 10. When the control unit 31 of the medical staff terminal 30 receives an instruction to print the determination result from the medical staff via the input unit 34, it transmits the determination result information and the print instruction to the printer 40 via the communication unit 33. The print instruction includes information on the format in which the determination result information is output. The format is set in advance and is stored in the storage unit 12 of the server device 10 or the storage unit 32 of the medical staff terminal 30. The format may be, for example, a format used in regular reports on regenerative medicine to the Ministry of Health, Labor and Welfare, etc.

[0067] FIG. 8 shows an example of the judgment result information output by the output unit 35 and the printing device 40 of the medical staff terminal 30. The judgment result information shown in FIG. 8 includes a patient ID for identifying the patient, the name of the disease or the condition before administration, the result of the effect judgment, the scientific basis of the effect judgment, the administration date, the judgment date, and the period elapsed since the administration date, and the diagnosis. The explanation of the treatment effect included in the diagnosis is "not improved" if the treatment effect is "stable" or "worsened", and "pain has been alleviated" if the treatment effect is "improved". The judgment result information may include the improvement rate of the patient's symptoms, which will be described later. Specifically, the VAS values ​​of the patient before and after administration of the original data 27212 in FIG. 8 are 6 points and 7 points. Therefore, the improvement rate of the VAS is 16.7%. Similarly, the patient's pain scores before and after administration were 53 and 44 points, with an improvement rate of -17.0%, the symptom scores were 50 and 57 points, with an improvement rate of 14.0%, the ADL scores were 56 and 48 points, with an improvement rate of -14.3%, the Sport / Rec scores were 10 and 18 points, with an improvement rate of 80.0%, and the QOL scores were 13 and 0 points, with an improvement rate of -100.0%. The therapeutic effect was judged using the MCID criterion described later. Details will be described later.

[0068] FIG. 9 shows an example of displaying past clinical scores for one patient in chronological order based on the judgment result information. FIG. 10 shows a composite graph illustrating the transition of clinical scores for one patient based on the judgment result information. In FIG. 10, the bar graph shows the VAS score, and the scale on the vertical axis on the left corresponds to the bar graph. The line graphs show Pain, Symptom, ADL, Sport / Rec, and QOL, respectively, and the scale on the vertical axis on the right corresponds to the line graph. The horizontal axis shows time. The output unit 35 and the printer 40 of the medical staff terminal 30 may output past clinical scores for one patient in chronological order as shown in FIG. 9. Furthermore, the control unit 31 of the medical staff terminal 30 may create a graph or the like relating to the transition of clinical scores for one patient based on the judgment result information, and output it via the output unit 35 or the printer 40.

[0069] The control unit 11 of the server device 10 calculates the improvement rate of the patient's symptoms from the clinical score calculated in step S102 and the previous score (step S104). The method for calculating the improvement rate is not particularly limited, but may be calculated, for example, by the following formula (1). In the following formula (1), P is the improvement rate, x is the clinical score, and y is the previous score.

number

[0070] The control unit 11 of the server device 10 may output the improvement rate calculated in step S104 via the output unit 35 of the medical staff terminal 30 or the printing device 40. The output format is not particularly limited, and may be, for example, a format in which it is written together with other judgment result information as shown in Fig. 8. The control unit 11 of the server device 10 may also call up one or more past improvement rates for one patient from the storage unit 12 and output the progress of the symptom improvement rate in chronological order.

[0071] The control unit 11 of the server device 10 may calculate statistical data by tabulating the improvement rate of the patient's symptoms based on a predetermined criterion. The predetermined criterion may be, for example, "improvement rate for each clinic," "improvement rate for each treatment method," "improvement rate for each patient attribute (age, sex, physique, treatment period, etc.)," ​​etc. The tabulation method is not particularly limited, but patients who are to become a population may be determined based on patient information, and statistical data may be calculated for the population using a predetermined criterion. For example, when calculating statistical data for "improvement rate for each clinic," attention is focused on "the clinic visited" among the patient information, and patients are set as a population for each clinic. After that, the improvement rate for the population is tabulated, so that the improvement rate for each clinic can be calculated.

[0072] The control unit 11 of the server device 10 may store the improvement rate of the patient's symptoms calculated in step S104 in the storage unit 12 by linking it with the contents of the treatment and medication performed on the patient. The control unit 11 of the server device 10 may propose at least one of the contents of the treatment or medication to be performed in the future for the patient based on the linking data between the improvement rate of the patient's symptoms and the contents of the treatment and medication performed on the patient. The method of generating the proposed contents is not particularly limited, and for example, a learning model may be trained using linked data between the past improvement rates and the treatment and medication contents including other patients as teacher data, and the proposed contents may be generated based on the learned model. The learning model is a model created by machine learning using a machine learning algorithm. The learning model may be, for example, a machine learning model built based on a decision tree. The machine learning model built based on a decision tree is, for example, Light GBM, XGBoost, etc., but is not limited thereto. Alternatively, the learning model may be a model generated based on a machine learning algorithm such as CNN (Convolutional Neural Network), RNN (Recurrent Neural Network), or other deep learning.

[0073] The control unit 11 of the server device 10 may predict the future improvement rate of the patient from the data linking the improvement rate of the patient's symptoms with the details of the treatment and medication administered to the patient. The method of predicting the future improvement rate is not particularly limited, but for example, the prediction may be made by a formula calculated by performing regression analysis on the linking data of the improvement rates and the treatment and medication administered in the past, including other patients.

[0074] When a patient is administered a plurality of therapies, a plurality of medications, or a combination thereof, the control unit 11 of the server device 10 may, for example, perform a multiple regression analysis of past therapies or medication contents and past improvement rates including other patients, and calculate which therapy, medication, or combination thereof contributes to the improvement rate of the patient. In this case, the control unit 11 of the server device 10 may use each of the therapies or medication contents as an explanatory variable and the improvement rate as an objective variable. The explanatory variables may include age, sex, number of treatments, severity of disease, classification of image findings, duration of disease, etc. The algorithm for variable selection is not particularly limited, and may be, for example, a brute force method or a stepwise method.

[0075] The method of calculating the relationship between the treatment method or medication, or a combination thereof, and the contribution to the patient's improvement rate is not limited to multiple regression analysis. For example, logistic regression analysis, decision tree, support vector machine, Bayesian model, or other methods may be used.

[0076] With such a configuration, the administrative burden on medical professionals can be reduced. Also, medical professionals can easily create explanatory materials for patients. Furthermore, patients have more opportunities to receive explanations about their symptoms and progress in treatment, and can feel satisfied and at ease with the treatment content. Therefore, one embodiment of the present disclosure having the above configuration contributes to the smooth progress of treatment.

[0077] Next, as a first modified example of the present disclosure, a method for selecting or proposing an evaluation method to be used in accordance with a patient's case will be described with reference to Fig. 11. Fig. 11 is a flowchart showing a process in which the treatment evaluation system 1 selects or proposes an evaluation method to be used and then judges the treatment effect.

[0078] The control unit 11 of the server device 10 receives information on the case of a patient from the patient terminal 20 or the medical staff terminal 30 via the communication unit 13 (step S301). The information on the case of a patient includes, for example, the name of the disease, the date of first consultation, the treatment period, the treatment method, the medication history, and the like, but is not limited thereto.

[0079] The control unit 11 of the server device 10 may acquire the patient's medical record information stored in the storage unit 12 or the storage unit 32 of the medical staff terminal 30 as information related to the patient's case. As another method, the control unit 11 of the server device 10 may display one or more options indicating the patient's condition on the patient terminal 20 or the medical staff terminal 30, accept the selection of an option that matches the patient's condition, and acquire the information related to the patient's case.

[0080] The control unit 11 of the server device 10 determines the evaluation method to be used from the evaluation methods stored in the storage unit 12 based on the information on the patient case acquired in step S301 (step S302). Instead of selecting one evaluation method to be used, the control unit 11 of the server device 10 may select one or more evaluation methods and output them as candidates for the evaluation method to be used to the medical staff terminal 30. In this case, the control unit 11 of the server device 10 may determine the evaluation method to be used as the evaluation method received from the medical staff terminal 30.

[0081] Thereafter, step S303 is the same as step S101, step S304 is the same as step S102, and step S305 is the same as step S103.

[0082] With this configuration, even inexperienced medical personnel can easily select an appropriate evaluation method. In addition, the time spent considering which evaluation method to use can be shortened, thereby reducing the administrative burden on medical personnel.

[0083] Next, a first example of a method for calculating a clinical score and a treatment evaluation method using the treatment evaluation system 1 according to the present embodiment will be described. In the first example, the KOOS is used as an evaluation method to evaluate treatment for a patient's knee symptoms. The criterion used is the MCID.

[0084] First, we will explain the questions that patients answer. Patients answer questions about the condition of their knees. The questions consist of 42 questions, and are answered on a 5-point scale.

[0085] Next, the method of calculating the clinical score will be explained. In the KOOS, questions belong to one of the categories of "Pain", "Symptoms", "ADL", "Sport / Rec" and "QOL". The number of questions in each category is 9 for "Pain", 7 for "Symptoms", 17 for "ADL", 5 for "Sport / Rec", and 4 for "QOL". In the KOOS, the maximum score for each category is 100 points, and the higher the score, the better the condition of the patient's knee. For each question, 0, 1, 2, and 3 points are assigned in order from the option with the mildest symptoms (best condition), and 4 points are assigned to the option with the most severe symptoms (worst condition). The clinical score a1 based on the KOOS is calculated for each category using the following formula (2). In the formula, x is the sum of the raw scores corresponding to the patient's answers, and y is the raw score when the patient answers all questions in the category with the most severe symptoms, that is, "the number of questions in the category x 4".

number

[0086] Next, a method for determining the therapeutic effect will be described. In the first embodiment, the therapeutic effect is determined using MCID. The MCID of KOOS is 6 to 20, and the threshold value is 10 points in the first embodiment. That is, if the difference between any score in each category between the calculated clinical score and the previously calculated clinical score is improved by 10 points or more, the patient's condition is determined to have improved. On the other hand, if the difference between any score in each category between the calculated clinical score and the previously calculated clinical score is worsened by 10 points or more, the patient's condition is determined to have worsened. If the difference between all scores in each category between the calculated clinical score and the previously calculated clinical score is improved or worsened by less than 10 points, the patient's condition is determined to be stable.

[0087] When at least one category of the clinical score has improved by more than a threshold value compared to the previously calculated clinical score, the patient's condition may be determined to have improved even if other categories have deteriorated by more than a threshold value compared to the previously calculated clinical score. In other words, when at least one category of the clinical score has improved by more than a threshold value compared to the previously calculated clinical score, the patient's condition may be determined to have improved. The method of determination when different results are calculated in multiple categories is not limited to this, and for example, when the number of categories that have deteriorated by more than a threshold value is greater than the number of categories that have improved by more than a threshold value, the patient's condition may be determined to have worsened. When the number of categories that have improved by more than a threshold value and the number of categories that have deteriorated by more than a threshold value are the same, the patient's condition may be determined to have improved.

[0088] 8, the difference between pre- and post-administration in any of "Pain," "Symptom," "ADL," and "Sport / Rec" does not exceed 10 points, and "QOL" has deteriorated by 10 points or more, so the control unit 11 of the server device 10 determines that the patient's symptoms have worsened. Note that the MCID of VAS is 10 to 30 as described later, but in the above example, the difference between pre- and post-administration is 1 point, which does not reach the minimum MCID and does not affect the above determination.

[0089] A second example of the method for calculating a clinical score and the treatment evaluation method by the treatment evaluation system 1 according to this embodiment will be described. In the second example, the KOOS is used as the evaluation method to evaluate the treatment for the patient's knee symptoms. The evaluation criteria used are those established by OMERACT. The method for calculating the clinical score based on the KOOS is the same as in the first example.

[0090] According to the criteria established by OMERACT, a patient's condition is judged to have improved if the improvement rate of the "Pain" or "ADL" score is 50% or more and the raw score has improved by 20 points or more, or if the score improvement rate of two or more of the three items "Pain", "ADL" and "QOL" is 20% or more and the raw score has improved by 10 points or more. On the other hand, a patient's condition is judged to have worsened if the score deterioration rate of the "Pain" or "ADL" score is 50% or more and the raw score has worsened by 20 points or more, or if the score deterioration rate of two or more of the three items "Pain", "ADL" and "QOL" is 20% or more and the raw score has worsened by 10 points or more. If none of the above applies, the patient's condition is judged to be stable.

[0091] A third example of the method for calculating a clinical score and the treatment evaluation method by the treatment evaluation system 1 according to the present embodiment will be described. In the third example, JOABPEQ is used as the evaluation method to evaluate the treatment for the patient's lower back pain. The criterion used is MCID.

[0092] First, we will explain the questions that patients will answer. Patients answer questions about their back pain. The questionnaire consists of 25 questions. Patients can choose the answer that best applies to them from two to five options.

[0093] Next, we will explain how to calculate the clinical score. In JOABPEQ, questions belong to one of five categories: "pain-related disorder," "lumbar spine dysfunction," "gait dysfunction," "social life disorder," and "psychological disorder." Some questions belong to multiple categories. Each category has four questions for "pain-related disorder," six for "lumbar spine dysfunction," five for "gait dysfunction," four for "social life disorder," and seven for "psychological disorder." Each category is scored out of a maximum of 100 points, and the higher the score, the better the patient's condition of lower back pain.

[0094] Next, a method for determining the therapeutic effect will be described. In the third embodiment, the therapeutic effect is determined using MCID. The MCID of JOABPEQ is 20. That is, if the difference between any score in each category between the calculated clinical score and the previously calculated clinical score is improved by 20 points or more, the patient's symptoms are determined to have improved. On the other hand, if the difference between any score in each category between the calculated clinical score and the previously calculated clinical score is worsened by 20 points or more, the patient's symptoms are determined to have worsened. If the difference between all scores in each category between the calculated clinical score and the previously calculated clinical score is improved or worsened by less than 20 points, the patient's symptoms are determined to be stable.

[0095] A fourth example of the method for calculating a clinical score and the method for evaluating a treatment by the treatment evaluation system 1 according to the present embodiment will be described. In the fourth example, the Quick DASH is used as an evaluation method to evaluate the treatment for the upper limbs of a patient. The criterion used is the MCID.

[0096] First, we explain the questions that patients will answer. Patients answer questions about the condition of their upper limbs. The questions consist of 19 questions. Patients choose the answer that best applies to them from five options.

[0097] Next, the method of calculating the clinical score will be explained. In the Quick DASH, questions belong to one of three categories: "functional impairment / symptoms," "work," and "sports / art activities." The number of questions in each category is 11 for "functional impairment / symptoms," 4 for "work," and 4 for "sports / art activities." The maximum score for each category is 100 points, and the lower the score, the better the condition of the patient's upper limbs. For each question, 1, 2, 3, and 4 points are assigned in order from the option with the mildest symptoms (best condition), and 5 points are assigned to the option with the most severe symptoms (worst condition). Among the clinical scores based on the Quick DASH, the "functional impairment / symptoms" score a2 is calculated using the following formula (3). In the following formula, x is the sum of the raw points corresponding to the patient's answers, and n is the number of questions answered by the patient.

number

[0098] Next, a method for determining the therapeutic effect will be described. In the fourth embodiment, the therapeutic effect is determined using MCID. The MCID of Quick DASH is 7 to 26, and the threshold value is 14 points in the fourth embodiment. That is, if the difference between any score in each category between the calculated clinical score and the previously calculated clinical score is improved by 14 points or more, the patient's symptoms are determined to have improved. On the other hand, if the difference between any score in each category between the calculated clinical score and the previously calculated clinical score is worsened by 14 points or more, the patient's symptoms are determined to have worsened. If the difference between all scores in each category between the calculated clinical score and the previously calculated clinical score is improved or worsened by less than 14 points, the patient's symptoms are determined to be stable.

[0099] A fifth example of the method for calculating a clinical score and the method for evaluating a treatment by the treatment evaluation system 1 according to the present embodiment will be described. In the fifth example, the EQ-5D-5L is used as the evaluation method to evaluate the health-related QOL of a patient. The criterion used is the MCID.

[0100] First, we explain the questions that patients will answer. Patients answer questions about their health-related QOL status. The questionnaire consists of five questions. Patients choose the answer that best applies to them from the five options.

[0101] Next, the method of calculating the clinical score will be explained. In the EQ-5D-5L, the questions are about "Mobility", "Self-Care", "Usual Activities", "Pain / Discomfort", and "Anxiety / Depression". The highest QOL (healthy) option is rated 1, and the lowest QOL option is rated 5. The EQ-5D-5L is scored full on 1, which is the best QOL (perfect health). Each option has a coefficient set as shown in Table 1 below, and the score is calculated by subtracting the sum of the constant term 0.060924 and the coefficient set for each option from 1. If all questions are scored 1, i.e., the option with the highest QOL is selected, the score will be 1.

[0102] [Table 1]

[0103] Next, a method for determining the therapeutic effect will be described. In the fifth embodiment, the therapeutic effect is determined using MCID. The MCID of EQ-5D-5L is 0.03 to 0.52. In the fifth embodiment, if the difference between the calculated clinical score and the clinical score calculated previously is improved by 0.11 points or more, the patient's health-related QOL is determined to have improved. On the other hand, if the difference between the calculated clinical score and the clinical score calculated previously is worsened by 0.11 points or more, the patient's health-related QOL is determined to have deteriorated. If the calculated clinical score and the clinical score calculated previously are improved or deteriorated by less than 0.11 points, the patient's health-related QOL is determined to be stable.

[0104] An embodiment of the present disclosure can be applied to evaluation methods other than those described above. Applicable evaluation methods include, for example, the Visual Analog Scale (VAS) for evaluating pain, the WOMAC for evaluating health-related QOL, the Health Assessment Questionnaire Disease Index (HAQ-DI) for evaluating physical functional disability, the Functional Assessment of Chronic Illness Therapy-Fatigue (FACIT-Fatique) for evaluating fatigue, the Oswestry Disability Index (ODI) for evaluating lower back pain, the Roland-Morris Disability Questionnaire (RMDQ), the Scoliosis Research Society-22r (SRS-22r) for evaluating idiopathic scoliosis, the Zurich Claudication Questionnaire (ZCQ) for evaluating postoperative symptoms of lumbar spinal canal stenosis, the Lumbar Stiffness Disability Index (LSDI) for evaluating complaints after lumbar fusion surgery, the Neck Disability Index (NDI) for evaluating neck pain, the JOA Cervical Myelopathy Evaluation Questionnaire (JOACMEQ) for evaluating cervical myelopathy, and the MHQ / brief for evaluating the hand. MHQ (Michigan Hand Outcomes Questionnaire), PRWE (Patient-Rated Wrist Evaluation) to evaluate wrist function, PREE (Patient-Rated Elbow Evaluation) to evaluate elbow function, CTSI / BCTQ (Carpal Tunnel Syndrome Instrument / Boston Carpal Tunnel Questionnaire) to evaluate carpal tunnel syndrome, ASES (American Shoulder and Elbow Score) to evaluate shoulder joint, SST (Simple Shoulder Test), SPADI (Shoulder Pain and Disability Index), Sholder36, iHOT12 (International Hip Outcome Score 12), iHOT33 (International Hip Outcome Score 33), NAHS (Non Arthritis Hip Score), mHHS (modified Harris Hip Score), HOOS (Hip Disability and Osteoarthritis Outcome Score), FJS-12 (Forgotten Joint Score-12), IKDC (International Knee Documentation Committee subjective knee form), Lysholm (Lysholm Knee Scoring Scale), Tegner (Tegner Activity Scale), KSS-2011 (Knee Society Score-2011), OKS (Oxford Knee Score), AOFAS (American Orthopaedic Foot & Ankle Society), JSSF (Japanese Society for Surgery of the Japanese Society of the American ... Foot), SAFE-Q (Self-Administered Foot Evaluation Questionnaire), PDAS (Pain Disability Assessment Scale) to evaluate chronic pain, SMI (Simplified Menopausal Index) to evaluate menopausal symptoms, KCCQ (Kansas City Cardiomyopathy Questionnaire) to evaluate heart failure, MLHFQ (Minnesota Living with Heart Failure Questionnaire), and MMSE (Mini-Mental State Examination) to evaluate dementia. When using the above evaluation methods, the MCID can be used for any of the judgment criteria. The MCID corresponding to each evaluation method is as shown in Table 2 below.

[0105] [Table 2] TIFF0007630210000007.tif38170

[0106] The above evaluation methods and criteria are merely examples, and the present disclosure is also applicable to evaluation methods and criteria other than those described above.

[0107] The present disclosure is not limited to the above-described embodiments. For example, multiple blocks shown in the block diagram may be integrated, or one block may be divided. Instead of executing multiple steps shown in the flowchart in chronological order as described, each step may be executed in parallel or in a different order depending on the processing capacity of the device executing each step, or as necessary. Other modifications are possible without departing from the spirit of the present disclosure. [Explanation of symbols]

[0108] 1. Treatment Evaluation System 2 Network 10. Server equipment 11 Control section 12 Storage section 13. Communications Department 20 Patient terminal 21 Control section 22 Memory section 23 Communications Department 24 Input section 25 Output section 30 Medical staff terminals 31 Control Unit 32 Storage section 33 Communications Department 34 Input section 35 Output section 40 Printing device 41 Communications Department 42 Printing Department

Claims

1. A treatment evaluation method executed by an information processing device, comprising: A quantification step of quantifying the patient's health condition as a clinical score; A previous score acquisition step of acquiring a previous score, which is the previous clinical score of the patient; a determining step of determining an improvement state of the patient's symptoms based on a difference between the clinical score and the previous score and a predetermined threshold value; an improvement rate calculation step of calculating an improvement rate of the patient's symptoms from the clinical score and the previous score; A method for evaluating a treatment, comprising:

2. In the digitizing step, The clinical score is quantified based on a patient-reported outcome scale; The method for evaluating a treatment according to claim 1.

3. In the determining step, If the difference between the previous score and the clinical score exceeds a predetermined threshold, it is determined that the patient's condition has improved or worsened. The method for evaluating a treatment according to claim 1.

4. In the determining step, If the difference is within a predetermined threshold range, the patient's condition is determined to be stable. The method for evaluating a treatment according to claim 3.

5. The method for evaluating a treatment further comprises: An output step of outputting a result of the evaluation of the therapeutic effect on the patient. The method for evaluating a treatment according to claim 1.

6. storing the improvement rate calculated in the improvement rate calculation step; In the output step, retrieving one or more of the stored past improvement rates of said patient; further outputting a transition between the retrieved past improvement rate and the improvement rate calculated in the improvement rate calculation step; The method for evaluating a treatment according to claim 5.

7. In the output step, outputting a preset character string corresponding to the determination result; The method for evaluating a treatment according to claim 5.

8. In the output step, outputting the determination result in a preset format; The method for evaluating a treatment according to claim 5.

9. The information output in the output step includes: Including transition information of the patient's clinical score, The method for evaluating a treatment according to claim 5.

10. The method for evaluating a treatment comprises: Further comprising a treatment suggestion step of proposing at least one of a treatment method for the patient or a medication for the patient based on the improvement rate. The method for evaluating a treatment according to claim 1.

11. The method for evaluating a treatment comprises: a case receiving step of receiving input of information regarding the case of the patient; Further includes an evaluation method determination step of determining or proposing an evaluation method to be used based on the accepted case; The method for evaluating a treatment according to claim 1.

12. In the case reception step, accepting an input of information relating to the case of the patient by accepting one or more selections that match the condition of the patient from a plurality of preset options; The method for evaluating a treatment according to claim 11.

13. In the case reception step, obtaining information regarding the patient's case from the patient's medical record; The method for evaluating a treatment according to claim 11.

14. An information processing device including a control unit, The control unit is The patient's health status is quantified as a clinical score, Obtain a previous score, which is the patient's previous clinical score; determining an improvement status of the patient's symptoms based on a difference between the clinical score and the previous score and a predetermined threshold value; Calculating an improvement rate of the patient's symptoms from the clinical score and the previous score. Treatment evaluation device.

15. On the computer, To quantify a patient's health status as a clinical score; obtaining a previous score, the previous clinical score for the patient; determining an improvement status of the patient's symptoms based on a difference between the clinical score and the previous score and a predetermined threshold; Calculating an improvement rate of the patient's symptoms from the clinical score and the previous score; A treatment evaluation program to implement

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