Medical assistance system, medical assistance method, and program

Abstract

To assist determination by clinicians based on inspection results of a clinical test.SOLUTION: In a medical assistance system 1, a user terminal has a clinical inspection result data acquisition unit for acquiring clinical inspection result data in which a plurality of clinical inspection items and parameters representing results of the inspection. A medical assistance device comprises: a storage unit including an analysis logic DB that selects a plurality of preliminarily defined clinical inspection items of a biological sample and one or more clinical inspection items for each disease to be determined from a reference range DB for recording a reference range of the items and the plurality of clinical inspection items, and that records the items in combination with the deviation from the reference range; a diagnosis assistance preprocessing unit for comparing the parameters acquired for each clinical inspection item with the reference range and determining the deviation of the parameters from the reference range; and a diagnosis assistance post-processing unit for determining whether or not the deviation per clinical inspection item satisfies the combination of deviation for the clinical inspection items of diseases stored in the analysis logic storage unit and determining, when satisfied, that a likely disease is a cause candidate disease.SELECTED DRAWING: Figure 3

Description

[Technical field]

[0001] The present invention relates to a medical support system, a medical support method, and a program. [Background technology]

[0002] Traditionally, diagnoses based on the results of clinical tests such as blood tests were made by sending a blood sample to a specialized testing institution, and a clinical doctor would read and interpret the test result report prepared by the testing institution and provide advice to the patient based on the clinical doctor's experience. Therefore, when multiple examinations are performed, particularly when examinations using medical imaging diagnostic equipment such as X-ray diagnostic equipment, X-ray CT equipment, MRI equipment, ultrasound imaging diagnostic equipment, and nuclear medicine diagnostic equipment are included, a technology has been disclosed that integrates the examination result reports for each examination performed into a single examination result report, thereby reducing the workload of doctors and improving diagnostic efficiency (see Patent Document 1). [Prior art documents] [Patent documents]

[0003] [Patent Document 1] JP 2014-096055 A Summary of the Invention [Problem to be solved by the invention]

[0004] However, while Patent Document 1 makes it easier to understand the test results by consolidating multiple test results into a single test result report, a doctor must make a judgment based on the test results, and the more test results there are, the more time and effort it takes.In addition, because the judgment is made by human beings, the judgments vary from person to person and depending on experience, which is a problem.

[0005] Therefore, an object of the present invention is to provide a medical support system, a medical support method, and a program for supporting a clinician's decision based on the test results of a clinical test. [Means for solving the problem]

[0006] The present invention relates to a method for testing a biological sample comprising: an analysis logic storage unit that selects one or more clinical test items for each disease to be diagnosed from the plurality of clinical test items, and records the combination of the deviation status from the reference range; a clinical test result data acquiring unit that acquires clinical test result data in which the plurality of clinical test items are associated with parameters that are test results of the clinical test items; a diagnostic support pre-processing unit that compares the acquired parameters with the reference ranges for each of the test items and determines whether the parameter values ​​deviate from the reference ranges; a post-diagnosis support processing unit that determines whether the deviation status determined for each test item satisfies a combination of deviation statuses of clinical test items for the disease stored in an analysis logic storage unit, and if so, determines the possible disease as a candidate cause disease; Equipped with A medical support system is provided that identifies the disease by presenting the candidate causative diseases to a doctor and receiving confirmation of the diagnosis from the doctor. Effect of the Invention

[0007] According to the present invention, it is possible to assist clinicians in making decisions based on the test results of clinical tests. [Brief description of the drawings]

[0008] [Figure 1] 1 is a schematic diagram of a medical support system according to an embodiment of the present invention. [Diagram 2] 2 is a block diagram showing the hardware configuration of a computer included in the medical support device and a user terminal according to the embodiment. FIG. [Diagram 3] 1 is a diagram illustrating a functional configuration of a medical support system according to an embodiment of the present invention. [Figure 4] FIG. 4 is a flowchart showing a medical support process according to the present embodiment. [Diagram 5]FIG. 11 is a flowchart showing a data extraction process performed by a clinical test result data acquisition unit of the medical support system according to the present embodiment. [Figure 6] FIG. 4 is a diagram illustrating a reference range DB according to the present embodiment. [Figure 7] FIG. 2 is a diagram illustrating an analysis logic DB according to the present embodiment. [Figure 8] FIG. 2 is a diagram showing a list of diseases to be diagnosed by the medical support system according to the present embodiment. [Figure 9] 4 is an example of a screen of the medical support system according to the present embodiment. [Figure 10] 4 is an example of a screen of the medical support system according to the present embodiment. [Figure 11] 4 is an example of a screen of the medical support system according to the present embodiment. [Figure 12] 4 is an example of a screen of the medical support system according to the present embodiment. [Figure 13] 4 is an example of a screen of the medical support system according to the present embodiment. [Figure 14] 4 is an example of a screen of the medical support system according to the present embodiment. [Figure 15] 4 is an example of a screen of the medical support system according to the present embodiment. [Figure 16] 4 is an example of a screen of the medical support system according to the present embodiment. [Figure 17] 4 is an example of a screen of the medical support system according to the present embodiment. [Figure 18] 4 is an example of a screen of the medical support system according to the present embodiment. [Figure 19] 4 is an example of a screen of the medical support system according to the present embodiment. [Figure 20] 4 is an example of a screen of the medical support system according to the present embodiment. [Figure 21] 4 is an example of a screen of the medical support system according to the present embodiment. [Figure 22] 4 is an example of a screen of the medical support system according to the present embodiment. [Figure 23] 4 is an example of a screen of the medical support system according to the present embodiment. DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0009] Hereinafter, a detailed description will be given of an embodiment of the present invention with reference to the accompanying drawings. In the following drawings, the same elements are designated by the same numbers or symbols throughout the description of the embodiment.

[0010] [Basic concept / basic configuration] FIG. 1 is a schematic diagram of a medical support system 1 according to this embodiment. The medical support system 1 is a system that supports a clinician in creating an analysis report on a clinical test result, and includes a user terminal 200 operated by the clinician, and a medical support device 100 connected to the user terminal 200 via an information communication line such as the Internet. In this embodiment, the medical support device 100 is a cloud server, but may be on-premise. Also, the medical support device 100 may be physically the same device as the user terminal 200.

[0011] First, clinician D obtains a biological sample from patient P, for example by drawing blood, based on a request from patient P. Clinician D sends this biological sample to a testing institution, which performs the required tests, and receives a clinical test result report 10 from the testing institution. This clinical test result report 10 lists multiple clinical test items, and which clinical test item is listed where is in a unique format determined by the testing institution, and is not a unified format across testing institutions, but the listed clinical test items themselves are generally similar.

[0012] The user terminal 200 acquires clinical test result data 20 in a predetermined format based on the clinical test result report 10 by scanning the clinical test result report 10 if it is paper, or by converting the data format if it is data (S1). Here, the clinical test result data 20 is data in which clinical test items in blood tests and the like are associated with biological parameters of the clinical test items. Details of the method of acquiring the clinical test result data 20 from the clinical test result report 10 will be described later. Then, the user terminal 200 transmits the acquired clinical test result data 20 to the medical support device 100 (S2).

[0013] After receiving the clinical test result data 20 from the user terminal 200, the medical support device 100 performs pre-diagnosis support processing (S3) to compare the reference ranges and biological parameters for each clinical test item based on the clinical test result data 20 and the reference ranges for each clinical test item stored in advance, and obtain the deviation status.

[0014] In detail, the medical support device 100 refers to the reference range for each clinical test item stored in advance, and acquires the deviation status of the biological parameter included in the clinical test result data 20 from the reference range for each clinical test item. For example, the deviation status of the biological parameter from the reference range includes "high" where the biological parameter exceeds the reference range, "positive" where the biological parameter is within the reference range, and "low" where the biological parameter is smaller than the reference range. Then, the medical support device 100 creates pre-diagnosis support result data in which the deviation status is associated with each clinical test item.

[0015] Next, the medical support device 100 executes post-diagnostic support processing to determine possible diseases as candidate causative diseases based on the pre-diagnostic support result data and a combination of deviation conditions for each clinical test item, which are conditions for determining each disease, which are stored in advance (S4).

[0016] In detail, for each disease for which a combination of deviation conditions for each clinical test item is stored as a judgment condition, the medical support device 100 judges whether the deviation conditions in the pre-diagnosis support result data satisfy or do not satisfy the combination of deviation conditions for each clinical test item.The medical support device 100 then identifies a disease for which the judgment result is "positive" as a possible cause disease, and creates analysis report data 30 in which the possible cause disease is associated with the judgment result of "positive."

[0017] As will be described later, the analysis report data 30 may include the clinical test result data 20, a description of the suspected causative disease that has been stored in advance, information on medications and supplements being taken that has been obtained from Patient P's electronic medical record or computerized medicine notebook on another terminal via API integration or the like, prescriptions that have been stored in advance for the suspected causative disease, and comment information that has been stored in advance for the suspected causative disease.

[0018] The medical support device 100 transmits the analysis report data 30 created in the post-diagnosis support process of S4 to the user terminal 200 (S5). After receiving the analysis report data 30, the user terminal 200 displays the received analysis report data 30 on the display unit and accepts instructions from the clinician D to modify the analysis report data 30. The analysis report data 30 is updated according to the clinician D's judgment, and upon receiving an input indicating that the clinician D has finished checking, the user terminal 200 executes an analysis result checking process in which the updated analysis report data 30 is checked and turned into analysis report data 40 (S6).

[0019] For example, if clinician D diagnoses disease A as “suspected” based on the clinical test result report 10 and the clinical test result data 20, but the disease is “positive” in the analysis report data 30, the user terminal 200 updates the analysis report data 30 upon receiving an instruction from clinician D to change “positive” to “suspected” for disease A in the analysis report data 30. In addition, if clinician D diagnoses disease B, which was determined to be “negative” in S4 and is not included in the analysis report data 30, as “suspected” based on the clinical test result report 10 and the clinical test result data 20, the user terminal 200 updates the analysis report data 30 upon receiving an instruction from clinician D to add that disease B is “suspected.”

[0020] In addition, if the analysis report data 30 includes a description of the suspected causative disease that is stored in advance, information on medications and supplements being taken obtained from the patient P's electronic medical record or electronic medicine notebook stored on another terminal, prescriptions that are stored in advance for the suspected causative disease, comment information that is stored in advance for the suspected causative disease, etc., the comment information, etc. are also displayed on the user terminal 200, and the clinician D can modify this information as desired.

[0021] Then, the user terminal 200 transmits the created post-confirmation analysis report data 40 to the medical support device 100 (S7). The medical support device 100 generates a definitive analysis report 50 based on the received post-confirmation analysis report data 40 (S8), and transmits it to the user terminal 200 (S9).

[0022] The definitive analysis report 50 is an analysis report of the results of a definitive diagnosis made by clinician D after checking the analysis result data, and includes at least a diagnosis result describing the causative disease diagnosed by clinician D, and may also include analysis results describing the clinical test result data 20, prescription results describing the prescription by clinician D based on the diagnosis result, and medication information describing medications and supplements currently being taken obtained from patient P's electronic medical record or electronic medication notebook on another terminal. The user terminal 200 executes a definitive analysis report display process for displaying the received definitive analysis report 50 on a display unit (S10). The contents of the displayed definitive analysis report are provided by the clinician D to the patient P. The definitive analysis report 50 may be output from an output unit such as a printer.

[0023] FIG. 2 is a block diagram showing the hardware configuration of the medical support device 100 and the computer 300 included in the user terminal 200 according to the embodiment of the present invention. The computer 300 includes, for example, a processor 301, a memory (main storage device) 302, an auxiliary storage device 303, an output device 304, an input device 305, and a communication interface (I / F) 306. The above components are connected to each other via a bus.

[0024] The memory 302 is primarily used to hold programs and data being executed, and the processor 301 operates in accordance with the programs stored in the memory 302 to realize various functional units (see FIG. 3) described below. The auxiliary storage device 303 stores data used by the processor 301, and corresponds to the storage unit 150 and user storage unit 250 in FIG.

[0025] The output device 304 is a hardware device that presents various images for input and output, such as a display device or a printing device. The input device 305 is a hardware device for inputting instructions and information from the user, and in the case of the user terminal 200, is an imaging device such as a scanner or a camera. The communication I / F 306 is an interface for connecting to a network.

[0026] FIG. 3 is a diagram showing the functional configuration of the medical support system 1 according to this embodiment. The medical support system 1 includes a medical support device 100 and a user terminal 200. The medical support device 100 includes a communication unit 110 , a diagnostic support pre-processing unit 120 , a diagnostic support post-processing unit 130 , a definitive analysis report creation unit 140 , and a storage unit 150 .

[0027] The storage unit 150 includes a clinical test result data DB 151, a reference range DB 152, an analysis logic DB 153, a report data DB 154, and a definitive analysis report DB 155. In this embodiment, the storage unit 150 is preferably configured as a cloud storage or a distributed ledger, but may also be configured as a hard disk, a semiconductor memory, a storage medium, a memory card, or the like.

[0028] The user terminal 200 includes a communication unit 210, a clinical test result data acquisition unit 220, an analysis report confirmation unit 230, a display unit 240, and a user storage unit 250. The user storage unit 250 includes an electronic clinical test result report DB 251, and a customized DB 252. Details of each functional unit will be explained together with the medical support processing flow shown in Figure 4.

[0029] FIG. 4 is a diagram showing a flowchart of the medical support process according to this embodiment. First, when the clinical test result data acquisition unit 220 acquires the clinical test result report 10, it extracts and associates the clinical test items included in the clinical test result report 10 with the biological parameters corresponding to those items, acquires the clinical test result data 20, and transmits it to the medical support device 100 (S11).

[0030] Here, the clinical test result report 10 may include not only blood test but also biological parameters obtained by testing a living body, such as hair, urine, sweat, saliva, DNA, and stool, at least in association with the test items. For example, the clinical test result report 10 for a blood test may include white blood cell count, red blood cell count, hemoglobin, hematocrit, MCV (mean corpuscular volume), MCH (mean corpuscular hemoglobin), MCHC (mean corpuscular hemoglobin concentration), platelets, reticulocytes, eosinophils, neutrophils, lymphocytes, Fe (serum iron), TIBC (total iron binding capacity), ferritin, blood glucose, HbAlc (hemoglobin Alc), insulin, glycoalbumin, 1.5AG, total protein, A / G ratio, albumin, GOT (AST), GPT (ALT), γGTP, ALP, LDH, cholinesterase, CPK, amylase, B It includes clinical test items such as UN (urea nitrogen), creatinine, uric acid, Cl (chlorine), Zn (zinc), Cu (copper), triglycerides, LDL cholesterol, TSH (thyroid stimulating hormone), FT3 (triiodothyronine), FT4 (thyroxine), CRP, homocysteine, 25(OH)2 vitamin D3, pepsinogen I, PGI / PGII ratio, NEFA, Helicobacter pylori antibody, basophil count, HOMA-R, indirect bilirubin, CaxP, GOT (AST)-GPT (ALT), etc., and test values ​​that are biological parameters corresponding to each of the items.

[0031] The process of acquiring the clinical test result data 20 from the clinical test result report 10 will be described with reference to FIG.

[0032] FIG. 5 is a diagram showing a flowchart of the data acquisition process by the clinical test result data acquisition unit 220 of the medical support system 1 according to this embodiment. When the clinical test result report 10 is a paper medium, the clinical test result report 10 is captured in advance by an imaging device such as a scanner or camera and stored as electronic data in the electronic clinical test result report DB 251. On the other hand, when the clinical test result report 10 is an electronic file such as PDF, since it is already electronic data, it is stored as it is in the electronic clinical test result report DB 251. Hereinafter, the electronic data clinical test result report 10 will be referred to as the electronic clinical test result report 11.

[0033] The clinical test result data acquiring unit 220 judges whether the electronic clinical test result report 11 stored in the electronic clinical test result report DB 251 is structured electronic data in a table format (S101). If the electronic data is not structured electronic data in a table format, the clinical test result data acquiring unit 220 advances the process to S102, whereas if the electronic data is structured electronic data in a table format, the clinical test result data acquiring unit 220 advances the process to S105. Here, the structured electronic data in a table format refers to electronic data in Excel or CSV format.

[0034] Since the electronic clinical test result report 11 stored in the electronic clinical test result report DB 251 is not structured electronic data in a table format, the clinical test result data acquiring unit 220 performs OCR processing on the electronic clinical test result report 11 to extract character strings (S102). Specifically, the clinical test result data acquiring unit 220 extracts character strings of clinical test items from the electronic clinical test result report 11 based on the format data corresponding to the electronic clinical test result report 11.

[0035] Here, since the arrangement of clinical test items is determined by the testing institution, the format showing which items are written where in the electronic clinical test result report 11 can be learned in advance and stored as format data. Since the character string that will be written in that position has been learned in advance as format data, when a character string is extracted from the electronic clinical test result report 11, the corresponding character string in the format data is extracted as the character string of the clinical test item. Therefore, even if the character string cannot be extracted completely correctly, the correct character string can be extracted and converted by matching the position where the character is written and the number and character. Note that if the character string extracted from the electronic clinical test result report 11 is completely different from the corresponding character string in the format data, a notification to that effect may be given.

[0036] Next, the clinical test result data acquiring section 220 extracts, for each character string extracted in S101, a number of a biological parameter written near the character string (S103). Since the positional relationship between the clinical test item and the numbers which are the biological parameters of the clinical test item in the electronic clinical test result report 11, for example, to the right of the clinical test item or two spaces below, is also determined by the testing institution, the positional relationship can be added to the format data and learned in advance, so that the numbers of the biological parameters can be extracted with high accuracy for each character string of the clinical test item extracted in S101. The options for numbers are limited compared to general characters, and the reading accuracy is also sufficiently higher than that of characters.

[0037] Next, the clinical test result data acquiring unit 220 associates the character string extracted in S102 with the numbers near the character string extracted in S102 for each character string, and arranges them in the order of the predetermined clinical test items set in advance to create the clinical test result data 20 (S104).

[0038] Since the electronic clinical test result report 11 stored in the electronic clinical test result report DB 251 is electronic data structured in a table format, the clinical test result data acquisition unit 220 arranges the character strings and the numbers associated with the character strings in the order of the predetermined clinical test items to create the clinical test result data 20 (S105). At this time, the variations in the notation of individual clinical test items, such as hemoglobin and Hb, are also collated and stored based on a previously set rule.

[0039] The clinical test result data acquisition unit 220 assigns a file name to the clinical test result data 20 created in S105 (S106). The file name is a unique format name for each testing institution given to the clinical test result report 10, and the file name may be assigned as is or may be arbitrarily renamed. In the case of arbitrarily renaming, the file name uses at least one of information for identifying the clinical test result data 20, the name of the patient P, the unique number of the clinical test result report 10, the date of the clinical test, and the date of creation of the clinical test result report 10.

[0040] When the file name is the creation date of the clinical test result report 10, the creation date of the clinical test result report 10 can be used as the file name, regardless of the time lag between the creation of the clinical test result report 10 and the creation of the clinical test result data 20. When the file name is the patient name, the clinician D can accurately select a desired clinical test result data 20 from multiple files in the diagnostic support pre-processing described later.

[0041] The file format of the clinical test result data 20 may be any format such as TXT, CSV, PDF, etc., as long as it stores character information, but in this embodiment, the CSV format is used. The advantage of using the CSV format is that it is easy to recognize on the system and easy to handle cases where the format is converted. In addition, header information indicating the start of the file is recorded at the beginning of the file of the clinical test result data 20, and footer information indicating the end of the file is recorded at the end.

[0042] Returning to FIG. 4, the clinical test result data acquiring unit 220 may link the created clinical test result data 20 with interview data, visual examination data, palpation data, percussion data, auscultation data, etc., and transmit them all together to the medical support device 100. In addition, the clinical test result data acquisition unit 220 may transmit customized data such as the reference range of biological parameters for each clinical test item, test item description, and test item name stored in the customized DB 252 to the medical support device 100 together with the clinical test result data 20. The customized data transmitted to the medical support device 100 is used by a diagnostic support pre-processing unit 120 and a diagnostic support post-processing unit 130, which will be described later.

[0043] The customized data is data that the clinician D customizes the data used in the medical support process, specifically, the standard range of the biological parameter for each clinical test item, the explanation of the test item, the name of the test item, etc. The customized data can be created by the clinician D or the like by displaying default data such as the standard range of the biological parameter for each clinical test item on the data setting screen displayed on the display unit 240 of the user terminal 200 and modifying or adding to the default data. The customized data does not have to be transmitted to the medical support device 100 together with the clinical test result data 20, and may be transmitted at any time and stored in the storage unit 150 of the medical support device 100 as needed.

[0044] Next, the diagnosis support preprocessing unit 120 stores the clinical test result data 20 acquired via the communication unit 110 in the clinical test result data DB 151 (S12). Next, the diagnosis support preprocessing unit 120 refers to the reference range DB 152, compares the reference range with the biological parameters of the clinical test result data 20 for each clinical test item, and acquires deviation from the reference range (S13). Here, the reference range is a value set for each test item and serves as a standard for detecting abnormalities.

[0045] 6 is a diagram showing a schematic diagram of the reference range DB 152 according to this embodiment. The reference range DB 152 includes information indicating clinical test items, upper and lower limits of the reference ranges of biological parameters, and units. The reference ranges may be set according to gender, age, smoking or drinking habits, work (desk work or physical labor), etc. For clinical test items for which customized reference ranges have been received from the user terminal 200 together with the clinical test result data 20, the customized reference ranges are given priority for use.

[0046] 4, the diagnosis support preprocessing unit 120 specifically determines the deviation status for each clinical test item as "positive" if the biological parameter is within the reference range, "low" if the biological parameter is outside the reference range and is equal to or lower than the lower limit, and "high" if the biological parameter is outside the reference range and is equal to or higher than the upper limit, and acquires the deviation status. Furthermore, the deviation status may be determined as "extra low" if the biological parameter is equal to or lower than a preset threshold value that is significantly lower than the lower limit, and as "extra high" if the biological parameter is equal to or higher than a preset threshold value that is significantly higher than the upper limit.

[0047] Next, the diagnostic support post-processing unit 130 performs post-diagnostic support processing to match the deviation conditions for each clinical test item acquired in S13 with the disease determination conditions consisting of a combination of deviation conditions for each clinical test item in the analysis logic DB 153, and determine the possible causative disease (S14).

[0048] In detail, the post-diagnosis support processing unit 130 extracts a combination of deviation conditions for each clinical test item, which is the judgment condition, from the analysis logic DB 153 for each disease, and compares the deviation conditions for each clinical test item acquired in S13. Then, if the deviation conditions for the judgment conditions are satisfied, the result is judged as "positive," and if the deviation conditions for the judgment conditions are not satisfied, the result is judged as "negative," and the disease judged as "positive" is judged to be a candidate cause disease.

[0049] 7 is a diagram illustrating the analysis logic DB 153 according to the present embodiment. Since the clinical test items used to determine whether or not a disease occurs differ for each disease category, the analysis logic DB 153 has a table for each disease category. Each table contains information indicating the deviation status of each clinical test item which is a condition for determining a disease, category 1 which indicates the category of a possible disease, category 2 which indicates the category of a possible disease, possible diseases, <Diet> which is comment information on diet for the disease, <Supplements> which is comment information on supplements and medication for the disease, and <Daily Actions> which is comment information on daily actions for the disease. <Diet>, <Supplements>, and <Daily Activities> are advice on diet, supplements, and daily activities to treat the underlying disease, and are used when creating the report described below.

[0050] 8 shows an example of a list of diseases whose determination conditions are stored in the analysis logic DB 153 and analyzed by the medical support system 1 of this embodiment. Note that the diseases shown in FIG. 8 are merely examples, and the list is not limited to these.

[0051] In the case of a human clinician, when data is obtained that the sugar level in blood is higher than the reference range, the typical step of diagnosing a disease is to assume several disease candidates, and to identify and diagnose one of them by sequentially checking the next clinical diagnostic items. On the other hand, in the present medical support system 1, in order to identify a plurality of types of diseases, for example 27 types, clinical tests are performed from the beginning, and the analysis logic storage unit 153 that stores the specific conditions of the disease is used to make a condition judgment for all diseases at once. Specifically, when deviations in the clinical test items are obtained from the clinical test results of a patient, the analysis logic storage unit 153 that stores the combination of the clinical test items and the deviations in the clinical test items as specific conditions of the disease is used to make a condition judgment for all diseases at once. As a result, the present medical support system 1 can automatically and comprehensively determine diseases, and can identify candidate diseases without omission.

[0052] 4, the post-diagnosis support processing unit 130 refers to the clinical test result data 151, the analysis logic DB 153, and the report data DB 154 based on the determined cause candidate disease, and creates analysis report screen data 31 that displays a predetermined screen that includes analysis report data 30 that the clinician D checks before creating the definitive analysis report 50 and accepts correction input to the data (S15). The report data DB 154 stores preset information to be presented in the definitive analysis report 50, the details of which will be described later, such as information on the disease, information on the treatment pyramid, and symptoms corresponding to the test results.

[0053] The analysis report screen data 31 includes analysis result screen data for displaying an analysis result screen including the clinical test result data 20, and diagnosis result screen data for displaying a diagnosis result screen including data on a candidate cause disease. The data on the candidate cause disease is, for example, "positive" for the candidate cause disease, an explanation of the candidate cause disease, diet for treating the candidate cause disease, prescription of medicine or supplements, and advice on daily activities. The analysis result screen and diagnosis result screen will be described later. Note that, when the interview data, visual examination data, palpation data, percussion data, and auscultation data are received from the user terminal 200 together with the clinical test result data 20, the analysis report screen data 31 includes examination result screen data for displaying each of them.

[0054] The diagnostic support post-processing unit 130 transmits the created analysis report screen data 31 to the user terminal 200, and the display unit 240 of the user terminal 200 displays the analysis result screen and the diagnosis result screen based on the received analysis report screen data 31 (S16). The analysis report confirmation unit 230 of the user terminal 200 accepts corrections to the data related to the cause candidate disease displayed on the diagnosis result screen (S17). Here, corrections include changing the data related to the cause candidate disease and adding data that is not included in the data related to the cause candidate disease.

[0055] When an instruction to create a definitive analysis report is input, the analysis report confirmation unit 230 of the user terminal 200 transmits the clinical test result data and the data on the candidate causative disease corrected in S17 to the medical support device 100 as post-confirmation analysis report data 40. If no correction is made in S17, the clinical test result data and the data on the candidate causative disease included in the analysis report screen data 31 received from the medical support device 100 are included as they are in the post-confirmation analysis report data 40.

[0056] When the definitive analysis report creation section 140 receives the post-confirmation analysis report data 40 from the user terminal 200, it creates a definitive analysis report 50 based on the received post-confirmation analysis report data 40 and stores it in the definitive analysis report DB 155 (S18). The definitive analysis report is stored in the definitive analysis report DB 155 in association with a report number for identifying the definitive analysis report, a patient name, a medical record number, an analysis method, a file name, a creation date and time, a creation status, and the like.

[0057] The definitive analysis report creating section 140 transmits the definitive analysis report 50 created in S18 to the user terminal 200, and the display section 240 displays the received definitive analysis report 50 (S19). The definitive analysis report 50 will be described in detail later.

[0058] The procedure for creating a definitive analysis report 50 from the clinical test result data 20 of a blood test by the medical support system 1 will be described with reference to Figs. The clinical test result data 20 is a text file obtained from the clinical test result report 10 by the above-mentioned clinical test result data creation unit 220 , and is stored in a folder of the user terminal 200 .

[0059] First, clinician D starts up the medical support system 1 on his / her own terminal (user terminal 200), and displays an analysis report creation initial screen shown in Fig. 9 on the display unit 240. As shown in the figure, a "Create new report" button and a list of existing reports are displayed on the analysis report creation initial screen. The list of existing reports displays a report number that identifies the analysis report, the patient name, the patient's chart number at clinician D's hospital, the analysis method, a file name arbitrarily set by clinician D, the date and time of the analysis report creation, and the analysis report creation status, and can be sorted by any item.

[0060] The analysis method is an analysis method performed on the clinical test result report 10, and is determined according to the test contents of the clinical test result report 10. In this procedure, since the clinical test result report 10 is a blood test, blood nutrition analysis is performed. The creation status is the creation status of the analysis report, and an analysis report that has not yet been confirmed by clinician D is displayed as “Unconfirmed”, while an analysis report that has been confirmed but not downloaded to the user terminal 200 is displayed as a “Download button” prompting downloading.

[0061] Clinician D presses the Create New Report button when creating a new analysis report. When making a definitive diagnosis or amending the contents of an analysis report whose creation status has not been confirmed, he selects the target analysis report and presses the Download button for selected items. The Download button for selected items becomes available for pressing once an analysis report is selected. When downloading an analysis report that has already been created, he presses the Download button displayed in the creation status of the target analysis report.

[0062] When the Create New Report button is pressed, the report creation confirmation screen shown in Figure 10 is displayed. As shown in the figure, the report creation confirmation screen has input fields for the analysis method, the analysis source file, and the patient name. In the input field for the analysis method, the analysis methods available in the medical support system 1 are displayed in a pull-down menu or the like, and the clinician D selects and inputs one of them. Note that the frequently used blood nutrition analysis may be displayed by default.

[0063] The clinical test result data 20 selected by the clinician D is input into the input field of the analysis source file. Specifically, when the clinician D presses the back button, a file selection screen (not shown) displaying a specified folder is displayed. A specified folder in the user terminal 200 is displayed on the file selection screen, and when the clinician D selects the clinical test result data 20 from the displayed folder, the screen returns to the report creation confirmation screen, and the selected clinical test result data 20 is input into the input field of the analysis source file. If the clinical test result data 20 is not in the specified folder, the clinician D performs an operation to change the folder, and the folder containing the clinical test result data 20 is displayed on the file selection screen.

[0064] In the patient name input field, clinician D inputs the patient name. If the medical support system 1 is linked to the hospital's electronic medical record system, when the patient name is input, the medical record number of that patient name is displayed, and when clinician D confirms it, the clinical test result data 20, the patient name, and the medical record number are linked. It is also possible to display previously entered patient names in a pull-down menu or the like in the patient name input field, and clinician D can select and input from there.

[0065] Then, on the report creation confirmation screen, when the input fields for the analysis method, analysis source file, and patient name are filled in, the analysis start button becomes available for pressing. When the analysis start button is pressed by clinician D, the analysis method, clinical test result data 20, and patient name are transmitted to medical support device 100.

[0066] When the medical support device 100 acquires the analysis method, the clinical test result data 20, and the patient name from the user terminal 200, the processes of S12 to S15 in Fig. 4 are executed. When the medical support device 100 starts the process of S12, it transmits the progress status of the process as a percentage progress status value to the user terminal 200 at any time. The display unit 240 of the user terminal 200 displays a pop-up screen showing the received progress status value on the report creation confirmation screen. The progress status value displayed on the pop-up screen may be a number, a line graph, or a pie chart.

[0067] In response to receiving a progress status value of 100% indicating that processing has been completed from the medical support device 100, the display unit 240 of the user terminal 200 displays a notification screen shown in FIG. 11 , which prompts the user to check the analysis report and make a definitive diagnosis. As shown in the figure, the notification screen displays the report number of the analysis report created by the medical support device 100, the patient name, operations on the analysis report, a confirmation check indicating the status of the analysis report, and a button to create a PDF of the analysis report. When the confirmation of the analysis report is completed, the confirmation check indicates that the analysis report has been confirmed, and when the confirmation of the analysis report is not completed, the button to check later cannot be pressed. The button to create a PDF cannot be pressed until the confirmation of the analysis report is completed, and the analysis report cannot be created at this point. When clinician D presses the confirm / edit button in the operation display field, the screen transitions to the pre-output confirmation screen shown in FIG.

[0068] As shown in the figure, the pre-output confirmation screen displays a button to display an analysis result screen based on the analysis report, a button to display a diagnosis result screen, a button to display a screen of medications and supplements currently being taken, a button to display a prescription screen, and a button to display a screen of comments from the doctor. In this embodiment, the analysis result screen, diagnosis result screen, screen of medications and supplements currently being taken, prescription screen, and screen of comments from the doctor are pop-up screens, but may be displayed on the same screen by screen transition. The pre-output confirmation screen also displays a checkbox to mark these five items as confirmed after they have been confirmed, as well as a "Return to List" button to return to the initial analysis report creation screen shown in Figure 9.

[0069] Clinician D displays the analysis results screen, diagnosis results screen, medications and supplements currently being taken screen, prescription screen, and comments from the patient's doctor screen, and confirms and corrects the contents.

[0070] When the analysis result button is pressed on the pre-output confirmation screen, the display unit 240 of the user terminal 200 displays the analysis result screen shown in Fig. 13 based on the analysis result screen data of the analysis report data. As shown in the figure, the analysis result screen displays a list of analysis results in which the test item name, reference value, appropriate range, numerical value of the test result, and unit are listed.

[0071] In the case of blood tests in this procedure, the test items are white blood cell count, red blood cell count, hemoglobin, hematocrit, MCV (mean corpuscular volume), MCH (mean corpuscular hemoglobin), MCHC (mean corpuscular hemoglobin concentration), platelets, reticulocytes, eosinophils, neutrophils, lymphocytes, Fe (serum iron), TIBC (total iron binding capacity), ferritin, blood glucose, HbAlc (hemoglobin Alc), insulin, glycoalbumin, 1.5AG, total protein, A / G ratio, albumin, GOT (AST), GPT (ALT), γGTP, ALP, LDH, These are lysyl esterase, CPK, amylase, BUN (urea nitrogen), creatinine, uric acid, Cl (chloride), Zn (zinc), Cu (copper), triglycerides, LDL cholesterol, TSH (thyroid-stimulating hormone), FT3 (triiodothyronine), FT4 (thyroxine), CRP, homocysteine, 25(OH)2 vitamin D3, pepsinogen I, PGI / PGII ratio, NEFA, Helicobacter pylori antibody, basophil count, HOMA-R, indirect bilirubin, CaxP, GOT (AST)-GPT (ALT).

[0072] Clinician D can check the numerical values ​​of each test item along with the reference values ​​and appropriate ranges on the analysis results screen.

[0073] When the diagnosis result button is pressed on the pre-output confirmation screen, the display unit 240 of the user terminal 200 displays the diagnosis result screen shown in Figs. 14 and 15 based on the diagnosis result screen data of the analysis report data. As shown in the figures, the diagnosis result screen displays a list of possible causative diseases and the determination result ("positive" or "suspected"). The determination result is initially "positive". Clinician D can then change the determination result from "positive" to "suspected", and in the figures, this can be changed using a radio button.

[0074] As shown in FIG. 14, it is preferable that causative diseases with a status of "negative" not be displayed on the diagnosis result screen that is the screen for clinician D to confirm. If causative diseases with a status of "negative" are also displayed, the number of candidate causative diseases displayed will be too large, and clinician D will have more items to check, which may lead to overlooking something. Clinician D can change the settings to display causative diseases with a status of "negative". Furthermore, with the medical support device 100, clinician D can also add causative diseases that are determined to have a status of "negative" as "positive" or "suspected".

[0075] When you click on each possible causative disease on the diagnosis result screen, the comment column will be expanded and displayed as shown in Figure 15. When you click on the possible causative disease again, the expanded comment column will be collapsed and the display will return to the possible causative disease and status. The comment column is linked as tabs for the result comment column, dietary advice column, daily actions column, and test item column, and you can switch the display by clicking the tabs.

[0076] In this procedure, each of the result comment field, dietary advice field, daily behavior field, and test item field is composed of a title input field and a body text input field. In the result comment field, data related to the disease included in the diagnosis result screen data and acquired from the report data DB 154 is displayed by default. In the dietary advice field, the <diet> data included in the diagnosis result screen data and acquired from the analysis logic DB 153 is displayed by default. In the daily behavior column, the <daily behavior> data included in the diagnostic test result data and obtained from the analysis logic DB 153 is displayed by default. In the examination item column, data extracted from the analysis result screen data regarding the examination items included in the diagnosis result screen data and used to determine the causative disease acquired from the analysis logic DB 153 is displayed.

[0077] Clinician D can modify, that is, change or add to, the result comment column, dietary advice column, and daily behavior column. The comments prepared in advance and stored in the medical support device 100 are based on a large amount of data and are applicable in many cases, but are not necessarily optimal for individual patients. Therefore, it is essential to place the utmost importance on the comments of clinician D who is directly involved with patient P.

[0078] The comment section is categorized into themes that correspond to the format of the final report presented to the patient, such as result comments, dietary advice, daily activities, and test items. This allows the comments entered by Clinician D to be written in the final report along with the default comments in accordance with the thematic classification.

[0079] When the Medications and Supplements button is pressed on the pre-output confirmation screen, the display unit 240 of the user terminal 200 displays the currently taken medications and supplements screen shown in FIG. 16. As shown in the figure, the currently taken medications and supplements screen displays an input field for the currently taken medications and supplements. In the input field, clinician D may input the medications and supplements the patient is currently taking by referring to the medication notebook brought by the patient, or the input may be automatically made by linking with an electronic medical record system or a medication notebook app via API. When the currently taken medications and supplements are entered in the input field, clinician D presses the save button to save it.

[0080] When the prescription button is pressed on the pre-output confirmation screen, the display unit 240 of the user terminal 200 displays the prescription screen shown in Fig. 17. As shown in the figure, the prescription screen displays a list of medicine and supplement names based on the supplement information included in the diagnosis result screen data, and when a medicine or supplement name is clicked, an input field is expanded. When the medicine or supplement name is clicked again, the input field is collapsed and the display returns to showing only the medicine or supplement name. Clinician D can delete the names of medications and supplements displayed on the prescription screen, and can also add names of medications and supplements that are not displayed.

[0081] In this procedure, the input fields consist of the name of the medicine or supplement, the purpose of taking it, the symptoms to be treated with the medicine or supplement, the timing of taking the medicine, the dosage, the unit of dosage, and an input field for entering notes by Clinician D. Since the active ingredient and generic name are entered by default in the input field for the name of the medicine or supplement, Clinician D can change it to the product name to be prescribed and add detailed information such as the dosage and the shape (e.g., tablet). The input fields for the name of the medication / supplement and the symptoms to be treated by the medication / supplement are filled in by default with the suspected causative disease included in the diagnosis result screen data, so in the case of a medication / supplement that is effective against multiple suspected causative diseases, Clinician D modifies the fields to add the suspected causative disease.

[0082] When the comment from the attending physician button is pressed on the pre-output confirmation screen, the display unit 240 of the user terminal 200 displays a comment from the attending physician screen shown in Fig. 18. As shown in the figure, the comment from the attending physician screen displays an input field for clinician D to input comments, and clinician D writes a general comment on the analysis results and presses the save button to save it.

[0083] When Clinician D has confirmed and corrected the content of the analysis results screen, diagnosis results screen, medications / supplements being taken screen, prescription screen, and comments from the doctor screen, the checkboxes on the pre-output confirmation screen shown in Figure 12 are checked. Clinician D then presses the Return to List button to return to the notification screen shown in Figure 11, and after checking the checkbox that reads "This will be created with the understanding that legal responsibility rests with the doctor," he or she will be able to press the button to create a PDF.

[0084] When the clinician D presses a button for creating a PDF, the analysis report is confirmed and edited by the clinician D and is transmitted to the medical support device 100. The medical support device 100 creates a definitive analysis report 50 based on the received edited analysis report (post-confirmation analysis report data 40) and transmits it to the user terminal 200. The medical support device 100 sets the file name of the definitive analysis report 50 to, for example, "report creation date_patient name_analysis method.pdf."

[0085] When the user terminal 200 receives the definitive analysis report 50, the file name of the definitive analysis report 50 is displayed on the analysis report creation initial screen shown in Fig. 9, and a download button is displayed in the creation status. When clinician D presses the download button, the definitive analysis report 50 is downloaded and can be displayed on the display unit 240 or output to a printer or the like.

[0086] The definitive analysis report 50 is composed of a cover page, an overview of the analysis method of the test data, the test results, prescription drugs and supplements, a summary of the test results, a treatment roadmap, and advice. The formats for the cover page and the overview of the analysis method of the test data are stored in advance in the report data DB 154 of the medical support device 100, and are selected and set based on the patient name and analysis method input on the report creation confirmation screen.

[0087] FIG. 19 is an example of the test results presented in a report. In this embodiment, 27 disease determinations are made in one blood test, with "positive" displayed in red, "suspected" in orange, and "negative" in light gray. In the test results seen by the patient, items determined to be "negative" as a result of the test are also displayed in gray, so that the patient can also know items that are not suspected of being a disease. In addition, each disease is listed separately in each block, and within the block, the test results that led to the diagnosis of that disease are displayed together with numerical values.

[0088] Figure 20 is an example of a prescription drug and supplement presentation. Because the prescription input screen for clinicians is linked to the disease, the report for the patient can also list the disease, its cause, and the drugs and supplements prescribed to treat it. This allows the patient to easily understand why they are taking the medicine, forming informed consent and motivating them to continue taking the medicine.

[0089] Figure 21 is an example of a test result summary presented in the definitive analysis report 50. The test result summary uses a treatment pyramid showing the treatment content and treatment order to present a treatment frame to the patient, making it easier to understand the treatment overview. The treatment pyramid shown in the figure is a fundamental treatment pyramid for treating the root cause, and treatment is basically performed from the bottom up, moving to the upper layers while maintaining the treatment in the lower layers.

[0090] In detail, the summary of the test results displays the treatment pyramid, the root causes of each layer of the treatment pyramid, the corresponding tests for the root causes, the diseases that can be diagnosed by the corresponding tests as test results, and the corresponding symptoms for each disease. The test results display diseases that are determined to be "positive" in red, diseases that are determined to be "suspected" in orange, and diseases that are determined to be "negative" in light gray. The treatment pyramid, the root causes of each layer of the treatment pyramid, the corresponding tests for the root causes, and the corresponding symptoms for each disease are stored in advance in report data 154.

[0091] The summary of test results allows the doctor to recognize the treatment frame, root cause, corresponding test, test results, and symptoms in a hierarchical manner, so that the doctor can determine the treatment based on the treatment pyramid, correct comments, etc., and revise the analysis report. In addition, by presenting the treatment frame, root cause, corresponding test, clinical test results, and symptoms in a hierarchical manner to patient P, the doctor can make it easier for the patient to understand the treatment plan.

[0092] Figure 22 is an example of a treatment roadmap created based on the treatment pyramid. As described above, the treatment pyramid basically starts from the bottom and moves to the upper layers while maintaining the treatment of the lower layers, and each layer has a predetermined treatment period. Therefore, the treatment roadmap is created by matching the treatment period with a monthly calendar so that the treatment period starts with the first layer, which is the fundamental treatment, and then moves to the second and third layers. The end of each period is a progress check.

[0093] By sharing such a visualized roadmap between clinician D and patient P, patient P can understand the treatment plan and the position of his or her current treatment in the overall picture, which can contribute to the establishment of informed consent regarding future treatment plans.

[0094] Figure 23 is a presentation example of a medication schedule for patient P corresponding to a treatment roadmap. The medication schedule is displayed in a screen transition or pop-up screen when a treatment period in the treatment roadmap shown in Figure 22 is clicked. The medication schedule shows when medication should be taken for each treatment period at each level of the treatment pyramid: from waking up to before breakfast, before lunch, after lunch, from midday to evening, before dinner, after dinner, and before bedtime.

[0095] The supplements and medicines for the treatment period of each level are identified by comparing the supplements and medicines for the fundamental treatment of each level of the treatment pyramid with the supplements and medicines prescribed to the patient P included in the post-confirmation analysis report data 40, and a medication schedule is created based on the dosage timing set for the identified supplements and medicines. Each medication for the fundamental cause is pre-stored in the report data 154.

[0096] In this way, a medication schedule is automatically created and presented that lists all medications that patient P should take for each treatment period at each tier, indicating when the medication should be taken, such as from waking up until before breakfast. Therefore, even if patient P needs to take multiple medications, there will be no mistake in the medication period or timing.

[0097] (Variation 1) In the above-mentioned embodiment, the biological parameters are numerical values ​​of the test results, but they are not limited to numerical values ​​and may be waveforms or images, for example, electrocardiograms, electroencephalograms, eye movements, echo images, X-ray images, and CT images. In the case of waveforms, for example, the reference range is a reference range of the width or height of the waveform or one or more normal waveforms, and the deviation status is judged as "high", "positive", or "low" based on comparison with these. In the case of images, for example, the reference range is one or more normal images, and the deviation status is judged as "high", "positive", or "low" based on comparison with the normal image. This makes it possible to identify possible underlying diseases from various clinical test results, and improves the accuracy of the identification.

[0098] (Variation 2) In addition, in the above-described embodiment, the interview data, visual examination data, palpation data, percussion data, auscultation data, etc., which are linked to the clinical test result data 20 and transmitted to the medical support device 100, are simply displayed on the display unit 240 of the user terminal 200, but the test results such as the interview data, visual examination data, palpation data, percussion data, auscultation data, etc. may also be used to determine the suspected causative disease in the post-diagnosis support processing unit 130.

[0099] In this case, the clinical test result data acquiring unit 220 extracts clinical test items and test results corresponding to the items from the interview data, visual examination data, palpation data, percussion data, auscultation data, etc., in association with each other, and includes them in the clinical test result data 20. Then, like the biological parameters extracted from the clinical test result report 10, it executes post-diagnosis support processing to determine the deviation status of the test results and determine the cause candidate disease based on the disease determination conditions. This allows for improved accuracy in determining possible causative diseases by taking into account the results of a doctor's examination as well.

[0100] Although the present invention has been described above using the embodiments, it goes without saying that the technical scope of the present invention is not limited to the scope described in the above embodiments. It is clear to those skilled in the art that various modifications or improvements can be made to the above embodiments. In addition, it is clear from the claims that such modifications or improvements can also be included in the technical scope of the present invention. In the above embodiments, the present invention has been described as a medical support system as an invention of a product, but it can also be considered as an invention of a method executed by the medical support system in the present invention, or a program that causes the medical support system to function as various means. [Explanation of symbols]

[0101] 1 Medical Support System 100 Medical Support Equipment 110 Communications Department 120 Diagnostic support preprocessing unit 130 Diagnostic support post-processing unit 140 Final Analysis Report Preparation Department 150 Storage section 200 User terminals 210 Communications Department 220 Clinical Test Results Data Acquisition Department 230 Analysis Report Verification Department 240 Display section 250 User memory section

Claims

1. a reference range storage unit for recording a plurality of clinical test items of a biological sample and reference ranges of the clinical test items; an analysis logic storage unit that selects one or more clinical test items for each disease to be diagnosed from the plurality of clinical test items, and records the selected clinical test items in combination with deviations from the reference range; a clinical test result data acquiring unit that acquires clinical test result data in which the plurality of clinical test items are associated with parameters that are test results of the clinical test items; a diagnostic support preprocessing unit that compares the acquired parameters with the reference ranges for each of the clinical test items and determines whether the parameter values ​​deviate from the reference ranges; a post-diagnosis support processing unit that determines whether the deviation status determined for each clinical test item satisfies a combination of deviation statuses of clinical test items of the disease stored in an analysis logic storage unit, and if so, determines the possible disease as a candidate cause disease; Equipped with A medical support system that identifies the disease by presenting the suspected causative disease to a doctor and receiving confirmation of the diagnosis from the doctor.

2. The medical support system according to claim 1 , wherein the biological sample includes at least one of blood, hair, urine, sweat, saliva, DNA, and feces.

3. The analysis logic storage unit records comment information to be presented to a patient for each of the diseases, The medical support system according to claim 1 , further comprising an analysis report creation unit that creates an analysis report in which the comment information acquired from the analysis logic storage unit for the identified disease is associated with the identified disease.

4. The analysis logic storage unit records prescription information required for a patient for each of the diseases, The medical support system according to claim 3 , wherein the analysis report creating unit includes the prescription information associated with the identified disease in the analysis report.

5. The medical support system according to claim 4 , further comprising an analysis report confirmation unit for allowing the doctor to confirm and correct the analysis report.

6. The analysis logic storage unit records a treatment pyramid indicating the contents and sequence of treatment, root causes of each layer of the treatment pyramid, corresponding tests for the root causes, the clinical test items included in the corresponding tests, and symptoms of the disease; The medical support system according to claim 3 , wherein the analysis report creation unit includes in the analysis report a test result summary in which the treatment pyramid, the root cause, the corresponding test, the disease identified based on the clinical test result data of the corresponding test, and the symptoms are presented in a hierarchical manner.

7. The analysis logic storage unit records the treatment duration of each tier of the treatment pyramid; The medical support system according to claim 6 , wherein the analysis report creation unit includes in the analysis report a treatment roadmap indicating a treatment plan for the patient created based on the treatment pyramid and a treatment period of the treatment pyramid.

8. The analysis logic storage unit records drugs corresponding to fundamental treatments at each level of the treatment pyramid; The medical support system according to claim 7, wherein the analysis report creation unit includes in the analysis report a medication schedule created for each treatment period of each hierarchical level based on the medication and prescription information recorded for each hierarchical level in the analysis logic memory unit.

9. 2. The medical support system according to claim 1, wherein the clinical test result data acquisition unit acquires clinical test result data arranged in a predetermined order of clinical test items by associating the plurality of clinical test items with the parameters which are the test results of the clinical test items through OCR processing using a report format for each clinical testing institution from a clinical test result report which is not electronic data in tabular format.

10. 2. The medical support system according to claim 1, wherein the clinical test result data acquisition unit acquires clinical test result data arranged in a predetermined order of clinical test items from a clinical test result report, which is electronic data in tabular format, by associating the plurality of clinical test items with the parameters which are the test results of the clinical test items.

11. a customization storage unit for recording the reference range customized by the doctor in association with the clinical test item; The medical support system of claim 1 , wherein when reference ranges are recorded in both the reference range memory unit and the customization memory unit, the diagnostic support pre-processing unit uses the reference range in the customization memory unit to compare with the acquired parameters.

12. 4. The medical support system according to claim 3, wherein the analysis report creation unit includes in the analysis report, as an unlikely disease, a disease in which the deviation status determined for each clinical test item in the diagnostic support post-processing unit does not satisfy a combination of deviation statuses of the clinical test items of the disease stored in the analysis logic storage unit.

13. a reference range storage unit for recording a plurality of clinical test items of a biological sample and reference ranges of the clinical test items; an analysis logic storage unit that selects one or more clinical test items for each disease to be diagnosed from the plurality of clinical test items, and records the selected clinical test items in combination with deviations from the reference range; acquiring clinical test result data in which the plurality of clinical test items are associated with parameters that are test results of the clinical test items; comparing the acquired parameters with the reference ranges for each of the clinical test items and determining whether the parameters deviate from the reference ranges; determining whether the deviation status determined for each clinical test item satisfies a combination of deviation statuses of clinical test items of the disease stored in an analysis logic storage unit, and if so, determining the possible disease as a candidate cause disease; Including, A medical support method for identifying a disease by presenting the candidate causative disease to a doctor and receiving a diagnosis confirmation from the doctor.

14. Medical support system, a reference range storage unit for recording a plurality of clinical test items of a biological sample and reference ranges of the clinical test items; an analysis logic storage unit that selects one or more clinical test items for each disease to be diagnosed from the plurality of clinical test items, and records the selected clinical test items in combination with deviation conditions from the reference range; a clinical test result data acquiring unit that acquires clinical test result data in which the plurality of clinical test items are associated with parameters that are test results of the clinical test items; a diagnostic support pre-processing unit that compares the acquired parameters with the reference ranges for each of the clinical test items and determines whether the parameter values ​​deviate from the reference ranges; a post-diagnosis support processing unit that determines whether the deviation status determined for each clinical test item satisfies a combination of deviation statuses of clinical test items of the disease stored in an analysis logic storage unit, and if so, determines the possible disease as a candidate cause disease; A program that functions as a

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