Information processing system and information processing method

Abstract

An information processing system 10 evaluates the worth of each of a plurality of inspection items. The information processing system 10 comprises: an information acquisition unit 201 that acquires patient information 215 on each of a plurality of patients to be inspected and inspection worth information 216 on an effect obtained by performing an inspection on each of the plurality of patients for the inspection items; a classification unit 202 that classifies the plurality of patients into a plurality of groups on the basis of the patient information 215 and the inspection worth information 216 that have been acquired by the information acquisition unit 201; and an inspection worth representative value calculation unit 204 that calculates, for each of the groups classified by the classification unit 202, an inspection worth representative value 218 that is an index value statistically obtained from the plurality of pieces of inspection worth information 216.

Description

Information processing system and information processing method

[0001] The present disclosure relates to technologies such as an information processing system and an information processing method for improving the efficiency of operations in facilities such as medical facilities.

[0002] In recent years, in the medical industry, due to factors such as a shortage of medical professionals, emphasis has been placed on improving the efficiency of various operations in medical facilities such as hospitals. Patent Document 1 describes a system for generating patient cohorts, which are groups of patients with defined similarities and are used as comparison subjects in medical research, in order to efficiently extract appropriate information for various purposes in a medical information system that holds a huge amount of data such as patient information and clinical information.

[0003] Special table 2018-535488 publication

[0004] Testing patients is one of the essential tasks in hospitals and other facilities. Therefore, evaluating and improving the efficiency of testing significantly contributes to improving the overall operations of the facility. To evaluate and improve the efficiency of clinical testing, it is necessary to evaluate tests based on patient characteristics and trends in test value, i.e., which tests are of high or low value when performed on which patients. Evaluating the test value of tests not only improves testing efficiency but also improves operations. This is because the evaluation of test value can be used in a wide range of situations, such as checking the validity of test orders and test results by laboratory technicians, and comparing test value due to differences in test measurement methods and outsourced testing centers.

[0005] The aforementioned Patent Document 1 describes extracting patient attributes from clinical information, predicting one specific attribute using other attributes, and obtaining a pattern for generating a patient cohort, but does not take into consideration evaluation focusing on the value of the test.

[0006] Furthermore, because tests, such as clinical tests, play an important role in the treatment of patients, there is a need to quantitatively evaluate the value of clinical tests, in other words, how useful they are in the treatment of patients.

[0007] An object of the present disclosure is to provide an information processing system and an information processing method that can reduce the workload within a facility.

[0008] A representative embodiment of the present disclosure has the following configuration. An information processing system of one embodiment evaluates the value of each of a plurality of test items. The information processing system includes an information acquisition unit that acquires patient information on each of a plurality of patients who are the subject of the test and test value information on the effects obtained by administering the test for each of the test items to each of the plurality of patients, a classification unit that classifies the plurality of patients into a plurality of groups based on the patient information and the test value information acquired by the information acquisition unit, and a representative value calculation unit that calculates, for each group classified by the classification unit, a representative value that is an index value statistically determined from the plurality of pieces of test value information.

[0009] An information processing method according to one embodiment evaluates the value of a plurality of test items by acquiring patient information on each of a plurality of patients who are the subject of the test and test value information on the effect obtained by administering the test to each of the plurality of patients for each of the test items, classifying the plurality of patients into a plurality of groups based on the acquired patient information and test value information, and calculating a representative value for each group, which is an index value statistically determined from the plurality of pieces of test value information.

[0010] According to a representative embodiment of the present disclosure, it is possible to provide a technology for improving the efficiency of operations in facilities such as hospitals. Problems, configurations, and effects other than those described above will be described in the description of the preferred embodiment.

[0011] FIG. 1 is a diagram showing an example of a schematic configuration of an information processing system according to a first embodiment. FIG. 2 is a diagram showing an example of a functional block configuration of the information processing system according to the first embodiment. FIG. 3 is a flowchart showing an example of a classification process in which a classification unit according to the first embodiment classifies patient information. FIG. 4 is a diagram showing an example of a first display screen for inputting extraction conditions according to the first embodiment. FIG. 5 is a diagram showing an example of a second display screen for displaying extraction results according to the first embodiment. FIG. 6 is a diagram showing an example of a third display screen for inputting extraction conditions according to the first embodiment. FIG. 7 is a diagram showing an example of a fourth display screen for displaying extraction results according to the first embodiment. FIG. 8 is a diagram showing an example of the configuration inside a medical facility according to a modified example of the first embodiment. FIG. 9 is a diagram showing an example of a functional block configuration of an information processing system according to a second embodiment. FIG. 10 is a diagram showing an example of a fifth display screen of an output unit according to the second embodiment. FIG. 11 is a diagram showing an example of a sixth display screen of an output unit according to the second embodiment.

[0012] Hereinafter, embodiments of the present disclosure will be described in detail with reference to the drawings. In the drawings, the same parts are generally designated by the same reference numerals, and repeated explanations will be omitted. In the drawings, the representation of components may not represent their actual positions, sizes, shapes, ranges, etc., in order to facilitate understanding of the invention.

[0013] For the purpose of explanation, when describing processing by a program, the program, function, processing unit, etc. may be described as the main entity, but the main hardware entity in these cases is a processor, or a controller, device, computer system, system, etc. configured with the processor. A computer system executes processing according to a program read into memory using resources such as memory and communication interfaces as appropriate through the processor. This realizes predetermined functions, processing units, etc. The processor is configured, for example, with semiconductor devices such as a CPU / MPU or GPU. Processing is not limited to software program processing, and can also be implemented using dedicated circuits. Dedicated circuits such as FPGAs, ASICs, and CPLDs can be used.

[0014] The program may be pre-installed as data on the target computer system, or may be distributed as data to the target computer system from a program source. The program source may be a program distribution server on a communication network, or a non-transitory computer-readable storage medium, such as a memory card or a disk. The program may be composed of multiple modules. The computer system may be composed of multiple devices. The computer system may be composed of a client-server system, a cloud computing system, an IoT system, etc. Various data and information may be composed of structures such as, for example, tables and lists, but are not limited to these. Expressions such as identification information, identifiers, IDs, names, and numbers are interchangeable.

[0015] Hereinafter, embodiments will be described with reference to the drawings.

[0016] <First embodiment> In the first embodiment, as an example, an information processing system will be described that can classify patients under predetermined conditions, evaluate the value and efficiency of test items for each group of classified patients, and output test items that recommend operational improvements based on the evaluation results.

[0017] 1 is a diagram showing an example of a schematic configuration of an information processing system 10. The configuration of the information processing system 10 is common to the configuration of an information processing system 11 described in the first embodiment and the second embodiment described later.

[0018] As shown in FIG. 1 , the information processing system 10 is applied to an environment including, for example, medical facilities 100a, 100b, and 100c, and a provider 113. The medical facilities 100a to 100c perform testing, such as specimen testing, on patients as part of their business. The provider 113 is a service provider that processes information received from the medical facilities 100a to 100c. The provider 113 is connected to intra-facility networks 108a to 108c within the medical facilities 100a to 100c via an extra-facility network 112. In this embodiment, the provider 113 is provided outside the medical facilities 100a to 100c and is shared by the medical facilities 100a to 100c.

[0019] The medical facility 100a includes an information processing device 101a, an external storage device 109a, and a diagnostic analysis device 111a, which are communicably connected to each other via an in-facility network 108a within the medical facility 100a.

[0020] The information processing device 101a is, for example, a computer system such as a personal computer, a tablet terminal, etc. Details of the information processing device 101a will be described later.

[0021] The diagnostic analyzer 111a is a device that can be used to perform tests on patients, in this embodiment, clinical tests. For example, the diagnostic analyzer 111a is an automated analyzer that analyzes samples collected from patients, such as blood or urine. The diagnostic analyzer 111a may also be other analyzers. Furthermore, the diagnostic analyzer 111a may include multiple analyzers or multiple types of analyzers.

[0022] The external storage device 109a includes a medical information server 110a, which collects and stores various information (described below) related to patients, including, for example, information on test results of samples obtained by the diagnostic analyzer 111a.

[0023] The medical facility 100b includes an information processing device 101b, an external storage device 109b, and a diagnostic analysis device 111b. The information processing device 101b, the external storage device 109b, and the diagnostic analysis device 111b are communicatively connected via an in-facility network 108b within the medical facility 100b. The medical facility 100c includes an information processing device 101c, an external storage device 109c, and a diagnostic analysis device 111c. The information processing device 101c, the external storage device 109c, and the diagnostic analysis device 111c are communicatively connected via an in-facility network 108c within the medical facility 100c. The information processing devices 101b and 101c, the external storage devices 109b and 109c, and the diagnostic analysis devices 111b and 111c are similar to the information processing device 101a, the external storage device 109a, and the diagnostic analysis device 111a, respectively, and therefore detailed description thereof will be omitted.

[0024] The provider 113 receives information stored in the information processing devices 101a to 101c, external storage devices 109a to 109c, etc. included in the medical facilities 100a to 100c via the in-facility networks 108a to 108c and the out-facility network 112, and processes the received information.

[0025] Next, the information processing device 101a will be described. The information processing devices 101b and 101c will be described in a similar manner, so only the information processing device 101a will be described and descriptions of the information processing devices 101b and 101c will be omitted.

[0026] The information processing device 101a includes an arithmetic unit 102, a main memory device 103, a communication unit 104, an input unit 105, an output unit 106, and an auxiliary memory device 107. The arithmetic unit 102 is communicably connected to each of the main memory device 103, the communication unit 104, the input unit 105, the output unit 106, and the auxiliary memory device 107.

[0027] The arithmetic unit 102 is a device that executes a program loaded into the main memory device 103. The arithmetic unit 102 is, for example, a processor such as a CPU.

[0028] The main memory device 103 is a device that stores programs executed by the arithmetic device 102, information to be processed, and information including processing results. The main memory device 103 is, for example, a hard disk drive (HDD) or a solid state drive (SSD).

[0029] The communication unit 104 is a device that transmits and receives data to and from external devices via a communication network. The communication unit 104 is, for example, a network interface. The communication unit 104 receives information stored in the external storage device 109a via, for example, the in-facility network 108a.

[0030] The input unit 105 is a device that allows a user to input instructions to the information processing device 101a. The input unit 105 is, for example, a keyboard, a mouse, a touch panel, etc. The output unit 106 is a device that displays information to the user. The output unit 106 is, for example, a display, a printer, etc.

[0031] The auxiliary storage device 107 is a device that stores various programs for evaluating the value of test items for each patient group in the information processing system 10.

[0032] <Example of Functional Configuration of Information Processing System> Fig. 2 is a diagram showing an example of the functional block configuration of the information processing system 10. The information processing system 10 has, as its functions, an information acquisition unit 201, a classification unit 202, and a calculation unit 203. The calculation unit 203 includes an inspection value representative value calculation unit 204, an inspection implementation rate calculation unit 205, an improvement inspection candidate calculation unit 206, and an estimated loss calculation unit 207. In Fig. 2, the input unit 105 and the output unit 106 are also shown.

[0033] 2 is realized by the arithmetic device 102 executing a program stored in the auxiliary storage device 107. This processing is realized in cooperation with other hardware. The program may be embedded in the auxiliary storage device 107 or the main storage device 103. Alternatively, the program may be provided as an installable or executable file by downloading it from an external server or by recording it on a recording medium such as a CD-ROM that can be read by the information processing device 101a.

[0034] The input information 208 is stored in the medical information server 110a. The input information 208 includes electronic medical record information 209, test order information 210, medical receipt information 211, in-hospital information 212, guideline information 213, test value information 216, and operation information 214 input from the input unit 105.

[0035] The electronic medical record information 209 is information relating to the progress of medical treatment given to a patient. By referring to this electronic medical record information 209, a doctor can grasp all information available from the patient at the time of reference. Information contained in the electronic medical record information 209 is information for grasping the patient's condition, such as medical records, interview forms, prescriptions, surgery records, nursing records, and hospitalization treatment plans. The electronic medical record information 209 includes information created by the medical facility 101a, health care organizations, and individual patients.

[0036] The test order information 210 includes order information related to the order issued by the doctor when the test order was issued, and test implementation information by the tester in the testing department who will perform the test. The order information includes, for example, information indicating the date and time the order was issued, order issuer information (information indicating the department and doctor), and order content information indicating the order content (test items). The test implementation information is information related to the test implementation and result reporting. The test implementation information includes, for example, information indicating the date and time the test was implemented, test result information (information indicating the test result value, abnormal value category, result comment, error, or cancellation), and information indicating the date and time the test result was reported. Note that the order information and test implementation information may each include other information.

[0037] The medical receipt information 211 is information about medical treatment covered by insurance received by patients enrolled in insurance such as national health insurance and social insurance. The medical receipt information 211 includes, for example, personal information about the patient, the medical department visited, the diagnosed illness, information about treatments such as surgery, examinations, and rehabilitation, and medical fee information 223 paid to the medical facility 101a for the treatment. The medical fee information 223 may be, for example, information indicating points. Note that the medical receipt information 211 may also include other information.

[0038] The in-hospital information 212 is information related to the operation of the medical facility 101a. The in-hospital information 212 includes, for example, work status information indicating the work status of medical staff, cost information indicating the cost of each medical procedure (information indicating labor costs, equipment costs, and material costs), and clinical indicator information indicating clinical indicators such as the number of outpatients and inpatients and the average length of stay. Note that the in-hospital information 212 may also include other information.

[0039] The guideline information 213 includes information indicating guidelines that doctors and other medical professionals refer to when providing medical care. Here, the guidelines include various guidelines such as medical care guidelines proposed by organizations such as academic societies, facility rules and facility guidelines of each facility, etc.

[0040] The test value information 216 is information that indicates an index related to the effect obtained by performing a test on a patient. The test value information 216 varies for each test item based on information about the patient at the time of the test. Even when tests of the same test item are performed on the same patient, if the test is performed at different times and the information about the patient is different, the test value information 216 will indicate different values. The test value information 216 is calculated, for example, based on test result information indicating the test results each time a test is performed on a patient and on patient information 215, and is acquired by the medical information server 110a. An example of the process for calculating the test value information 216 will be described in a modified example of the information processing system 10, which will be described later.

[0041] The operation information 214 is information related to operations including switching the display on the screen of the output unit 106 and changing the display content. The operation information 214 is information input by operating the input unit 105 by the user of the information processing device 101a.

[0042] The information acquisition unit 201 acquires at least patient information 215 on each of a plurality of patients who are the subjects of a test, for example, a clinical test, and test value information 216 on the effects obtained by performing the test for each test item on each of the plurality of patients. The information acquisition unit 201 also acquires medical fee information 223 indicating the fee for each of the plurality of test items, and test cost information 224 indicating the test costs incurred by performing each of the plurality of test items. The medical fee information 223 is acquired, for example, from medical receipt information 211. The test cost information 224 is acquired, for example, from in-hospital information 212.

[0043] The information acquisition unit 201 extracts information necessary for processing from, for example, input information 208. The information acquisition unit 201 analyzes text data contained in electronic medical record information 209, guideline information 213, etc. in the medical information server 110a, breaks it down into category data and numerical data, and extracts necessary information. In this embodiment, patient information 215 and examination value information 216 are extracted. The patient information 215 and examination value information 216 are output to the classification unit 202. An improvement threshold 221, medical fee information 223, and examination cost information 224, which will be described later, are output to the calculation unit 203.

[0044] The patient information 215 is information about the patient who is the subject of the examination. The patient information 215 is a collective term for all information about the patient obtained by the medical facility 100a. The patient information 215 includes, for example, age, sex, chief complaint, findings, symptoms, medical history, family history, examination items performed on the patient, treatment history, medication information, various test results, and other information about medical procedures.

[0045] The classification unit 202 classifies a plurality of patients into a plurality of groups based on the patient information 215 and the test value information 216 acquired by the information acquisition unit 201 .

[0046] The classification unit 202 classifies multiple patients into multiple groups under predetermined conditions based on, for example, patient information 215 and testing value information 216 extracted by the information acquisition unit 201, and calculates patient classification information 217 indicating optimal classification conditions. Here, optimal classification conditions refer to convergence of classification. The classification process of the classification unit 202 will be described in detail later with reference to FIG. 3. The patient classification information 217 is output to the calculation unit 203 and the output unit 106.

[0047] The calculation unit 203 includes an inspection value representative value calculation unit 204, an inspection implementation rate calculation unit 205, an improvement inspection candidate calculation unit 206, and an estimated loss calculation unit 207. The inspection value representative value calculation unit 204 calculates an inspection value representative value 218. The inspection implementation rate calculation unit 205 calculates an inspection implementation rate 219. The improvement inspection candidate calculation unit 206 calculates an improvement inspection candidate 222. The estimated loss calculation unit 207 calculates an estimated loss 220. The calculated inspection value representative value 218, inspection implementation rate 219, improvement inspection candidate 222, and estimated loss 220 are output to the output unit 106.

[0048] The inspection value representative value calculation unit 204 calculates a representative value (hereinafter referred to as the inspection value representative value 218) which is an index value statistically obtained from multiple pieces of inspection value information 216 for each group classified by the classification unit 202.

[0049] The inspection value representative value calculation unit 204 calculates, for example, a representative value, which is an index value statistically obtained from the inspection value information 216, as the inspection value representative value 218 for each group classified by the classification unit 202. As described above, the inspection value information 216 is calculated for each patient information 215 at the time of testing. Therefore, the inspection value information 216 varies in value even for patients belonging to the same group. When the values ​​vary, it is difficult for the calculation device 102 to interpret the inspection value information 216. Similarly, when the values ​​vary, visibility on the screen is poor even when a user checks the output results on the screen of the output unit 106. For this reason, it is desirable to perform a process of calculating the inspection value representative value 218 from the inspection value information 216. Here, for example, if the inspection value information 216 is expressed as a score, the mean value, median, or mode can be used as the inspection value representative value 218. Alternatively, if the inspection value information 216 is expressed as an ordinal scale such as a five-point scale, the median or mode can be used. The settings for calculating the inspection value representative value 218 may be set in advance by the user operating the input unit 105. In this way, the settings for the inspection value representative value 218 can be flexibly selected.

[0050] The test implementation rate calculation unit 205 calculates a test implementation rate 219 indicating the rate at which each test item is implemented for each group classified by the classification unit 202 .

[0051] The improvement inspection candidate calculation unit 206 calculates the inspection efficiency for each inspection item in the group classified by the classification unit 202 based on the inspection implementation rate 219 calculated by the inspection implementation rate calculation unit 205 and the inspection value representative value calculation unit 204, and calculates improvement inspection candidates 222 for the inspection items in the group based on the calculated inspection efficiency and an improvement threshold 221 that defines the improvement efficiency. The improvement inspection candidate calculation unit 206 may also calculate the improvement inspection candidates 222 based on the inspection value representative value 218, the inspection implementation rate 219, and an estimated loss 220 calculated by the estimated loss calculation unit 207, which will be described later.

[0052] The improvement inspection candidate calculation unit 206, for example, evaluates the inspection efficiency for each group classified by the classification unit 202 based on the inspection value representative value 218, the inspection implementation rate 219, and the estimated loss 220, and calculates the improvement inspection candidate 222 by extracting the inspections that are determined to be less efficient than the improvement threshold 221 as the improvement inspection candidate 222.

[0053] The improvement inspection candidate 222 is an inspection item that is recommended for improvement in terms of the inspection implementation rate. When an inspection item that has become an improvement inspection candidate 222 is displayed on the output unit 106, it is highlighted. The highlighted display of the improvement inspection candidate 222 includes, for example, a background highlight, the display of a mark indicating a caution or warning, and text information encouraging an improvement in the inspection implementation rate. In this embodiment, the highlighted display of the improvement inspection candidate 222 is displayed on the output unit 106 as an improvement inspection candidate display 409, which will be described later.

[0054] The improvement threshold 221 includes information on the upper and lower limits of the inspection value representative value 218 and the inspection implementation rate 219, as well as the allowable value of the estimated loss 220. The improvement threshold 221 can be set by the user operating the input unit 105. The inspection value representative value 218 and the inspection implementation rate 219 are essential elements in the processing of the improvement inspection candidate calculation unit 206. Therefore, if the inspection value representative value 218 and the inspection implementation rate 219 are not set, any default values ​​set in advance are used.

[0055] The improvement inspection candidate calculation unit 206 targets inspection items that are over-inspected or under-inspected. For example, when extracting inspection items using an improvement threshold 221 of the inspection value representative value 218 and the inspection implementation rate 219, the improvement inspection candidate calculation unit 206 performs the following processing. The improvement inspection candidate calculation unit 206 extracts as over-inspection inspections those inspections for which the inspection value representative value 218 is below the lower limit and the inspection implementation rate 219 is above the upper limit of the improvement threshold 221. The improvement inspection candidate calculation unit 206 also extracts as under-inspection inspections those inspections for which the inspection value representative value 218 is above the upper limit and the inspection implementation rate 219 is below the lower limit. The improvement inspection candidate calculation unit 206 outputs the inspection items calculated in this manner to the output unit 106 as improvement inspection candidates 222.

[0056] The estimated loss calculation unit 207 calculates an estimated loss 220 related to the cost of testing the test item estimated by performing the test on the test item based on the test implementation rate 219, the test value representative value 218, medical fee information 223, and test cost information 224.

[0057] The medical fee information 223 is information indicating the fee (amount) obtained from providing medical care. The medical fee information 223 includes information on the fee obtained by performing tests for each test item. The test cost information 224 is information including information related to costs incurred when performing tests for each test item, such as actual costs such as reagent costs, equipment costs, system costs, and labor costs, workload such as working hours, and patient burden including invasiveness such as blood sampling volume and risk of side effects. Here, the estimated loss 220 includes business losses at the medical facility 100a associated with testing for each test item, loss of human resources due to workload such as working hours, and burden on patients due to invasiveness and / or risk of side effects.

[0058] In the case of overtesting (a test for which the testing value information 216 is low and the testing implementation rate 219 is high), the estimated loss 220 indicates the difference between the current situation and the case where the test is not performed. Furthermore, in the case of undertesting (a test for which the testing value information 216 is high and the testing implementation rate 219 is low), the estimated loss 220 indicates the difference between the current situation and the case where the test is performed. For example, with regard to business losses, the estimated loss calculation unit 207 calculates the testing margin, which is the medical fee information 223, which is the income associated with performing the test, minus the actual costs included in the testing cost information 224, for both the case where the test candidate for improvement 222 is improved and the current situation, and outputs the difference between the two as the estimated loss 220. In the case of undertesting, the estimated loss calculation unit 207 calculates the difference between the testing margin if the testing implementation rate 219 is increased to 100% and the current testing margin as the estimated loss 220. For excessive testing, the estimated loss calculation unit 207 calculates the difference between the current testing margin and the testing margin that would result if the testing implementation rate 219 were reduced to 0%, as the estimated loss 220. Medical procedures, including testing, are not entirely fee-for-service, but rather have set medical fee calculation conditions. For this reason, reducing testing often results in financial benefits within the medical facility 100a. For this reason, by having the information processing system 10 estimate the current losses from excessive or insufficient testing and outputting the estimated losses to the output unit 106, the user can select tests to be improved from the candidate test for improvement 222, taking into account the financial effect of improving operational efficiency.

[0059] For example, when using an inspection value representative value 218 and an improvement threshold 221 for the estimated loss 220, the improvement inspection candidate calculation unit 206 calculates, from among the inspection value representative values ​​218 with low values, inspection items that meet the improvement threshold 221, such as inspections that increase inspection profit margins by 100,000 yen or more per month or inspections that reduce work time by four hours or more per month, as improvement inspection candidates 222. This allows the calculation unit 203 to quantitatively calculate different improvement effects for each objective in improving the operational efficiency of inspections and output the calculated results to the output unit 106. Therefore, the user can select the improvement inspection candidate 222 for an inspection item that matches the objective as an improvement candidate. The estimated loss calculation unit 207 may calculate the business loss, workload, and patient workload as the estimated loss 220. The business loss, workload, and patient workload may be calculated using real values ​​such as monetary value, work time, and blood collection volume, or categorical values ​​such as a three-level display of large, medium, and small, and output to the output unit 106.

[0060] The output unit 106 outputs the inspection value representative value 218 calculated by the inspection value representative value calculation unit 204. The output unit 106 also highlights and outputs the improvement inspection candidate display 409 of the improvement inspection candidate 222 calculated by the improvement inspection candidate calculation unit 206. This allows the user to visually recognize the inspection value representative value 218 and the improvement inspection candidate display 409 for each inspection item.

[0061] The output unit 106 outputs, for example, patient classification information 217, a test value representative value 218, a test implementation rate 219, an estimated loss 220, and improvement test candidates 222 to a display in a predetermined display format. By receiving operation information 214 from the input unit 105 via the information acquisition unit 201, the output unit 106 is able to update the screen by changing screen transitions and display conditions. Details of specific display screen examples of the output unit 106 (FIGS. 4 to 7, which will be described later) will be described later.

[0062] 3 is a flowchart showing an example of the classification process in which the classification unit 202 classifies the patient information 215. In the following description, the classification unit 202 is the subject of operations in each step, but the classification unit 202 loads a program into the main storage device 103 and executes it on the arithmetic unit 102, so the arithmetic unit 102 may also be the subject of operations. Furthermore, in the following description, processing is performed using a test for differences between two groups, which is a traditional statistical method in the medical field and is often used in, for example, evaluating the effectiveness of pharmaceuticals, but other data analysis methods such as clustering, linear analysis, and logistic regression may also be used.

[0063] (Step S1 ) The classification unit 202 receives the patient information 215 and the examination value information 216 from the information acquisition unit 201 .

[0064] (Step S2) The classification unit 202 performs preprocessing such as converting the data format of the patient information 215 received in step S1 so that the subsequent classification process can be performed. As preprocessing, the classification unit 202 converts, for example, items expressed as continuous values, such as age and test results, included in the patient information 215, into categorical values. The conversion method may be any method, such as assigning equal divisions, such as percentiles like quartiles or dividing values ​​into groups of 10, or assigning values ​​based on medical evidence, such as BMI, obese, normal, or thin.

[0065] (Step S3) The classification unit 202 counts the frequency of occurrence of values ​​included in each item of the patient information 215 that has been preprocessed in step S2. Note that missing values, in which no value is entered in an item, and information with unknown details are also counted as information that represents the patient's condition.

[0066] (Step S4) The classification unit 202 divides the patient information 215 into a relevant group and a non-relevant group using the mode based on the result of counting the occurrence frequencies in step S3. The items and item values ​​that are the conditions for dividing the patient information 215 may be separately specified by the user using the input unit 105.

[0067] (Step S5) The classification unit 202 determines whether the number of cases in each of the relevant group and the non-relevant group divided in step S4 is equal to or greater than a lower limit. If the number of cases in both the relevant group and the non-relevant group is equal to or greater than the lower limit, the process proceeds to step S6. If the number of cases in either the relevant group or the non-relevant group is less than the lower limit, the process proceeds to step S8. Here, the value of the lower limit is an actual number, a ratio to the total number, or the like. The value of the lower limit can be set arbitrarily.

[0068] (Step S6) The classification unit 202 tests the difference between the two groups for the testing value information 216 corresponding to the patient information 215 divided into a relevant group and a non-relevant group in step S4, and determines whether there is a significant difference. Here, the test for significant difference between the two groups is performed using a nonparametric test, such as the Wilcoxon rank sum test. Furthermore, when determining significant differences in the testing value information 216 for multiple test items, in this embodiment, the classification unit 202 tests the difference between the two groups in the testing value information 216 for each test item, and if there is a significant difference in even one test item, it determines that there is a significant difference in the testing value information 216 between the two groups. If it is determined that there is a significant difference, the process proceeds to step S7. If it is determined that there is no significant difference, or that there is no significant difference in all test items, the process proceeds to step S8.

[0069] (Step S7) The classification unit 202 classifies the patient information 215 of the relevant group and the non-relevant group determined in step S6 to have a significant difference in the testing value information 216 into separate patient information 215. The processing from step S3 onwards described above is executed on the information thus classified as separate patient information 215. In other words, recursive processing is executed on each piece of information classified as separate patient information 215.

[0070] (Step S8) Based on the tabulation results of step S3, the classification unit 202 determines whether the frequency of occurrence of the item value next most frequent after the mode (second most frequent value) is equal to or greater than a lower limit. Here, the value of the lower limit can be set arbitrarily, as in the case of step S5 described above. Note that if there are multiple conditions (items and item values) separately specified in step S4 described above, the classification unit 202 uses the item value that meets the next specified condition instead of the second most frequent value. If it is determined to be equal to or greater than the lower limit, the process proceeds to step S9. If it is determined to be less than the lower limit, the process proceeds to step S10.

[0071] (Step S9) The classification unit 202 divides the patient information 215 into a relevant group and a non-relevant group based on the second most frequent value in step S8 or a condition separately specified in step S8. The processes from step S5 onward described above are executed on the divided patient information 215. In other words, recursive processing is executed on the divided patient information 215.

[0072] (Step S10) The classification unit 202 outputs the converged classification conditions, in other words, the optimal classification conditions, as patient classification information 217 to the calculation unit 203 and the output unit 106 through the processing of steps S1 to S9. The patient classification information 217 is displayed on the output unit 106, for example, as shown in a second display screen example 405 in FIG. 5 (described later). The patient classification information 217 may also be stored in the main storage device 103.

[0073] <Display Screen Examples of Output Unit> FIGS. 4, 5, 6, and 7 are diagrams showing display screen examples of the output unit 106. FIG. 4 shows a first display screen example 401 for inputting extraction conditions. FIG. 5 shows a second display screen example 405 for displaying extraction results. FIG. 6 shows a third display screen example 401a for inputting extraction conditions. FIG. 7 shows a fourth display screen example 501 for displaying detailed inspection value information. The first display screen example 401 and the second display screen example 405, as well as the third display screen example 401a and the fourth display screen example 501, may be displayed on the same screen. Hereinafter, the output by the output unit 106 will be described assuming that information is displayed as in the first display screen example 401, the second display screen example 405, the third display screen example 401a, and the fourth display screen example 501. However, this is not limited thereto. The information displayed on each display screen may be printed on a paper medium or stored as data in a predetermined storage device, such as the main storage device 103.

[0074] 4, a first example display screen 401 has an update button 402, an improvement threshold setting section 403, and a patient information setting section 404. The improvement threshold setting section 403 allows the user to set values ​​for determining overtesting and undertesting for each of the three items: the testing value representative value 218, the testing implementation rate 219, and the estimated loss 220.

[0075] The patient information setting section 404 sets conditions for extracting patient information 215. The patient information setting section 404 has a period 404a, admission / exit category 404b, medical department 404c, diagnosed illness name 404d, age 404e, and gender 404f. The period 404a sets the first day and last day of the period. The admission / exit category 404b sets whether the patient is hospitalized or outpatient. The medical department 404c sets the department that provided the medical care. The diagnosed illness name 404d sets the diagnosed illness name. The age 404e sets the age range. The gender 404f sets the gender.

[0076] For example, in Figure 4, data with inspection dates falling within the period from January 1, 20XX to December 31, 20XX is set to be extracted. Also, inspection items with an inspection value representative value 218 of less than 30 points and an inspection implementation rate 219 of 50% or more are set to be determined as over-inspection. Inspection items with an inspection value representative value 218 of 90 points or more and an inspection implementation rate 219 of less than 50% are set to be determined as under-inspection. Note that Figure 4 shows a case in which an improvement threshold value 221 (tolerance value) for the estimated loss 220 is not set.

[0077] After setting conditions in the improvement threshold setting section 403 and the patient information setting section 404, when the user presses the update button 402, the above-described processing is executed and the extraction results shown in Figure 5 are output to the output section 106.

[0078] As shown in FIG. 5 , the second display screen example 405 displays information processed under the conditions set in the first display screen example 401. The second display screen example 405 displays, for example, the number of relevant data 406, category items, and category item values. The category items each display the item name used to classify the patient. The category items are, for example, admission / admission category 407a, medical departments 407b1 and 407b2, diagnosed disease names 407c1 and 407c2, age 407d, and others 407e. The admission / admission category 407a, medical departments 407b1 and 407b2, diagnosed disease names 407c1 and 407c2, and age 407d each display category value 408a to 408d. The category item value for others 407e is not shown in the figure.

[0079] The number of relevant data 406 displays information that allows for understanding the approximate numbers of extracted results, such as the number of test orders and the number of patients. In FIG. 5, the number of test orders is 312,227, and the number of patients is 14,665.

[0080] For example, the classification item value 408a indicates "outpatient" as the value of the admission / exit category 407a. Therefore, the user can see that the outpatient examination value information 216 is significantly different from the non-outpatient (inpatient) examination value information 216. The number of corresponding test orders is 52,297, and the number of patients is 6,887. Each classification item, such as the admission / exit category 407a, has a link attached. For example, the user can transition the screen display from the second display screen example 405 to a fourth display screen example 501 (see FIG. 7 ) for checking details of the examination value information 216 by operating the input unit 105 to click on each link.

[0081] The improvement test candidate display 409 is displayed as an alert mark within the display of, for example, the admission / discharge category 407a, the medical departments 407b1 and 407b2, the diagnosed disease names 407c1 and 407c2, and the age 407d. In this embodiment, the improvement test candidate display 409 is described as a triangular display including an exclamation mark. The improvement test candidate display 409 is not limited to this and may be any display that is recognized by the user as an alert.

[0082] 5, the diagnostic disease name 407c1 is displayed with an improvement test candidate display 409. That is, it is shown that the diagnostic disease name 407c1 of the group classified from the patient information 215 and the test value information 216 includes test items that meet the conditions specified as the improvement threshold 221. As for specific test items and test value information 216, as described above, when the user clicks on the link of the diagnostic disease name 407c1 using the input unit 105, the screen display transitions from the second display screen example 405 to a display screen example for confirming details (for example, a fourth display screen example 501 in FIG. 7 described later).

[0083] Instead of the display of the extraction results in the second display screen example 405 shown in FIG. 5 , the display may be limited to test items including the improvement test candidate display 409, and the limited test items may be displayed in a list format. Also, while FIG. 5 shows the extraction results for patients who meet the conditions set in the patient information setting section 404 as an example, the present invention is not limited to this. A specific patient may also be specified in the patient information setting section 404. In this case, the patient information setting section 404 may be provided with a setting section for specifying a specific patient. For example, the setting section may be configured to allow specification of the patient's ID and / or patient's name. The output unit 106 then highlights the classification item 407 and / or the value of the classification item 407 corresponding to the specified specific patient in the second display screen example 405. For example, the user may operate the input unit 105 to click the highlighted classification item 407, thereby displaying the patient information 215 of the specified patient on the output unit 106. This allows the user to visually check the patient information 215 of the specified patient and understand the basis for the value of the patient's examination value information 216. This makes it possible to broaden the applications of the information processing system 10.

[0084] The third display screen example 401a shown in FIG. 6 is similar to the first display screen example 401, but the conditions set in the patient information setting section 404 are different. For example, in FIG. 6, data whose examination dates fall within the period from January 1, 20XX, to December 31, 20XX, is set to be extracted, as in FIG. 4. Meanwhile, in FIG. 6, the admission / exit category 404b is set to outpatient, the medical department 404c is set to medical department A, and the diagnosed disease name 404d is set to disease A. Note that in the third display screen example 401a, test items whose test value representative value 218 is less than 30 points and whose test implementation rate 219 is 50% or more are set to be determined as overtesting. Test items whose test value representative value 218 is 90 points or more and whose test implementation rate 219 is less than 50% are set to be determined as undertesting. Regarding the estimated loss 220, a case in which the improvement threshold 221 (tolerance value) for the estimated loss 220 is not specified is shown. These are the same as in FIG.

[0085] After setting conditions in the improvement threshold setting section 403 and the patient information setting section 404, when the user presses the update button 402, the above-mentioned processing is executed, and a display similar to that shown in FIG. 6 is displayed on the output section 106. Then, when the user clicks on the improvement test candidate display 409 displayed for one of the classification item values ​​408a to 408d, the extraction result shown in FIG. 7 is output to the output section 106.

[0086] 7, a fourth display screen example 501 is a display example of detailed inspection value information. The fourth display screen example 501 displays an inspection item display section 502, an inspection value representative value display section 503, an inspection implementation rate display section 504, an estimated loss display section 505, and an improvement inspection candidate display section 506.

[0087] The inspection item display section 502 displays the names of inspection items included in the classified group. The inspection item names displayed in the inspection item display section 502 may be any information that can identify the inspection item, such as an inspection item code. The inspection value representative value display section 503, inspection implementation rate display section 504, estimated loss display section 505, and improvement inspection candidate display section 506 respectively display the inspection value representative value 218, inspection implementation rate 219, estimated loss 220, and improvement inspection candidate display 409 linked to the inspection item displayed in the inspection item display section 502.

[0088] For example, in the fourth display screen example 501, the improvement examination candidate display 409 is not displayed for tests A, B, and C. On the other hand, in the fourth display screen example 501, the improvement examination candidate display 409 is displayed for test D. More specifically, for test D, the estimated loss display section 505 indicates that the estimated loss 220 is 28 points in the test value representative value display section 503, 75% in the test implementation rate display section 504, an annual business loss of 560,000 yen in the estimated loss display section 505, a monthly workload of 3 hours, and a level 1 (slight) patient workload. Therefore, for test D, the improvement examination candidate display 409 indicating that test D corresponds to the improvement examination candidate display section 506 is displayed together with a message "Possible overtesting" indicating that improvement of the test is recommended. By checking the information of the test corresponding to the improvement examination candidate display 409 on the fourth display screen example 501, the user can identify the test that needs improvement and confirm the loss of performing the test, which can lead to improvements in the testing operations.

[0089] As described above, the information processing system 10 can assess the value of a test by grasping the patient characteristics and the trend of the test value information 216 for each group classified by the classification unit 202 from the value of each individual test item (test value information 216) calculated each time a test is performed on a patient. Therefore, the information processing system 10 can quantitatively assess the value of a test for each group of patients with common characteristics. Furthermore, by using the information processing system 10, facilities such as hospitals can improve the efficiency of operations within the medical facilities 100a to 100c, for example, by avoiding performing tests with low test value or by avoiding performing tests that are being performed excessively.

[0090] <Modification> Next, a modification of the first embodiment will be described. Fig. 8 is a diagram showing an example of a modification of the configuration within the medical facility 100a. In the information processing system 10 of the modification, an inspection value information calculation system 120 is added to the medical facility 100a. The inspection value information calculation system 120 is connected to an intra-facility network 108a. The inspection value information calculation system 120 is configured to be able to communicate with the information processing device 101a, the external storage device 109a, and the diagnostic analysis device 111a, respectively, via the intra-facility network 108a. Although not shown in the figure, inspection value information calculation systems are also added to the medical facilities 100b and 100c in a similar manner.

[0091] The examination value information calculation system 120 calculates the examination value information 216. The examination value information 216 is calculated every time an examination is performed on a patient. The calculated examination value information 216 is output to the medical information server 110a.

[0092] The test value information calculation system 120 has a learning unit 121 and a calculation unit 122. The learning unit 121 receives patient information 215 and test result information relating to test results obtained by administering clinical tests to a patient for test items, and uses a data set that outputs test value information 216 to learn a model used to calculate the value of a test item.

[0093] The learning unit 121 executes the following process, for example, each time an examination is performed. The learning unit 121 integrates the patient information 215 and extracts feature quantities of the patient information 215. Specifically, the learning unit 121 converts the patient information 215 received after an examination into text and into digital form so that it can be processed by a neural network (integration of patient information), and calculates feature quantities of the numerical information by applying the integrated patient information 215 to a neural network (e.g., deep learning).

[0094] Next, the learning unit 121 aggregates multiple test results for each test item from the test result information and estimates a probability distribution (function) for each test item using a probability distribution model. The learning unit 121 restores the test results based on the estimated probability distribution. Since the test results as the correct values ​​are known, this is a process of confirming whether the correct values ​​can be obtained from the estimated probability distribution.

[0095] Next, the learning unit 121 estimates the inspection value from the restored inspection result. If the original inspection result can be restored from the estimated probability distribution, the estimated probability distribution is deemed to have been correctly estimated. Next, the learning unit 121 estimates the learning error in the estimated inspection value. Here, the learning error is the error between the original inspection result and the restored inspection result.

[0096] Next, the learning unit 121 determines whether the value of the estimated learning error has converged. Whether or not the value has converged is determined by whether or not the value is smaller than a preset threshold. The learning unit 121 sets the learning parameters to which the learning error has converged in the learned model. Here, the learning parameters include the above-mentioned neural network parameters, parameters used in probability distribution estimation, etc. The learning unit 121 updates the learning parameters (e.g., neural network parameters) in accordance with an optimization function for updating so as to reduce the learning error. If the learning error is small, it means that a model capable of predicting the patient's test value when new patient information 215 is input has been constructed.

[0097] The calculation unit 122 calculates the test value information 216 for the test item based on the patient information 215 and test result information that are input each time a clinical test is performed, and the model learned by the learning unit 121. The calculation unit 122 outputs the test value information 216 each time the test value information is calculated. For example, the calculation unit 122 outputs the test value information 216 to the medical information server 110a.

[0098] The inspection value information calculation system 120 can calculate inspection value information 216 every time an inspection is performed and output it to the medical information server 110a (inspection value information storage unit). This allows the inspection value information 216 stored in the medical information server 110a to be kept up to date. Since the processing for calculating inspection value information is performed within each of the medical facilities 100a, 100b, and 100c, it is possible to prevent information about the inspection from leaking outside the medical facility 100a. Furthermore, because the learning unit 121 trains the model, the calculation unit 122 can calculate the inspection value information 216 using a model that reflects up to the results of the most recent inspection.

[0099] <Second embodiment> In the second embodiment, an information processing system 11 is described which, in addition to the process of evaluating the test value for each group performed by the information processing system 10 according to the first embodiment, performs a process of anonymizing the patient name, the name of the medical facility performing the test, and the name of the medical professional, and can compare the test value, including that of other facilities, under specified conditions.

[0100] The hardware configuration of the information processing system 11 according to the second embodiment is common to the information processing system 10 shown in Fig. 1. Therefore, a detailed description of the hardware configuration of the information processing system 11 will be omitted.

[0101] <Example of Functional Configuration of Information Processing System> FIG. 9 is a diagram showing an example of the functional block configuration of the information processing system 11. The information processing system 11 has, as its functions, an in-facility anonymization unit 601 (first anonymization unit), an authority determination unit 603, and an inter-facility anonymization unit 602 (second anonymization unit). The input unit 105 and the output unit 106 are also shown. The in-facility anonymization unit 601 and the authority determination unit 603 are provided in the information processing device 101a. That is, the information processing device 101a has, as its functions, the in-facility anonymization unit 601 and the authority determination unit 603 in addition to the information acquisition unit 201, the classification unit 202, and the calculation unit 203. Although not shown, the information processing devices 101b and 101c have the same configuration as the information processing device 101a. The inter-facility anonymization unit 602 is provided in the external shared server 114. The external shared server 114 is provided outside the medical facilities 100a to 100c. When the information processing devices 101a to 101c are installed on the cloud, the functions of the external shared server 114 may be provided within any one of the information processing devices 101a to 101c.

[0102] The in-facility anonymization unit 601 anonymizes the patient information 215 and the testing value information 216. The patient information 215 includes patient identification information that identifies the patient who underwent the test. The testing value information 216 includes medical professional identification information that identifies the medical professional who underwent the test. In this embodiment, the in-facility anonymization unit 601 anonymizes the patient identification information and the medical professional identification information. The patient identification information is, for example, the patient's name. The medical professional identification information is, for example, the medical professional's name. In other words, the anonymization performed by the in-facility anonymization unit 601 can anonymize the patient's name and the medical professional's name.

[0103] The in-facility anonymization unit 601 performs anonymization on, for example, the patient information 215 and the test value information 216 to create in-facility anonymized information 604. Here, the anonymization process is performed so that information identifying the medical professional (doctor, laboratory technician, etc.) who performed the test and the patient, i.e., the medical professional's name and the patient's name, cannot be identified. The anonymization process is configured to select a combination of any processing methods according to the desired level of protection, such as k-anonymization and 1-diversity. The timing for performing anonymization in the in-facility anonymization unit 601 may be when an update to the information to be anonymized is detected, periodically at a date and time, or at any timing based on the operation of the input unit 105.

[0104] The intra-facility anonymized information 604 is stored in the information processing device 101a. The intra-facility anonymized information 604 may be acquired from the information processing device 101a by the inter-facility anonymization unit 602 when the inter-facility anonymization unit 602 (described later) executes processing. The intra-facility anonymization information 604 may also be automatically uploaded to the external shared server 114 when the inter-facility anonymization unit 602 executes processing.

[0105] The inter-facility anonymization unit 602 receives the patient information 215 and the testing value information 216 that have been anonymized by the intra-facility anonymization unit 601, which are acquired from the information processing devices 101a to 101c, and anonymizes the facility-specific information indicating the facility name included in or added to the received anonymized patient information 215 and the testing value information 216. This makes it possible to anonymize which facility the patient information 215 and the testing value information 216 belong to.

[0106] The inter-facility anonymization unit 602 performs anonymization on intra-facility anonymized information 604 output from the information processing devices 101a of multiple facilities, for example, to calculate inter-facility anonymized information 605. The anonymization process here is performed so that the facility that conducted the inspection cannot be identified. As with the process performed by the intra-facility anonymization unit 601, the inter-facility anonymization unit 602 can select an anonymization process by combining any processing methods. Furthermore, the timing of executing the anonymization process may be set at any timing to coincide with the anonymization process performed by the intra-facility anonymization unit 601.

[0107] When outputting the patient information 215 and the testing value information 216 to the output unit 106, the authority determination unit 603 determines, based on authority information 606 indicating whether or not there is authority to view the patient information 215 before being anonymized by the in-facility anonymization unit 601 and the testing value information 216. Furthermore, when outputting the patient information 215 and the testing value information 216 to the output unit 106, the authority determination unit 603 determines, based on the authority information 606, whether or not there is authority to view the facility names of the patient information 215 and the testing value information 216 that have been anonymized by the inter-facility anonymization unit 602.

[0108] The authority determination unit 603 receives the operation information 214 and the authority information 606 from the input unit 105. For example, based on the authority information 606 included in the operation information 214, the authority determination unit 603 determines whether the user has the authority to view the patient information 215, the examination value information 216, the intra-facility anonymized information 604, and the inter-facility anonymized information 605.

[0109] The operation information 214 includes login information linked to the user's personal information, such as the medical department to which the user belongs. This login information includes information indicating whether each user has the authority to view the patient information 215, the examination value information 216, the intra-facility anonymized information 604, and the inter-facility anonymized information 605. The authority determination unit 603 identifies the user from the operation information 214 and determines whether the identified user has the authority to view each piece of information to be output by linking the identified user to the authority information 606. This enables, for example, the following settings. The information processing system 11 can configure the authority determination unit 603 so that a user, i.e., a doctor, can view the patient information 215 and the examination value information 216 before anonymization for patients under his / her care. On the other hand, the information processing system 11 can configure the authority determination unit 603 so that the doctor cannot view the intra-facility anonymized information 604 and the inter-facility anonymized information 605 before anonymization for patients not under his / her care. If the operation information 214 does not include information indicating whether the user has permission to view the authority information 606, the output unit 106 may display, for example, a message indicating that the information is not viewable. By visually checking this display on the output unit 106, the user can understand that he or she does not have permission to view the information before anonymization.

[0110] If the authority determination unit 603 determines that the user has the authority to view the patient information 215 before being anonymized by the in-facility anonymization unit 601 and the testing value information 216, the output unit 106 outputs information based on the patient information 215 before being anonymized by the in-facility anonymization unit 601 and the testing value information 216, and if the authority determination unit 603 determines that the user does not have the authority to view the patient information 215, the output unit 106 outputs information based on the patient information 215 anonymized by the in-facility anonymization unit 601 and the testing value information 216. Furthermore, if the authority determination unit 603 determines that the user has the authority to view the facility name, the output unit 106 outputs information based on the patient information 215 before being anonymized by the inter-facility anonymization unit 602 and the testing value information 216, and if the authority determination unit 603 determines that the user does not have the authority to view the facility name, the output unit 106 outputs information based on the patient information 215 anonymized by the second anonymization unit and the testing value information 216. Here, the information based on the anonymized patient information 215 and the testing value information 216 is the patient information 215 and the testing value information 216 displayed according to the classified groups described in the first embodiment.

[0111] In this way, based on the authority determination result of the authority determination unit 603, the output unit 106 outputs the information before being anonymized (patient information 215, testing value information 216), intra-facility anonymized information 604 anonymized by the intra-facility anonymization unit 601, or inter-facility anonymized information 605 anonymized by the inter-facility anonymization unit 602. The output unit 106 may also output information such as patient classification information 217, testing value representative value 218, and testing implementation rate 219 linked to the patient information 215 and testing value information 216 for which the user has the viewing authority.

[0112] <Screen Examples of Output Unit> Fig. 10 is a diagram showing a fifth display screen example 701 of the output unit 106. Fig. 11 is a diagram showing a sixth display screen example 705 of the output unit 106. The following describes an example in which the output unit 106 of the information processing device 101a displays information on a display screen, but the information displayed on the display screen may be printed on a paper medium or stored as data in a storage device. The fifth display screen example 701 and the sixth display screen example 705 may be displayed on the same screen, or may be displayed as one screen within another screen and displayed by switching between screens.

[0113] As shown in FIG. 10 , the fifth display screen example 701 includes a patient information designation section 702, an add group button 703, an update button 704, and a facility designation button 705a. The patient information designation section 702 displays patient information for each group to be compared. In FIG. 10 , the patient information designation section 702 allows designation of two groups of patient information: a group A patient information designation section 702a and a group B patient information designation section 702b. The add group button 703 is a button for expanding the area displaying the groups to be compared. The update button 704 is a button for executing processing based on the new patient information 215 for each group when the designation in the group A patient information designation section 702a and the group B patient information designation section 702b is updated. The facility designation button 705a is a button for selecting either the medical facility 101a to which the user belongs or all medical facilities 100a, 100b, and 100c including the facility to which the user belongs.

[0114] The patient information designation section 702 allows designation of extraction conditions for the patient information 215 to be compared. The patient information designation section 702 includes columns for period, admission / discharge category, medical department, diagnosed disease name, age, and attending physician for each of the group A patient information designation section 702a and group B patient information designation section 702b. The user can operate the input section 105 to designate the period, admission / discharge category, medical department, diagnosed disease name, age, and attending physician.

[0115] For example, in the group A patient information designation section 702a, patient information 215 within the "own facility" is designated as group A patient information, where the examination date falls within the period "January 1, 20XX to December 31, 20XX" and the diagnosed disease is "Disease A." Meanwhile, in the group B patient information designation section 702b, patient information 215 within "all facilities" is designated as group B patient information, where the examination date falls within the period "January 1, 20XX to December 31, 20XX" and the diagnosed disease is "Disease A." Neither the group A patient information nor the group B patient information specifies the admission / discharge category, medical department, diagnosed disease, age, or attending physician. In the fifth display screen example 701, the same patient information 215 is designated, and a condition for comparing the own facility (medical facility 100a) with all facilities (medical facilities 100a-100c) is specified.

[0116] Furthermore, when the user operates the input unit 105 and clicks the Add Group button 703, a Group C patient information designation section (not shown) for designating, for example, Group C patient information is displayed in the patient information designation section 702, and the user can then designate extraction conditions for new patient information to be compared in the Group C patient information designation section.

[0117] When the user inputs comparison conditions in the group A patient information designation section 702a and group B patient information designation section 702b on the fifth display screen example 701 and then clicks the update button 704, the authority determination process of the authority determination section 603 described above with reference to Figure 9 is executed. The output unit 106 outputs information that matches the extraction conditions designated on the fifth display screen example 701. As a result, a sixth display screen example 705 is displayed on the output unit 106.

[0118] 11 is a diagram showing a sixth example display screen 705 of the output unit 106. As shown in FIG. 11, the sixth example display screen 705 displays an inspection item display section 706, an inspection value representative value display section 707, an inspection implementation rate display section 708, and an inspection value information display section 709. The inspection item display section 706 displays the types of inspections extracted based on the specified conditions. The inspection value representative value display section 707 and the inspection implementation rate display section 708 display the inspection value representative value 218 and the inspection implementation rate 219 obtained for each inspection, as described above. The inspection value information display section 709 displays a graph showing statistical information on the inspection value.

[0119] In the sixth display screen example 705, there is no display section that displays the patient name, medical professional name, and facility name, but when the screen is switched to one that displays the patient name, medical professional name, and facility name, the patient name, medical professional name, and facility name are displayed anonymized based on the user's authority information.

[0120] Note that the sixth display screen example 705 may be set to display information that is determined to be authorized for viewing by the user. In this case, if the information extracted based on the extraction conditions does not include information that the user has permission to view, a message to that effect, such as "There is no information to display," may be displayed on the sixth display screen example 705 (not shown).

[0121] The test item display section 706 displays test items A to D. For each of tests A to D, a test value representative value 218 calculated from the group A patient information and the group B patient information, and a test implementation rate 219 are displayed. In FIG. 11 , it is displayed that group A is the group A patient information, and group B is the group B patient information. For example, it is displayed that the test value representative value 218 for test A is 92 points in the group A patient information and 88 points in the group B patient information. It is also displayed that the test implementation rate for test A is 90% in the group A patient information and 70% in the group B patient information.

[0122] Furthermore, statistical information of the examination value information 216 calculated from the group A patient information and group B patient information for each of the examinations A to D is displayed in the examination value information display section 709 using box and whisker plots 713 and 714. The group A display 711 displays the same content as the box and whisker plot 713 to indicate that the statistical information is calculated from the group A patient information, and the group B display 712 displays the same content as the box and whisker plot 714 to indicate that the statistical information is calculated from the group B patient information. In FIG. 11 , the group A display 711 and the box and whisker plot 713 are hatched, and the group B display 712 and the box and whisker plot 714 are hollowed out, allowing the group A patient information and the group B patient information to be displayed distinctly. Because the statistical information is displayed using box and whisker plots 713 and 714, the user can easily visually recognize the distribution of each of the group A patient information and the group B patient information. The inspection value information 216 is shown in the box plots 713 and 714, but is not limited to this and may be displayed in other formats such as a graph, a histogram, a distribution chart, a scatter diagram, etc. Furthermore, instead of the inspection value information 216 displayed in the inspection value information display unit 709, distribution information of the inspection result values ​​or the like may be displayed instead.

[0123] In addition, in the information processing system 11, the fifth display screen example 701 and the sixth display screen example 705 shown in Figures 10 and 11 may be displayed on the same screen together with the first display screen example 401, the second display screen example 405, the third display screen example 401a, or the fourth display screen example 501 already described.

[0124] As described above, the information processing system 11 according to the second embodiment can output the test value information 216, including that of other facilities, to the output unit 106 so that it can be compared according to any conditions, while maintaining the anonymity of the patient who is the subject of the test, the medical facility that performs the test, and the medical staff thereat.

[0125] For example, in the medical facility 100a, when a user who has the authority to identify patients and medical professionals attempts to view patient information 215 and testing value information 216 related to tests performed in the medical facility 100a using the information processing device 101a, the information processing system 11 displays the patient information 215, testing value information 216, etc. on the output unit 106 so that the patient name and the medical professional name can be identified. On the other hand, in the medical facility 100a, when a user who does not have the authority to identify patients and medical professionals attempts to view the patient information 215 and testing value information 216 related to tests performed in the medical facility 100a, the information processing system 11 displays the patient information 215, testing value information 216, etc. on the output unit 106 so that the patient name and the medical professional name cannot be identified.

[0126] Furthermore, for example, when a user at the medical facility 100a attempts to view patient information 215 and testing value information 216 related to examinations at the medical facilities 100a to 100c using the information processing device 101a, the information processing system 11 displays the patient information 215 and testing value information 216 related to examinations at the medical facility 100a on the output unit 106 in a manner that allows the facility name to be identified. On the other hand, the information processing system 11 displays the patient information 215 and testing value information 216 related to examinations at the medical facilities 100b and 100c on the output unit 106 in a manner that prevents the patient name, medical professional name, and facility name from being identified.

[0127] The information processing system 11 allows a user to compare the test value information 216 based on desired conditions. At this time, the information processing system 11 can ensure the anonymity of patients, medical facilities, and medical professionals.

[0128] Furthermore, in this embodiment, a comparison between two groups of patients that meet the conditions specified in the patient information specifying unit 702 has been described, but the information processing system 11 can also compare a specific patient with a group of patients that meet the specified conditions. This allows the information processing system 11 to compare the test result values ​​of a specific patient with, for example, the distribution of test result values ​​of a group of patients that have conditions similar to those of the patient, and output the comparison results to the output unit 106. Therefore, the user can visually understand, for example, whether the test result values ​​of a specific patient fall within a statistically valid range.

[0129] The technology described in this embodiment is not limited to the above-described embodiment, and includes various modifications. In the above-described embodiment, the explanation has been given using an example of testing at the medical facilities 100a to 100c. However, for example, the information processing system 10 and the information processing system 11 can perform processing similar to the processing performed on the testing value information 216 for prescription value information that indicates an index related to the effect obtained by administering a drug or the like to a patient within the medical facility. This allows the technology described in this embodiment to be applied to the evaluation of the value of prescribing a drug and the efficiency of prescribing a drug.

[0130] In addition, for example, the above-described embodiments have been described in detail to clearly explain the technology of the present disclosure, and are not necessarily limited to those including all of the described configurations. Furthermore, it is possible to replace part of the configuration of one embodiment with the configuration of another embodiment, and it is also possible to add the configuration of another embodiment to the configuration of one embodiment. Furthermore, it is also possible to add, delete, or replace part of the configuration of each embodiment with other configurations.

[0131] 10, 11... Information processing system, 101a to 101c... Information processing device, 102... Arithmetic unit, 103... Main memory device, 104... Communication unit, 105... Input unit, 106... Output unit, 107... Auxiliary memory device, 108a to 108c... In-facility network, 109a to 109c... External memory device, 110a to 110c... Medical information server, 111a to 111c... Diagnostic analysis device, 112... Outside facility network, 113... Provider, 114... External shared server, 120...inspection value information calculation system, 121...learning unit, 122...calculation unit, 201...information acquisition unit, 202...classification unit, 203...calculation unit, 204...inspection value representative value calculation unit, 205...inspection implementation rate calculation unit, 206...improvement examination candidate calculation unit, 207...estimated loss calculation unit, 208...input information, 209...electronic medical record information, 210...examination order information, 211...receipt information, 212...in-hospital information, 213...guideline information, 214...operation information, 215...patient information, 216...examination value information, 217...patient classification information, 218...examination value representative value, 219...examination implementation rate, 220...estimated loss, 221...improvement threshold, 222...improvement examination candidate, 223...medical fee information, 224...examination cost information, 401...first display screen example, 401a...third display screen example, 403...improvement threshold setting section, 404...patient information setting section, 405...second display screen example, 409...improvement examination candidate display , 501...Fourth display screen example, 603...Authority determination section, 604...Intra-facility anonymized information, 605...Inter-facility anonymized information, 606...Authority information, 701...Fifth display screen example, 702a...Group A patient information designation section, 702b...Group B patient information designation section, 703...Add group button, 704...Update button, 705...Sixth display screen example, 706...Test item display section, 707...Test value representative value display section, 708...Test implementation rate display section, 709...Test value information display section

Claims

1. An information processing system that evaluates the value of multiple test items, comprising: an information acquisition unit that acquires patient information on each of multiple patients who are the subject of the test, and test value information on the effects obtained by administering the test to each of the multiple patients for each of the test items; a classification unit that classifies the multiple patients into multiple groups based on the patient information and test value information acquired by the information acquisition unit; and a representative value calculation unit that calculates, for each group classified by the classification unit, a representative value which is an index value statistically obtained from the multiple pieces of test value information.

2. An information processing system according to claim 1, further comprising an output section that outputs the representative value calculated by the representative value calculation section.

3. An information processing system according to claim 1, further comprising: an inspection implementation rate calculation unit that calculates an inspection implementation rate indicating the proportion of inspection items that are being implemented for each group classified by the classification unit; and an improvement inspection candidate calculation unit that calculates inspection efficiency for each inspection item in the classified group based on the inspection implementation rate calculated by the inspection implementation rate calculation unit and the representative value calculated by the representative value calculation unit, and calculates improvement inspection candidates for the inspection items in the group based on the calculated inspection efficiency and a threshold value that specifies improvement efficiency.

4. An information processing system according to claim 3, further comprising an output unit that outputs the improvement inspection candidate calculated by the improvement inspection candidate calculation unit in an emphasized manner.

5. An information processing system according to claim 3, wherein the information acquisition unit acquires medical fee information indicating the fee for testing each of the plurality of test items and test cost information indicating the test costs incurred by performing each of the plurality of test items; and further comprises an estimated loss calculation unit that calculates an estimated loss related to the cost of testing each of the test items estimated by performing each of the test items based on the test implementation rate, the representative value, the medical fee information, and the test cost information; and the improvement test candidate calculation unit calculates the improvement test candidate based on the representative value, the test implementation rate, and the estimated loss.

6. An information processing system according to claim 1, further comprising: a learning unit that uses a dataset that receives as input the patient information and test result information relating to the test results obtained by administering the test to the patient and outputs the test value information to learn a model used to calculate the value of the test item; and a calculation unit that calculates the test value information of the test item based on the patient information and test result information that are input each time the test is administered, and the model.

7. An information processing system according to claim 6, further comprising an inspection value information storage unit that stores the inspection value information, wherein the calculation unit outputs the inspection value information to the inspection value information storage unit every time the inspection value information is calculated.

8. An information processing system according to claim 1, further comprising: a first anonymization unit that anonymizes the patient information and the testing value information; and an authority determination unit that, when outputting the patient information and the testing value information, determines whether or not there is authority to view the patient information and the testing value information before being anonymized by the first anonymization unit, based on authority information indicating whether or not there is authority to view the patient information and the testing value information before being anonymized.

9. An information processing system according to claim 8, further comprising an output unit that, when the authority determination unit determines that there is authority to view, outputs the patient information before being anonymized by the first anonymization unit and information based on the testing value information, and, when the authority determination unit determines that there is no authority to view, outputs the patient information anonymized by the first anonymization unit and information based on the testing value information.

10. An information processing system according to claim 9, wherein the patient information includes patient identification information that identifies the patient who performed the test, the test value information includes medical professional identification information that identifies the medical professional who performed the test, and the first anonymization unit anonymizes the patient identification information and the medical professional identification information.

11. An information processing system according to claim 10, wherein the information processing system includes information processing devices installed in a plurality of facilities, and a server communicably connected to each of the information processing devices, wherein the authority information further includes information indicating whether or not there is authority to view the names of the facilities where the information processing devices are installed, wherein the information processing devices each include the information acquisition unit, the classification unit, the representative value calculation unit, the first anonymization unit, the authority determination unit, and the output unit, and wherein the server receives the patient information and the testing value information anonymized by the first anonymization unit, respectively, acquired from the information processing device, and includes a second anonymization unit that anonymizes the received patient information and facility-specific information indicating the facility name included in or added to the testing value information, wherein the authority determination unit, when outputting the patient information and the testing value information to the output unit, further determines, based on the authority information, whether or not there is authority to view the patient information anonymized by the second anonymization unit and the name of the facility from which the testing value information was obtained, When the authority determination unit determines that there is authority to view the facility name, the output unit outputs the patient information before being anonymized by the second anonymization unit and information based on the testing value information, and when the authority determination unit determines that there is no authority to view the facility name, the output unit outputs the patient information anonymized by the second anonymization unit and information based on the testing value information.

12. An information processing method for evaluating the value of multiple test items, comprising: acquiring patient information on each of multiple patients who are the subjects of the test; and test value information on the effects obtained by administering the test to each of the multiple patients for each of the test items; classifying the multiple patients into multiple groups based on the acquired patient information and test value information; and calculating, for each classified group, a representative value, which is an index value statistically determined from the multiple pieces of test value information.

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