JP5818321B2 - Medical examination information analysis system and operation method of medical examination information analysis system - Google Patents

Description

  The present invention relates to a system for analyzing a result of a medical examination.

  Organizations such as companies and health insurance associations (hereinafter abbreviated as health insurance) sign contracts with health examination implementation organizations (hereinafter abbreviated as health examination organizations) to check the health of employees and insured members. Has been implemented. For this reason, each organization pays the cost of the medical examination of the members to the medical examination organization.

  The medical examination organization reports the results of the medical examination to the examinee, the client organization charges the medical examination fee, provides data for reporting to the government office, and the data necessary for the customer organization's own health management activities. ing.

  Companies and organizations such as health insurance are required to utilize health checkup information in order to maintain the health of members. In addition, in order to maintain and expand the contracts for health checkups of client organizations, it is necessary for health checkup organizations to support health maintenance and promotion activities in customer organizations by analyzing and utilizing the health checkup information held. Yes.

  As a technology for analyzing and utilizing health checkup information, a method for obtaining health based on a calculation formula arbitrarily set from items of health checkup information, and estimating future health care costs from the relationship between past health levels and current health care costs And a method for estimating a difference in medical expenses depending on the presence or absence of an intervention service has been proposed (see, for example, Patent Document 1).

  In addition, a method has been proposed in which the medical examination information is used to calculate the disease incidence based on a predetermined formula for calculating the disease incidence, predict the likely disease, and select the recommended test items for the individual. (For example, refer to Patent Document 2).

JP 2004-341611 A JP 2008-77603 A

  The main problems of the invention disclosed in this specification are as follows.

  When a medical examination organization reports the results of a medical examination to a customer organization, in addition to the individual medical examination results of people belonging to the customer organization, whether the health examination results as a group are good or bad, It is required to clearly show whether it is improving or worsening.

  For example, items with good results or items that have improved are encouraged by the group's health maintenance activities and employees' efforts to improve their willingness to receive medical examinations continuously. Appealing the effectiveness of a health checkup can be a motivation to maintain a health checkup contract.

  In addition to the fact that items with poor results and those that have deteriorated were discovered through medical examinations, the medical examination was conducted by appealing the necessity of examinations, such as reducing the cost for treatment of diseases found in this examination. Can be a motivation to maintain the contract.

  However, when judging whether the results of health examinations are good or bad as a group, the criteria differ depending on the unit and abnormality standards depending on the health examination items, and the average proportion of abnormal persons varies depending on the disease. It is required to prioritize pass / fail for each item from a plurality of medical examination items and diseases.

  For example, Patent Document 1 describes a method for obtaining a health level from a plurality of medical examination items, a method for estimating a medical cost from a relationship between a health level and a medical cost, and a relationship between an intervention and a medical cost. However, the estimation of medical expenses described in Patent Document 1 is mainly intended to evaluate the effects of intervention services and to select intervention subjects.

  In addition, if a medical cost related to a medical examination item, a medical cost related to a disease, and the like can be estimated, a method of prioritizing according to the estimated medical cost can be considered. However, because medical expenses vary depending on the type and symptoms of the disease, the medical expenses are high, but it is difficult to deal with as a group because the number of people is small, and diseases that do not have a large number of medical expenses but require many countermeasures. There are issues that cannot be done.

A typical example of the invention disclosed in the present application is as follows. That is, a health examination information analysis system for analyzing a test result of a medical examinee obtained by a health check, and classifying the test result of a target group composed of persons belonging to a group to be evaluated within a predetermined range A target group distribution creation unit that creates a distribution of the number of people for each hierarchy, and a reference group distribution creation unit that creates a distribution of the number of people for each of the test results of a reference group composed of people who do not belong to the target group And a distribution comparison unit that compares the distribution of the target group and the distribution of the reference group, and calculates a difference in the number of persons whose test results are worse than a predetermined reference value, and based on the difference in the number of persons, An output unit for ranking and outputting.

  According to the exemplary embodiment of the present invention, it is possible to more accurately and easily indicate whether the medical examination result of the target group is good or bad.

It is a block diagram which shows the hardware constitutions of the medical examination information analysis system of the 1st Embodiment of this invention. It is a figure explaining the structure of the data stored in the medical examination information management part 121 of the 1st Embodiment of this invention. It is a figure explaining the structure of the data stored in the personal information management part 122 of the 1st Embodiment of this invention. It is a figure explaining the structure of the data stored in the group information management part 123 of the 1st Embodiment of this invention. It is a figure explaining the structure of the data stored in the reference value management part 124 of embodiment of this invention. It is a figure explaining the structure of the data stored in the background factor item management part 125 of the 1st Embodiment of this invention. It is a figure explaining the structure of the data stored in the parameter | index management part 126 of the 1st Embodiment of this invention. It is a figure explaining the structure of the data stored in the non-variable item management part 127 of the 1st Embodiment of this invention. It is a figure explaining the structure of the data stored in the contract item management part 128 of the 1st Embodiment of this invention. It is a flowchart of the subject item extraction process of the 1st Embodiment of this invention. It is a flowchart of the index calculation process of the 1st Embodiment of this invention. It is a flowchart of the object organization distribution creation process of the 1st Embodiment of this invention. It is a flowchart of the reference population distribution creation process of the 1st Embodiment of this invention. It is a flowchart of the distribution comparison process of the 1st Embodiment of this invention. It is a figure explaining the specific example of the background factor adjustment process of the 1st Embodiment of this invention, and shows the number distribution of the index value of the object organization calculated in step S133 of object organization distribution creation processing. It is a figure explaining the specific example of the background factor adjustment process of the 1st Embodiment of this invention, and shows the number distribution according to the combination of the background factor adjustment item of the object organization calculated by the object organization distribution creation process. It is a figure explaining the specific example of the background factor adjustment process of the 1st Embodiment of this invention, and shows the number distribution according to the combination of the background factor of the reference group calculated in step S142 of a reference group distribution creation process. It is a figure explaining the specific example of the background factor adjustment process of the 1st Embodiment of this invention, and shows the number distribution according to the combination of the background factor of the adjusted reference group calculated by the reference group distribution creation process. It is a figure explaining the specific example of the background factor adjustment process of the 1st Embodiment of this invention, and shows the number distribution before adjustment according to the combination of the background factor and index value layer of a reference group. It is a figure explaining the specific example of the background factor adjustment process of the 1st Embodiment of this invention, and shows the number distribution after adjustment according to the combination of the background factor and index value layer of a reference group. It is a figure explaining the specific example of the background factor adjustment process of the 1st Embodiment of this invention, and shows the number distribution before adjustment according to the hierarchy of the index value of a reference group. It is a figure explaining the specific example of the background factor adjustment process of the 1st Embodiment of this invention, and shows the number distribution after adjustment according to the hierarchy of the index value of a reference group. It is a figure explaining the specific example of the background factor adjustment process of the 1st Embodiment of this invention, and shows the difference in the number of persons according to the hierarchy of the index value of a target group and the adjusted reference group. It is a figure explaining the specific example of the background factor adjustment process of the 1st Embodiment of this invention, and shows the difference in the number of people of an object group and the reference group after adjustment. It is a figure explaining the display of the analysis result of the number of relative abnormal persons derived | led-out by the medical examination information analysis system of the 1st Embodiment of this invention. It is a figure explaining the display of the analysis result of the number of relative abnormal persons derived | led-out by the medical examination information analysis system of the 1st Embodiment of this invention. It is a flowchart of the change calculation process of the 1st Embodiment of this invention. It is a flowchart of the change calculation process of the 1st Embodiment of this invention. It is a figure explaining the display of the analysis result of the number of relative abnormal persons derived | led-out by the medical examination information analysis system of the 1st Embodiment of this invention. It is a flowchart of another example of the distribution comparison process of the 1st Embodiment of this invention. It is a figure explaining the display of the analysis result of the number of unexamined persons derived | led-out by the medical examination information analysis system of the 1st Embodiment of this invention. It is a figure explaining the display of the analysis result of the number of unexamined persons derived | led-out by the medical examination information analysis system of the 1st Embodiment of this invention. It is a flowchart of the recommended medical examination item extraction process of the 1st Embodiment of this invention. It is a flowchart of the recommended medical examination item extraction process of the 1st Embodiment of this invention. It is a figure explaining the display of the analysis result of the recommended medical examination item derived | led-out by the medical examination information analysis system of the 1st Embodiment of this invention. It is a flowchart of the background factor item determination process of the 2nd Embodiment of this invention. It is a block diagram which shows the hardware constitutions of the medical examination information analysis system of the 2nd Embodiment of this invention. It is a figure explaining the structure of the data stored in the improvement program information management part 221 of the 2nd Embodiment of this invention. It is a figure explaining the structure of the data stored in the improvement program log | history management part 222 of the 2nd Embodiment of this invention. It is a figure explaining the structure of the data stored in the improvement program effect management part 223 of the 2nd Embodiment of this invention. It is a flowchart of the improvement program proposal process of the 2nd Embodiment of this invention. It is a figure explaining the display of the cost-benefit analysis result of the improvement program derived | led-out by the medical examination information analysis system of the 2nd Embodiment of this invention.

<Embodiment 1>
FIG. 1 is a block diagram illustrating a hardware configuration of a medical examination information analysis system according to the first embodiment of this invention.

  The medical examination information analysis system of this embodiment includes a server 101, a database 102, and a terminal device 103.

  The server 101 and the database 102 are connected so that the server 101 can access data stored in the database 102. The server 101 and the terminal device 103 are connected via the network 104.

  The server 101 is a computer having an input device 111, an output device 112, a processor (CPU) 113 that executes a program, a memory that stores a program (not shown), a storage device 114, and a communication interface 115.

  The input device 111 is a keyboard, a mouse, or the like, and is an interface that receives input from an administrator. The output device 112 is a display device, a printer, or the like, and outputs a calculation result in a format that can be viewed by an administrator.

  The processor 113 executes a program stored in the memory.

  The memory is a high-speed and volatile storage device such as a dynamic random access memory (DRAM), and stores an operating system (OS) and application programs. When the processor 113 executes the operating system, the basic function of the server 101 is realized, and when the application program is executed, the function provided by the server 101 is realized.

  The communication interface 115 connects the server 101 to a network and controls communication with other devices.

  The storage device 114 is a large-capacity nonvolatile storage device such as a magnetic storage device or a flash memory, and stores a program executed by the processor 113 and data used when the program is executed. That is, the program executed by the processor 113 is read from the storage device 114, loaded into the memory, and executed by the processor 113.

  Specifically, the storage device 114 includes a control unit 131, a target group distribution creation unit 132, a reference population distribution creation unit 133, a distribution comparison unit 134, an index value calculation unit 135, a treatment status determination unit 136, an output unit 137, and a background. A program for implementing each part of the factor item management part 138 is stored.

  The control part 131 calls other each part by execution of a predetermined program, and controls the whole operation | movement of the medical examination information analysis system of this embodiment.

  The target group distribution creating unit 132 creates the distribution of the target group index and the background factor item distribution by executing a predetermined program (see FIG. 12).

  The reference population distribution creation unit 133 creates a reference population index distribution and a background factor item distribution by executing a predetermined program (see FIG. 13).

  The distribution comparison unit 134 obtains an area difference in distribution between the target group and the reference group by executing a predetermined program (see FIG. 14).

  The index value calculation unit 135 calculates an index from the medical examination results of persons belonging to the target group or the reference group by executing a predetermined program (see FIG. 11).

  The treatment status determination unit 136 extracts a person who is performing treatment related to the medical examination item from the target group and the reference group by executing a predetermined program.

  The output unit 137 outputs data for displaying the analysis result by the medical examination information analysis system on a display device or printing by a printer by executing a predetermined program.

  The background factor item creation unit 138 generates data of the background factor item management unit 125 (see FIG. 6) by executing a predetermined program (see FIG. 34).

  The database 102 is data for the server 101 to analyze the medical examination information, that is, the medical examination information management unit 121 (see FIG. 2), the personal information management unit 122 (see FIG. 3), and the group information management unit 123 (FIG. 4). Reference value management unit 124 (see FIG. 5), background factor item management unit 125 (see FIG. 6), index management unit 126 (see FIG. 7), non-variable item management unit 127 (see FIG. 8), and contract items. The management unit 128 (see FIG. 9) is stored.

  The server 101 may be physically constructed on one computer, or may be physically constructed on a logical partition configured on one or a plurality of computers.

  Note that the program executed by the processor 113 is provided to the server 101 via a nonvolatile storage medium or a network. For this reason, the server 101 may include an interface for reading a storage medium (CD-ROM, flash memory, etc.).

  The terminal 103 is a computer having a communication interface 141, a processor (CPU) 142 that executes a program, a memory (not shown) that stores the program, an input device 143 and an output device 144, and a storage device (not shown).

  The communication interface 141 connects the terminal 103 to a network and controls communication with other devices.

  The processor 142 executes a program stored in the memory.

  The memory of the terminal 103 is a high-speed and volatile storage device such as a DRAM (Dynamic Random Access Memory), and stores an operating system (OS) and application programs. When the processor 142 executes the operating system, the basic function of the terminal 103 is realized, and when the application program is executed, the function provided by the terminal 103 is realized.

  The input device 143 includes a keyboard, a mouse, a touch panel, and the like, and is an interface that receives input from the user. The output device 144 is a display device, a printer, or the like, and outputs a processing result in a format that can be visually recognized by the user.

  The storage device of the terminal 103 is a large-capacity non-volatile storage device such as a magnetic storage device or a flash memory, and stores a program executed by the processor 142 and data used when the program is executed. That is, the program executed by the processor 142 is read from the storage device, loaded into the memory, and executed by the processor 142.

  The terminal 103 only needs to operate an application (for example, a web browser) that displays a calculation result output from the server 101 and receives an input from the user.

  FIG. 2 is a diagram illustrating the configuration of data stored in the medical examination information management unit 121 according to the first embodiment of this invention.

  The medical examination information management unit 121 is a database in which medical examination information is stored. The medical examination ID 12101, personal ID 12102, consultation date 12103, consultation age 12104, height 12105, weight 12106, BMI 12107, GOT12108, GPT12109, blood glucose level 12110, smoking 12111, snack 1212, exercise 12113, diabetes treatment 12114, dyslipidemia treatment 12115, hypertension treatment 12116, family history 12117, and occupational type 12118.

  The medical examination ID 12101 is identification information for uniquely identifying a medical examination. The personal ID 12102 is identification information that uniquely identifies the examinee. The consultation date 12103 is the date on which the health check was performed. The consultation age 12104 is the age of the examinee on the date of the medical examination.

  The BMI 12107 is an index indicating the degree of obesity of the examinee, and can be calculated from the height 12105 and the weight 12106. GOT12108 and GPT12109 are blood concentrations of the deviating enzyme and represent liver function. The blood glucose level 12110 is a blood glucose level of the examinee. These height 12105, weight 12106, BMI 12107, GOT 12108, GPT 12109, and blood glucose level 12110 are examples of medical examination results obtained by a medical examination, and the medical examination information management unit 121 may include other types of medical examination results. .

  Smoking 12111 indicates whether the examinee has a habit of smoking, snacks 12112 indicates whether the examinee has a habit of snacking (eg, whether or not to eat snacks), and exercise 12113 indicates to the examinee Indicates whether there is an exercise habit (for example, whether there is more or less exercise during one week). These smoking 12111, snack 1212, and exercise 12113 are examples of medical checkup results obtained by medical checkups, and the medical checkup information management unit 121 may include the results of other types of checkups related to lifestyle habits.

  Diabetes treatment 12114 indicates whether the patient is being treated for diabetes, dyslipidemia treatment 12115 is indicative of whether the patient is being treated for dyslipidemia (eg, hyperlipidemia), and hypertension treatment 12116 is Indicates whether the patient is being treated for hypertension. In the illustrated example, “1” is recorded when treatment is in progress. These diabetes treatment 12114, dyslipidemia treatment 12115, and hypertension treatment 12116 are examples of treatment histories obtained by an inquiry in a medical examination, and the medical examination information management unit 121 may include information on other types of treatment histories.

  The family medical history 12117 is the medical history of the family of the examinee, and the occupation type 12118 is the occupation type of the examinee. The medical examination information management unit 121 may include other types of personal information.

  FIG. 3 is a diagram illustrating the configuration of data stored in the personal information management unit 122 according to the first embodiment of this invention.

  The personal information management unit 122 is a database in which information on a medical checkup recipient is stored, and includes data of a personal ID 12201, a name 12202, a gender 12203, a company 12204, a department 12205, a business type 12206, and a region 12207.

  The personal ID 12201 is identification information for uniquely identifying the examinee, and the same value as the personal ID 12102 of the medical examination information management unit 121 is used. The name 12202 is the name of the examinee. The sex 12203 is the sex of the examinee. The company 12204 is identification information of a company where the examinee works. A department 12205 is identification information of a department to which the examinee belongs. The business type 12206 is identification information of the business type in which the examinee works. A region 12207 is identification information of a place where the examinee works.

  FIG. 4 is a diagram illustrating the configuration of data stored in the group information management unit 123 according to the first embodiment of this invention.

  The organization information management unit 123 is a database that stores information on the organization to which the examinee belongs, and includes data of an organization ID 12301, an organization attribute 12302, and a name 12303.

  The organization ID 12301 is identification information that uniquely identifies the organization to which the examinee belongs. The organization attribute 12302 indicates an organization attribute. The name 12303 is the name of the organization.

  In the group information management unit 123 shown in the figure, the group ID 12301 = J0000 is assigned to the group of all examinees.

  FIG. 5 is a diagram illustrating the configuration of data stored in the reference value management unit 124 according to the embodiment of this invention.

  The reference value management unit 124 is a database that stores reference values that are determined to be abnormal in a medical examination, and includes data of items 12401 and a consultation recommendation level 12402. When a medical examination result that satisfies the condition of the consultation recommendation level 12402 is obtained in the item specified in the item 12401, a diagnosis by a doctor is recommended.

  For example, in the illustrated example, the recommended consultation level is not set for BMI, but if the blood glucose level is 126 or higher, a medical institution is recommended, and if the neutral fat is 150 or higher, the consultation is not accepted. Recommended.

  FIG. 6 is a diagram illustrating the configuration of data stored in the background factor item management unit 125 according to the first embodiment of this invention.

  The background factor item management unit 125 is a database that stores background factors, and includes data of item / index 12501, item 1 (12502), item 2 (12503), and item 3 (12504).

  Item / index 12501, medical examination item and evaluation index. Items 1 to 3 (12502 to 12504) are background factors for the medical examination items and evaluation indexes. Background factors are items that affect health checkup items and evaluation indices. For example, the type of job of the examinee and whether the family has a diabetic patient affects the blood glucose level.

  For this reason, when comparing the distribution of test results of groups or groups, it is necessary to align the background factors of groups and members of the group to the same conditions (S141 to S143 in FIG. 13).

  FIG. 7 is a diagram illustrating the configuration of data stored in the index management unit 126 according to the first embodiment of this invention.

  The index management unit 126 is a database in which a method for calculating an index for evaluating and analyzing a medical examination result (for example, a calculation formula and a pointer for calling a function) is stored. , Index value calculation logic 12603 and abnormal value direction 12604 data.

  The evaluation index 12601 is the name of the calculated index. The health check item 12602 is a health check result used for calculation of the evaluation index. The index value calculation logic 12603 is a method for calculating the evaluation index, and for example, a calculation formula and a pointer for calling a function are recorded therein. An abnormal value direction 12604 indicates an abnormal value when the evaluation index is large or an abnormal value when the evaluation index is small.

  For example, the analysis item BMI can be calculated by BMI = weight / (height × height) using the height and weight of the health check result.

  FIG. 8 is a diagram illustrating the configuration of data stored in the non-variable item management unit 127 according to the first embodiment of this invention.

  The non-variable item management unit 127 is a database in which items that cannot be changed by one's own intention among the medical examination items are stored, and includes data of a number 12701 and an item 12702.

  FIG. 9 is a diagram illustrating the configuration of data stored in the contract item management unit 128 according to the first embodiment of this invention.

  The contract item management unit 128 is a database that stores contract details with each group regarding health checkups. The group ID 12801, contract start 12802, contract end 12803, height / weight 12804, blood glucose level 12805, liver function 12806, blood pressure 12807. , Lipid 12808, lung cancer 12809, colon cancer 12810 data.

  The organization ID 12801 is identification information for uniquely identifying the organization to which the examinee belongs, and the same value as the organization ID 12301 of the organization information management unit 123 is used.

  The contract start 12802 and the contract end 12803 indicate the year and month when the health check contract with the organization starts and ends, respectively. Height / weight 12804, blood glucose level 12805, liver function 12806, blood pressure 12807, lipid 12808, lung cancer 12809 and colorectal cancer 12810 are the contents of the health examination, and the contents that people belonging to the group receive are indicated by “1” .

  FIG. 10 is a flowchart of task item extraction processing according to the first embodiment of this invention. In the task item extraction process illustrated in FIG. 10, an item that is a task in the target group in the comparison with the reference group is extracted.

  First, the control unit 131 of the server 101 receives the designation of the target organization input by the user from the input device 143 of the terminal 103 via the communication interface 115 (S101), and receives the data of the designated target organization as the organization information management unit. 123 (S102).

  Thereafter, the control unit 131 selects one analysis item from the acquired data of the target group (S103), and refers to the contract item management unit 128 to confirm whether the target group has contracted for an item necessary for the analysis. (S104).

  As a result, if the target group has not contracted the items necessary for the analysis, the process returns to step S103, and the next analysis item is selected. On the other hand, if the target organization has contracted the items necessary for the analysis, the process proceeds to step S105.

  In step S <b> 105, the index value calculation unit 135 calculates an index value from the health check result of a person belonging to the target group. Details of the index value calculation processing will be described later with reference to FIG.

  Thereafter, the target group distribution creation unit 132 creates the index distribution and the background factor item distribution for the target group based on the calculated index values (S106). Details of the target group distribution creation processing will be described later with reference to FIG.

  Thereafter, data of organizations other than the target organization that have contracted items necessary for analysis is acquired from the organization information management unit 123 as a reference group (S107). The reference group is a population to be compared with the target group, and may be all examinees who have undergone a medical examination, or may be those who have been narrowed down by conditions such as age, occupation, and lifestyle.

  After that, the index value calculation unit 135 calculates an index value from the medical checkup result of people belonging to the reference group. (S108). Details of the index value calculation processing will be described later with reference to FIG.

  Thereafter, the reference group distribution creation unit 133 adjusts the reference group data using the background factors, and creates a distribution of index values (S109). Details of the reference group distribution creation processing will be described later with reference to FIG.

  Thereafter, the distribution comparison unit 134 obtains an area difference between the distribution of the target group and the distribution of the reference group (S110). Details of this distribution comparison processing will be described later with reference to FIG.

  Thereafter, the control unit 131 determines whether the calculation has been completed for all analysis items (S111).

  As a result, if calculation of some analysis items is not completed, the control unit 131 returns to step S103 and selects the next analysis item. On the other hand, if calculation of all the analysis items has been completed, the control unit 131 determines the priority order of the analysis items based on the area difference between the distribution of the target group and the distribution of the reference group (S112).

  FIG. 11 is a flowchart of index value calculation processing according to the first embodiment of this invention. The index value calculation process shown in FIG. 11 is executed by the index value calculation unit 135 of the server 101.

  First, the index value calculation unit 135 acquires items to be analyzed from parameters passed from the task item extraction process (FIG. 10) or the like (S121).

  Thereafter, the index value calculation logic 12603 corresponding to the analysis item 12601 is acquired from the index management information 126 (S122).

  Thereafter, data used in the index value calculation logic is acquired from the medical examination information management unit 121 (S123).

  Then, using the acquired index value calculation logic, an index for the personal data is calculated (S124).

  Finally, it is determined whether the calculation for all members has been completed (S125). As a result, if calculation of some subjects is not completed, the process returns to step S124 to calculate the next subject. On the other hand, if the calculation for all the members has been completed, this process ends.

  FIG. 12 is a flowchart of target group distribution creation processing according to the first embodiment of this invention. This target group distribution creation process is executed by the target group distribution creation unit 132 of the server 101.

  First, an index value of a person belonging to the target group is acquired. The index value is calculated by an index value calculation process (FIG. 11). Further, the background factor adjustment item for the acquired index value is acquired from the background factor adjustment item management unit 125 (S131).

  Next, the maximum value and the minimum value of the index values are acquired, and the interval between the maximum value and the minimum value of the acquired index values is divided by a predetermined number to determine the hierarchy interval (S132). Note that the number of layers may be determined in advance.

  Next, the frequency (number of people) for each layer is calculated for the individual index value (S133).

  Thereafter, the value of the background factor adjustment item acquired in step S131 is acquired from the medical examination information management unit 121 (S134).

  And about the acquired background factor adjustment item, the number of persons according to the combination of background factors is totaled (S135).

  Thereafter, it is determined whether the total of all background factor combinations has been completed for the index to be evaluated (S136). As a result, if the summation of some combinations has not been completed, the process returns to step S135 to sum up the next combination. On the other hand, if the summation of all the combinations has been completed, this process ends.

  FIG. 13 is a flowchart of reference population distribution creation processing according to the first embodiment of this invention. This reference group distribution creation process is executed by the reference group distribution creation unit 133 of the server 101.

  First, index values of people belonging to the reference group are acquired. The index value is calculated by an index value calculation process (FIG. 11). Moreover, the value of the background factor adjustment item for the index value is acquired from the medical examination information management unit 121 (S141).

  Next, with respect to the reference group, the number of persons for each combination of background factors and the number of persons for each combination of background factor and index value layers are tabulated (S142).

Then, by using the following formula, the number of persons for each combination of the background factor of the reference group and the index value layer considering the background factor is calculated (S143).
Number of people by combination of background factors of reference group and index value group x Number of people by combination of background factors of target group / Number of people by combination of background factors of reference group

  Thereafter, it is determined whether all the calculations have been completed (S144). As a result, if some of the calculations are not completed, the process returns to step S143 to perform the next calculation. On the other hand, if all the calculations have been completed, the number of persons is tabulated according to the index value layer (S145), and this process ends.

  FIG. 14 is a flowchart of distribution comparison processing according to the first embodiment of this invention. This distribution comparison process is a process for obtaining an area difference between the distributions of the target group and the reference group, and is executed by the distribution comparison unit 134 of the server 101.

  First, the distribution of the target group created by the target group distribution creation process (FIG. 12) and the distribution of the reference group created by the reference group distribution creation process (FIG. 13) are acquired (S151). The distribution of the target group and the distribution of the reference group are temporarily stored in the buffer area of the storage device 114.

  Next, for the reference group, an index value layer having the maximum number distribution is obtained and set as a layer for starting calculation (S152).

  Then, a value obtained by subtracting the number of people in the index value layer of the reference group from the number of people in the index value layer of the target group is added to the total number of people difference (S153).

  After that, the index value layer is moved one layer in the abnormal value direction (S154).

  Then, it is determined whether the calculation has been completed for all layers in the abnormal value direction (S155). As a result, if a part of the calculation is not completed, the process returns to step S153 to calculate the next layer. On the other hand, if the calculation has been completed for all the layers, the total difference in the number of people is set to the difference between the two groups (S156), and this process is terminated.

  Next, background factor adjustment in the target group distribution creation process and the reference group distribution creation process will be described using a specific example.

  In a specific example, blood glucose level is used, and it is assumed that the background factor of blood glucose level is age and gender, age is stratified by less than 40 and 40 or more, and gender is classified by gender. The number of people used for the explanation is an example, and the number of people belonging to the target group and the number of people belonging to the reference group are 100 people.

  First, the number distribution A (FIG. 15) of the index value of the target group and the number distribution C (FIG. 16) for each combination of the background factor adjustment items of the target group are obtained by the target group distribution creation process. Here, the total number of persons in the target group is substituted into variable B.

  Next, in S142 of the reference group distribution creation process, the number distribution D (FIG. 17) for each combination of background factors of the reference group is obtained. Comparing the number distribution C (FIG. 16) of the target group and the number distribution D (FIG. 17) of the reference group, it can be seen that the number of persons (distribution) for each combination of background factors differs between the target group and the reference group. Here, the total number of reference groups is defined as E.

  As shown in FIG. 18, by adjusting the background factor by the reference group distribution creation process, the number distribution of the reference group after the adjustment of the background factor combination is the number distribution C of the target group by the combination of the background factors of the target group (FIG. 15). ).

  Specifically, in step S142 of the reference group distribution creation process, the number distribution F (FIG. 19) for each combination of the background factor of the reference group and the index value layer is calculated. Thereafter, in step S143, the adjusted number distribution G (FIG. 20) for each combination of the background factor of the reference group and the index value layer is calculated using the following equation.

G = F × (C / B) / (D / E)
In the above equation, F is the number distribution (FIG. 19) according to the combination of the background factor of the reference group and the index value layer, C is the number distribution of the target group (FIG. 16), and B is the background of the target group. The total number of persons for each combination of factors, D is the distribution of the number of persons for each combination of background factors of the reference group (FIG. 17), and E is the total number of persons for the reference group.

  After the calculation of the number distribution according to the combination of the background factor and the index value layer is completed, the number of persons is totaled for each index value hierarchy in step S145 of the reference group distribution creation process. FIG. 21 shows the number distribution of the index values of the reference group before adjustment. In this example, for convenience of explanation, when the number of people is simply summed for each index value layer, the number distribution of the reference group (FIG. 21) is the same as the number distribution of the target group (FIG. 15). .

  The number distribution H of the index values of the reference group after adjustment is shown in FIG. The calculation start layer determined in the distribution comparison process (step S125 in FIG. 14) is a layer having a blood glucose level of 80 to 99.

  Next, in the distribution comparison process (step S153 in FIG. 14), the difference in the number of persons in the index value of the reference group after adjustment is subtracted from the number of persons in the index value of the target group to calculate the difference in the number of persons in both groups. . Then, the calculated difference in the number of people is totaled to obtain an area difference I in the number distribution of both groups (FIG. 23).

  FIG. 24 illustrates the difference in the number of index values between the target group and the adjusted reference group. In this way, the distribution of the reference group changes by aligning the number distribution of the background factors of the reference group with the number distribution of the background factors of the target group.

  Next, an example of an analysis result display method (how to show the calculated area difference) will be described.

  FIG. 25, FIG. 26, FIG. 28, FIG. 30, FIG. 31 and FIG. 33 are diagrams for explaining the display of the analysis result of the relative abnormal number derived by the medical examination information analysis system of the first embodiment of the present invention. It is.

  For example, as shown in FIG. 25, the analysis result is displayed in a bar graph format indicating the number of relative abnormal persons, and in each medical examination item, the number of abnormal persons in the target group is compared with the number of abnormal persons in the reference group. Whether it is more or less is shown by the area of each bar in the graph.

  For example, FIG. 25A shows the ratio of the number of abnormal persons in the target group to the ratio of the abnormal persons in the reference group in “BMI”, “blood glucose level”, and “systolic blood pressure” which are examination items for the medical examination. More, “HDL” indicates that the ratio of the number of abnormal persons in the target group is smaller than the ratio of the number of abnormal persons in the reference group.

  In addition, FIG. 25 (B) shows that, as a result of the inquiry, in the “drinking amount”, “smoking amount”, and “number of snacks”, the ratio of the abnormal number of the target group is larger than the ratio of the abnormal number of the reference group. “Exercise” indicates that the ratio of the number of abnormal persons in the target group is smaller than the ratio of the number of abnormal persons in the reference group.

  Further, FIG. 25C shows that in the disease onset risk, in “diabetes”, “metabolic syndrome”, and “hypertension”, the ratio of the number of abnormal persons in the target group is larger than the ratio of the number of abnormal persons in the reference population. In “abnormal disease”, it indicates that the ratio of the number of abnormal persons in the target group is smaller than the ratio of the abnormal number in the reference group.

  Next, the method for creating the bar graph of the relative abnormal number of persons shown in FIG. 25 will be specifically described according to the flowchart shown in FIG.

  First, in step S101, a certain group (for example, a group whose group ID is J0001 in FIG. 4) is designated.

  Next, in step S102, referring to the personal information management unit 122 (FIG. 3), the personal ID of a person belonging to the group (target group) whose group ID is J0001 is acquired, and the medical examination information of the acquired personal ID is obtained. Obtained from the medical examination information management unit 121 (FIG. 2).

  Next, in step S103, one evaluation index is selected from the index management unit 126 (FIG. 7) (for example, BMI is selected first).

  Next, in step S104, the contract item is acquired from the contract item management unit 128 (FIG. 9), and the medical examination information necessary for calculating the selected evaluation index itself or the selected evaluation index (for example, necessary for calculating the BMI). (Weight and height) are included in the contract items of the target group.

  Next, in step S105 (index value calculation processing (FIG. 11)), the BMI is calculated from the height and weight of the person belonging to the target group according to the index value calculation logic (12603 in FIG. 7) of the index management unit 126.

  Next, in step S106 (target group distribution creation process (FIG. 12)), the distribution of BMI of persons belonging to the target group is obtained. In addition, referring to the background factor adjustment item management unit 125 (FIG. 6), the background factor adjustment item (for example, “job type” for the BMI) of the evaluation index is acquired, and the job type of the acquired personal ID is obtained as the medical examination information. Obtained from the management unit 121 (FIG. 2), and obtains the distribution of BMI for each job type.

  Next, in step S107, referring to the contract item management unit 128 (FIG. 9), the organization ID of the reference group, that is, the other organizations that are contracted to measure the height and weight used in the calculation of BMI. The organization ID (J0002, J0003, J0004...) Is acquired.

  Next, in step S108 (index value calculation processing (FIG. 11)), the heights and weights of persons belonging to the reference group are acquired from the medical examination information management unit 121 (FIG. 2), and the index value calculation logic of the index management unit 126 is obtained. (12603 in FIG. 7) BMI is calculated from the acquired height and weight.

  Next, in step S109 (reference population distribution creation process (FIG. 13)), the calculated BMI distribution is obtained. At this time, with respect to the background factor adjustment item (job type) of the BMI, the distribution of the reference group is adjusted using the distribution for each job type of the target group.

  Thereafter, in step S110 (distribution comparison process (FIG. 14)), an area difference between the BMI distribution of the target group created in step S106 and the BMI distribution of the reference group created in step S109 is calculated.

  Thereafter, in step S111, it is confirmed that the calculation has been completed for all evaluation indexes included in the index management unit 126. If there is an evaluation index that has not been calculated, the process returns to step S103, the next evaluation index (for example, blood glucose level) is selected from the index management unit 126 (FIG. 7), and the processing from step S104 to S110 is repeated.

  After the calculation is completed for all the evaluation indexes, in step S112, for each index (BMI, blood glucose level, etc.), the number of reference groups and the number of target organizations in each layer when the number of people in the worsening direction is positive. Calculate the difference. This is categorized into test items, medical interviews, and disease onset risks, and a graph is displayed in each category in order of the number of people in the target group that are worse than the reference population.

  Also, as shown in FIG. 26, the analysis result can be displayed in the form of a frequency distribution. In the display by frequency distribution, the area of each distribution in the graph indicates how much or how many abnormal people in the target group are, compared with the number of abnormal people in the reference group, in the health check item. Can be shown. In the display using the frequency distribution shown in FIG. 26, the frequency area of the reference group (number of people × section width) and the frequency area of the target group (number of people × width of the section) in the section (layer) represented on the horizontal axis. Thus, it is possible to know how good or bad the target group is with respect to the reference group.

  The frequency distribution shown in FIG. 26 is created by superimposing and displaying the BMI distribution of the target organization created in step S106 and the BMI distribution of the reference group created in step S109.

  The interface for displaying the frequency distribution may display the frequency distribution of the selected item by, for example, clicking a bar graph shown in FIG. 25 and selecting a specific evaluation index.

  For example, FIG. 26A shows the frequency distribution between the target group and the reference group for “BMI”, which is an examination item for medical examination, and the ratio of people with high BMI in the target group is large. You can see that

  FIG. 26 (B) is a frequency distribution for “drinking amount” in an inquiry, and FIG. 26 (C) is a frequency distribution for “diabetes” risk in disease onset risk.

  In addition, the vertical thin broken line in FIG. 26 shows the peak (mode value) of the number of people in the reference group.

  Specifically, in the frequency distribution of FIG. 26, the hierarchy determined in step S132 of the target group distribution creation process (FIG. 12) is set on the horizontal axis, and the number of persons classified by hierarchy determined in step S133 is set on the vertical axis. Then, the frequency distribution of the target group is created. In addition, the frequency distribution of the reference population is created by setting the number of people in each hierarchy determined in step S143 of the reference population distribution creation processing (FIG. 13) on the vertical axis.

  As described above, in the task item extraction process according to the first embodiment, the target group distribution creation unit 132 creates a distribution of the number of health check results and disease-related index values for each target group, and the target. By comparing with the distribution comparison unit 134 the health distribution result and the number distribution of the index values created by the reference group distribution creation unit 133 for the reference group other than the group, each health check result and index value is Whether the result is good or bad for the target group can be clearly shown (FIGS. 25 and 26).

  In particular, since the distribution comparison unit 134 compares the target group and the reference group to determine the number of people in a bad state, it is determined how many people are in a bad state for each health check result and index value. An accurate comparison can be made.

  Further, the reference group distribution creation unit 133 creates a distribution of medical examination results and index values in which the ratio of background factors (for example, gender ratio, percentage by age group, occupation type, etc.) is combined with the target group, and the distribution comparison unit 134 compares the distribution of the reference group with the distribution of the target group. For this reason, it is possible to present whether there are more or fewer people in a bad state than other groups having the same gender ratio, age structure, and occupation as the target group.

  Further, the background factor item management unit 125 manages the relationship between the medical examination result and evaluation value and items (job type, family medical history, etc.) that cannot be changed, and the reference population distribution creation unit 133 The distribution of the reference group with the same factors is created, and the distribution comparison unit 134 compares the distribution of the reference group with the distribution of the target group. As a result, items that cannot be changed by the examinee, such as occupation and family history, can be arranged between the target group and the reference group, and the distribution of the health check items and index values can be more accurately evaluated. .

<Change in number of abnormal people>
Next, processing for calculating a change in the number of abnormal persons in the first embodiment will be described.

  27A and 27B are flowcharts of change calculation processing according to the first embodiment of this invention.

  First, the control unit 131 of the server 101 receives the designation of the target organization and the year to be evaluated input by the user from the input device 143 of the terminal 103 via the communication interface 115 (S161), and the data of the designated target organization is received. Is acquired from the group information management unit 123 (S162).

  After that, the control unit 131 selects one analysis item from the acquired data of the target group (S163), and refers to the contract item management unit 128 to confirm whether the target group has contracted for an item necessary for the analysis. (S164).

  As a result, if the target group has not contracted the items necessary for the analysis, the process returns to step S163 to select the next analysis item. On the other hand, if the target organization has contracted the items necessary for the analysis, the process proceeds to step S165.

  In step S165, the index value calculation unit 135 calculates an index value of a person belonging to the target group from the health check result for the year specified in step S161. The details of the index value calculation process are as shown in FIG.

  Thereafter, the target group distribution creation unit 132 creates a calculated index value distribution and a background factor item distribution for the target group (S166). Details of the target group distribution creation processing are as shown in FIG.

  Thereafter, the index value calculation unit 135 calculates an index value of a person belonging to the target group from the health checkup result of the previous year of the designated year (S167). The details of the index value calculation process are as shown in FIG.

  After that, the reference group distribution creation unit 133 adjusts the data of the previous year of the designated year of the target group using the background factor of the designated year, and creates the index value distribution (S168). Details of the process of creating the distribution of the target group in the previous year of the designated year are as shown in FIG.

  Thereafter, the distribution comparison unit 134 calculates the area difference between the designated year distribution of the target group and the previous year distribution (S169). Details of this distribution comparison processing are as shown in FIG.

  Thereafter, the control unit 131 acquires data of a group (reference group) that contracts items necessary for the analysis from data other than the target group from the group information management unit 123 (S170).

  Thereafter, the index value calculation unit 135 calculates the index value of the person belonging to the reference group from the health check result in the designated year (S171). The details of the index value calculation process are as shown in FIG.

  Thereafter, the reference group distribution creation unit 133 adjusts the data of the designated year of the reference group using the background factors of the target group, and creates the index value distribution (S172). Details of this reference population distribution creation processing are as shown in FIG.

  Thereafter, the index value calculation unit 135 calculates an index value of a person belonging to the reference group from the health checkup result of the previous year of the designated year (S173). The details of the index value calculation process are as shown in FIG.

  After that, the reference group distribution creation unit 133 adjusts the data of the previous year of the designated year of the reference group using the background factor of the designated year, and creates the index value distribution (S174). Details of this reference population distribution creation processing are as shown in FIG.

  Thereafter, the distribution comparison unit 134 obtains an area difference between the distribution of the designated year of the target group and the distribution of the previous year (S175). The details of this distribution comparison processing are as shown in FIG.

  Thereafter, the control unit 131 determines whether the calculation has been completed for all analysis items (S176).

  As a result, if calculation of some analysis items has not been completed, the control unit 131 returns to step S163 and selects the next analysis item. On the other hand, if calculation of all analysis items has been completed, the control unit 131 determines the priority order of the analysis items based on the area difference of the target group and the area difference of the reference group (S177).

  Thereafter, the analysis items are graphed with the area difference of the target group and the area difference of the reference group as axes (S178).

  Further, as shown in FIG. 28, the analysis result can be displayed in the form of a scatter diagram. The display based on the scatter diagram shows the change in the number of abnormal persons between the last year and the current year in the target group and the reference group, for example, as a percentage (or the number of people).

  For example, FIG. 28A is a scatter diagram in which the horizontal axis indicates increase / decrease in the number of abnormal persons in the reference group and the vertical axis indicates increase / decrease in the number of abnormal persons in the target group. The number of abnormal persons may be a ratio to the total number or the number of persons. According to FIG. 28 (A), it can be seen that the number of abnormal blood glucose levels decreases in the target group and increases in the reference population. FIG. 28B and FIG. 28C show the frequency distribution of the number of abnormal persons between the previous fiscal year and the current fiscal year in the target group and reference population regarding blood glucose levels. According to FIG. 28 (B), the number of abnormal blood glucose levels in the target group is lower this year than in the previous fiscal year. According to FIG. 28 (C), the number of abnormal blood sugar levels in the reference group is lower than the previous fiscal year. You can see that this year has increased.

  Furthermore, according to FIG. 28 (A), it can be seen that the number of neutral fat abnormalities increases in the target group and the reference group. Moreover, it turns out that the number of abnormal persons of HDL cholesterol has decreased in the object group and the reference group, and the reduction degree of both is comparable. Moreover, it can be seen that the number of persons with abnormal systolic blood pressure decreases in the target group and the reference group, and the degree of decrease in the reference group is larger.

  Next, the method for creating the scatter diagram of the relative abnormal number of persons shown in FIG. 28A will be specifically described according to the flowcharts shown in FIGS. 27A and 27B.

  First, in step S161, a certain group and a year to be evaluated (for example, a group whose group ID is J0001 in FIG. 4, target year = 2009) are designated.

  Next, in step S162, the personal information management unit 122 (FIG. 3) is referred to, the personal ID of a person belonging to the group (target group) whose group ID is J0001 is acquired, and the target year (2009) of the acquired personal ID Year) medical examination information is acquired from the medical examination information management unit 121 (FIG. 2).

  Next, in step S163, one evaluation index is selected from the index management unit 126 (FIG. 7) (for example, BMI is selected first).

  Next, in step S164, referring to the contract item management unit 128 (FIG. 9), the selected evaluation index itself or the medical examination result necessary for calculating the selected evaluation index (weight and height necessary for the calculation of BMI) is obtained. Check whether it is included in the contract item of the target group.

  Next, in step S165 (index value calculation process (FIG. 11)), according to the index value calculation logic (12603 in FIG. 7) of the index management unit 126, the height and weight of 2009 from those belonging to the target group are calculated. Calculate the BMI.

  Next, in step S166 (target organization distribution creation processing (FIG. 12)), the 2009 BMI distribution of persons belonging to the target organization is obtained. In addition, referring to the background factor adjustment item management unit 125 (FIG. 6), the background factor adjustment item (for example, “job type” for the BMI) of the evaluation index is acquired, and the job type of the acquired personal ID is obtained as the medical examination information. Obtained from the management unit 121 (FIG. 2), and obtains the distribution of BMI for each job type.

  Next, in step S167 (index value calculation processing (FIG. 11)), according to the index value calculation logic (12603 in FIG. 7) of the index management unit 126, the height of the previous year (2008) of the designated year of the person belonging to the target organization And BMI is calculated from the body weight.

  Next, in step S168 (reference population distribution creation processing (FIG. 13)), the calculated 2008 BMI distribution is obtained. At this time, for the BMI background factor adjustment item (job type), the distribution of the target group in 2008 is adjusted using the distribution of the target group for each job type in 2009.

  Thereafter, in step S169 (distribution comparison process (FIG. 14)), the area difference between the 2009 BMI distribution of the target organization created in step S166 and the 2008 BMI distribution of the target organization created in step S168 is calculated. To do.

  Next, in step S170, referring to the contract item management unit 128 (FIG. 9), the organization ID of the reference group, that is, the other organizations that are contracted to measure the height and weight used in the calculation of BMI. The organization ID (J0002, J0003, J0004...) Is acquired.

  Next, in step S171 (index value calculation process (FIG. 11)), according to the index value calculation logic (12603 in FIG. 7) of the index management unit 126, it belongs to the reference group (organizations whose group IDs are J0002, J0003, J0004). Calculate BMI from a person's 2009 height and weight.

  Next, in step S172 (reference population distribution creation process (FIG. 13)), the calculated BMI distribution is obtained. At this time, for the BMI background factor adjustment item (job type), the distribution of the reference group in 2009 is adjusted using the distribution of the target group for each job type in 2009.

  Next, in step S173 (index value calculation process (FIG. 11)), according to the index value calculation logic (12603 in FIG. 7) of the index management unit 126, the height of the previous year (2008) of the designated year of the person belonging to the reference group And BMI is calculated from the body weight.

  Next, in step S174 (reference population distribution creation process (FIG. 13)), the calculated BMI distribution is obtained. At this time, for the BMI background factor adjustment item (job type), the distribution of the reference group in 2008 is adjusted using the distribution of the target group for each job type in 2009.

  Thereafter, in step S175 (distribution comparison process (FIG. 14)), the area difference between the 2009 BMI distribution of the reference group created in step S172 and the 2008 BMI distribution of the reference group created in step S174 is calculated. To do.

  Thereafter, in step S176, it is confirmed that the calculation has been completed for all evaluation indexes (all evaluation indexes included in the index management unit 126). If there is an evaluation index for which calculation has not been completed, the process returns to step S163, the next evaluation index (for example, blood glucose level) is selected from the index management unit 126 (FIG. 7), and the processing of steps S164 to S175 is repeated.

  If the calculation has been completed for all the evaluation indexes, in step S177, the evaluation indexes are ranked based on the difference between the area difference of the target group and the area difference of the reference group.

  Finally, in step S178, the scatter diagram of FIG. 28 (A) is created. Specifically, the horizontal axis shows the number of abnormal persons in the reference group in 2008 and the number of abnormal persons in the reference group in 2008, based on the number of abnormal persons in the reference group in 2008 calculated in step S175 (center). If the number of abnormal persons in 2009 is smaller than the number of abnormal persons in 2008, the difference will be reduced, and if the number of abnormal persons in 2009 is larger than the number of abnormal persons in 2008, the difference will be on the increasing side. Plot for each evaluation index. The vertical axis represents the difference between the number of abnormal persons in the target group in 2009 and the number of abnormal persons in the target group in 2008, based on the number of abnormal persons in the target group in 2008 calculated in step S169. If the number of abnormal persons in the year is smaller than the number of abnormal persons in 2008, it will be on the decrease side, and if the number of abnormal persons in 2009 is larger than the number of abnormal persons in 2008, it will be on the increase side. Plot. At this time, a predetermined number of evaluation indices may be plotted in order from the top in accordance with the ranks assigned in step S177.

  The frequency distribution of the target group shown in FIG. 28B can be created by displaying the distribution of the target group created in step 166 and step 168 in an overlapping manner. Further, the frequency distribution of the reference group shown in FIG. 28C can be created by displaying the reference group distribution created in step 172 and step 174 in an overlapping manner.

  Note that the interface for displaying the frequency distribution (FIG. 28B, FIG. 28C) is, for example, by clicking an index plotted in the scatter diagram shown in FIG. By selecting, the frequency distribution of the selected item may be displayed.

  As described above, in the change calculation process of the first embodiment, the distribution comparison unit 134 compares the distribution of the target group in the previous year with the distribution in the current year, and obtains the difference in the number of people in a bad state. Compare the distribution of the reference group in the previous year with the distribution in the current year, find the difference in the number of people in bad condition, compare the two obtained difference in the number of people (change), and the relationship between these two differences in the number of people Therefore, by evaluating the change in the health checkup result of the target group, the improvement amount of the target group can be evaluated based on the change amount of the reference group.

  For example, in the target group, even if the number of people with high blood pressure decreases, if the amount of change (decrease) in the reference group is worse, the target group is still not improving enough. It can be evaluated that there is a possibility of improvement. In addition, even if the number of people with high triglycerides is increasing, if the reference population is greatly increasing, the number of people with high triglycerides is increasing, but it is suppressed compared to others. Can be evaluated. In this way, it is possible to present to the customer organization in an easy-to-understand manner whether the number of bad people is increasing or decreasing, and whether the increase or decrease is compared with other organizations (FIG. 28).

<Determination of recommended level for consultation>
Next, the consultation recommendation level determination process in the first embodiment will be described. In the consultation recommendation level determination process, a distribution comparison process shown in FIG. 29 is called from the assignment item extraction process (step S110 in FIG. 10) instead of the above-described distribution comparison process (FIG. 14).

  FIG. 29 is a flowchart of another example of distribution comparison processing according to the first embodiment of this invention. The distribution comparison process shown in FIG. 29 is executed by the distribution comparison unit 134, and the distribution of the target group and the distribution of the reference group are compared using the standard value to obtain an area difference between them.

  First, the distribution of the target group created by the target group distribution creation process (FIG. 12) and the distribution of the reference group created by the reference group distribution creation process (FIG. 13) are acquired (S181). The distribution of the target group and the distribution of the reference group are temporarily stored in the buffer area of the storage device 114.

  After that, the index value layer in the distribution determined to correspond to the consultation recommendation level 12402 of the reference value management unit 124 is acquired (S182).

  Then, the number of people in the index value layer of the target group is subtracted from the number of people in the index value layer of the target group, and the calculated number difference is added to the total number of people difference (S183).

  Then, the index value layer is moved one step in the abnormal value direction (S184).

  Thereafter, it is determined whether or not the calculation of all the layers determined to correspond to the consultation recommendation level is completed (S185).

  As a result, if the calculation of some layers is not completed, the process returns to step S183 to calculate the next layer. On the other hand, if the calculation for all the layers has been completed, the sum of the difference in the number of people is taken as the difference between the two groups (S186).

  FIG. 30 is a diagram for explaining a display of the result of analyzing the number of unexamined persons who have not been examined although the test result is at the recommended consultation level.

  For example, as shown in FIG. 30 (A), the relative number of unexamined persons is displayed in a bar graph format, and the number of unexamined persons in the target group is compared with the number of unexamined persons in the reference group in each medical examination item. How much or less is shown by the area of each bar in the graph.

  Further, as shown in FIG. 30B, the relative number of unexamined patients can be displayed in the form of a frequency distribution. The area of each distribution in the graph indicates how many or how many unexamined examinees whose test results exceed the recommended consultation level in the target group, and in which area. In addition, you may display the person under treatment in the form of a bar graph out of distribution.

  Next, a method for creating a bar graph of the number of patients who have not received the recommended consultation level shown in FIG. 30 will be specifically described according to the flowchart shown in FIG.

  First, in step S101, a certain group (for example, a group whose group ID is J0001 in FIG. 4) is designated.

  Next, in step S102, referring to the personal information management unit 122 (FIG. 3), the personal ID of a person belonging to the group (target group) whose group ID is J0001 is acquired, and the medical examination information of the acquired personal ID is obtained. Obtained from the medical examination information management unit 121 (FIG. 2).

  Next, in step S103, the reference value management unit 124 (FIG. 5) is referred to, and one evaluation index for which a consultation recommendation level is set is selected from the index management unit 126 (FIG. 7) (for example, first Select blood sugar level).

  Next, in step S104, the contract item of the target group is acquired from the contract item management unit 128 (FIG. 9), and the selected evaluation index itself or the medical examination result necessary for calculating the selected evaluation index is included in the contract item. Make sure that Specifically, it is confirmed whether the blood glucose level is included in the contract item.

  Next, in step S105 (index value calculation process (FIG. 11)), a blood glucose level is acquired from the acquired medical examination result. Regarding the blood sugar level, since the index value calculation logic (12603 in FIG. 7) of the index management unit 126 is not defined, the medical examination information is used as it is.

  Next, in step S106 (target group distribution creation process (FIG. 12)), the distribution of blood glucose levels of persons belonging to the target group is obtained. Further, referring to the background factor adjustment item management unit 125 (FIG. 6), the background factor adjustment items (“job type” and “family medical history” for the blood glucose level) of the evaluation index are acquired, and the job type of the acquired personal ID and The family medical history is acquired from the medical examination information management unit 121 (FIG. 2), and the distribution of blood glucose levels by job type and family medical history is obtained.

  Next, in step S107, referring to the contract item management unit 128 (FIG. 9), the group ID of the reference group, that is, the group IDs of other groups that have contracted blood glucose measurement (J0002, J0003, J0004). ...) is acquired.

  Next, in step S108 (index value calculation process (FIG. 11)), blood glucose levels of persons belonging to the reference group (group IDs J0002, J0003, J0004) are acquired from the medical examination information management unit 121 (FIG. 2).

  Next, in step S109 (reference population distribution creation process (FIG. 13)), the blood sugar level distribution is obtained. At this time, the distribution of the reference population is adjusted using the distribution for each occupation type and family medical history of the target group with respect to the background factor adjustment items (job types and family medical history) of the blood glucose level. Moreover, information (diabetes treatment 12114) under treatment from the medical examination information management unit 121 (FIG. 2) is acquired, and persons under diabetes treatment are separately counted.

  Thereafter, in step S110 (distribution comparison process (FIG. 29)), the area difference between the blood glucose level distribution of the target group created in step S106 and the blood glucose level distribution of the reference population created in step S109 is calculated. At this time, as the area difference, the area difference is calculated for the recommended consultation level (in blood glucose level, 126 or more) of the reference value management unit (FIG. 5).

  Thereafter, in step S111, it is confirmed that the calculation has been completed for all evaluation indexes included in the index management unit 126. If there is an evaluation index that has not been calculated, the process returns to step S103, the next evaluation index (for example, blood glucose level) is selected from the index management unit 126 (FIG. 7), and the processing from step S104 to S110 is repeated.

  After the calculation is completed for all the evaluation indexes, the number of reference recommended consultation levels and target groups in each group in the case where the number of people in the worsening direction is positive for each index (BMI, blood glucose level, etc.) in step S112. Calculate the difference between the recommended number of people who attended the examination. This is categorized into test items, medical interviews, and disease onset risks, and a graph is displayed in each category in order of the number of people in the target group that are worse than the reference population.

  For example, as shown in FIG. 31, the analysis result can be displayed in the form of a scatter diagram. The display by a scatter diagram shows the change in the number of unexamined persons in the target group and the reference group last year and this year.

  For example, FIG. 31A is a scatter diagram in which the horizontal axis is set to increase / decrease in the number of unchecked patients in the reference group, and the vertical axis is set to increase / decrease in the number of unchecked persons in the target group. The number of unexamined persons may be a ratio to the total number of persons or the number of persons. According to FIG. 31 (A), it can be seen that the number of unvisited blood sugar levels decreases in the target group and increases in the reference group. 31 (B) and 31 (C) show the frequency distribution of the number of unexamined persons in the target group and the reference group regarding blood glucose levels in the previous fiscal year and the current fiscal year. According to FIG. 31 (B), the number of unvisited blood sugar levels in the target group has decreased in the current fiscal year compared to the previous year, and according to FIG. 31 (C), the number of unvisited blood sugar levels in the reference population is It can be seen that this year has increased from last year.

  Furthermore, according to FIG. 31 (A), it can be seen that the number of undiagnosed patients with neutral fat has increased in the target group and the reference group. Moreover, it can be seen that the number of unexamined HDL cholesterol patients has decreased in the target group and the reference group, and the degree of decrease in both is comparable. In addition, it can be seen that the number of patients who have not received systolic blood pressure has decreased in the target group and the reference group, and the degree of decrease in the reference group is larger.

  Next, a method for creating a scatter diagram of the number of unexamined persons shown in FIG. 31A will be specifically described according to the flowcharts shown in FIGS. 27A and 27B. The scatter chart of the number of unexamined persons shown in FIG. 31 (A) is created by the above-described change calculation process (FIGS. 27A and 27B). From step S169 and step S175, the distribution comparison process (FIG. 14) is changed. Instead, the distribution comparison process shown in FIG. 29 is called.

  First, in step S161, a certain group and a year to be evaluated (for example, a group whose group ID is J0001 in FIG. 4, target year = 2009) are designated.

  Next, in step S162, the personal information management unit 122 (FIG. 3) is referred to, the personal ID of a person belonging to the group (target group) whose group ID is J0001 is acquired, and the target year (2009) of the acquired personal ID Year) medical examination information is acquired from the medical examination information management unit 121 (FIG. 2).

  Next, in step S163, the reference value management unit 124 (FIG. 5) is referred to, and one evaluation index with the recommended consultation level is selected from the index management unit 126 (FIG. 7) (for example, first, Select blood sugar level).

  Next, in step S164, referring to the contract item management unit 128 (FIG. 9), the selected evaluation index itself (for example, blood glucose level) or the medical examination result necessary for calculating the selected evaluation index is the contract item of the target group. To check if it is included.

  Next, in step S165 (index value calculation process (FIG. 11)), the blood sugar level for 2009 is acquired from the acquired medical examination information. Regarding the blood sugar level, since the index value calculation logic (12603 in FIG. 7) of the index management unit 126 is not defined, the medical examination information is used as it is.

  Next, in step S166 (target organization distribution creation process (FIG. 12)), the distribution of blood glucose levels in 2009 for people belonging to the target organization is obtained. In addition, referring to the background factor adjustment item management unit 125 (FIG. 6), the background factor adjustment items (“job type” and “diabetes family history” for blood glucose level) of the evaluation index are acquired, and the job type of the acquired personal ID And the diabetes family medical history is acquired from the medical examination information management part 121 (FIG. 2), and the distribution of blood glucose level according to the occupation type of 2009 of a target group and diabetes family medical history is calculated | required.

  Next, in step S167 (index value calculation process (FIG. 11)), the blood glucose level of the previous year (2008) of the specified year is acquired from the acquired medical examination information.

  Next, in step S168 (reference population distribution creation process (FIG. 13)), the distribution of blood glucose levels in 2008 of the target group is obtained. At this time, the distribution of 2008 is adjusted by using the distribution of each factor and family history in 2009 for the background factor adjustment items of the blood glucose level (job type and diabetes family history). Moreover, information (diabetes treatment 12114) under treatment from the medical examination information management unit 121 (FIG. 2) is acquired, and persons under diabetes treatment are separately counted.

  Thereafter, in step S169 (distribution comparison process (FIG. 29)), the area difference between the 2009 blood glucose level distribution of the target group created in step S166 and the 2008 blood glucose level distribution of the target group created in step S168. Calculate

  Next, in step S170, referring to the contract item management unit 128 (FIG. 9), the organization ID of the reference group, that is, the organization ID of another organization that has contracted blood glucose measurement (J0002, J0003, J0004). ...) is acquired.

  Next, in step S171 (index value calculation process (FIG. 11)), the blood glucose level in 2009 of people belonging to the reference group (groups with group IDs J0002, J0003, and J0004) is obtained from the medical examination information management unit 121 (FIG. 2). )

  Next, in step S172 (reference group distribution creation processing (FIG. 13)), the distribution of the 2009 blood glucose level of the reference group is obtained. At this time, the distribution of the reference population in 2009 is adjusted by using the distribution of each subject occupation in 2009 and the family medical history for the background factor adjustment items (job type, diabetes family history) of the blood glucose level.

  Next, in step S173 (index value calculation process (FIG. 11)), the blood glucose level in the previous year (2008) of the designated year of the person belonging to the reference group according to the index value calculation logic (12603 in FIG. 7) of the index management unit 126 The value is acquired from the medical examination information management unit 121 (FIG. 2).

  Next, in step S174 (reference population distribution creation process (FIG. 13)), the distribution of 2008 blood glucose levels of the reference population is obtained. At this time, for the background factor adjustment item (job type) of the blood glucose level, the distribution of the reference group in 2008 is adjusted using the distribution of the target group for each job type in 2009.

  Thereafter, in step S175 (distribution comparison process (FIG. 29)), the area difference between the 2009 blood glucose level distribution of the reference population created in step S172 and the 2008 blood glucose level distribution of the reference population created in step S174. Calculate

  Thereafter, in step S176, it is confirmed that the calculation has been completed for all evaluation indexes (all evaluation indexes included in the index management unit 126). If there is an evaluation index that has not been calculated, the process returns to step S163, the next evaluation index is selected from the index management unit 126 (FIG. 7), and the processing of steps S164 to S175 is repeated.

  If the calculation has been completed for all the evaluation indexes, in step S177, the evaluation indexes are ranked based on the difference between the area difference of the target group and the area difference of the reference group.

  Finally, in step S178, the graph of FIG. 31A is created. Specifically, the horizontal axis shows the number of abnormal persons in the reference group in 2008 and the number of abnormal persons in the reference group in 2008, based on the number of abnormal persons in the reference group in 2008 calculated in step S175 (center). The difference is evaluated so that if the number of abnormal persons in 2009 is smaller than the number of abnormal persons in 2008, it will be on the decreasing side, and if the number of abnormal persons in 2009 is larger than the number of abnormal persons in 2008, it will be on the increasing side. Plot for each indicator. The vertical axis represents the difference between the number of abnormal persons in the target group in 2009 and the number of abnormal persons in the target group in 2008, based on the number of abnormal persons in the target group in 2008 calculated in step S169. Plot for each evaluation index so that if the number of abnormal persons in the year is less than the number of abnormal persons in 2008, it will be on the decreasing side, and if the number of abnormal persons in 2009 is larger than the number of abnormal persons in 2008, it will be on the increasing side. . At this time, a predetermined number of evaluation indices may be plotted in order from the top in accordance with the ranks assigned in step S177.

  The frequency distribution of the target group shown in FIG. 31 (B) can be created by displaying the distribution of the target group created in step 166 and step 168 in an overlapping manner. In addition, the frequency distribution of the reference group shown in FIG. 31C can be created by displaying the reference group distribution created in step 172 and step 174 in an overlapping manner.

  Note that the interface for displaying the frequency distribution (FIG. 31B, FIG. 31C) is, for example, by clicking an index plotted in the scatter diagram shown in FIG. By selecting, the frequency distribution of the selected item may be displayed.

  As described above, in the consultation recommendation level determination process of the first embodiment, the treatment status determination unit 136 determines whether the examinee is being treated from the inquiry result, and the target group distribution creation unit 132 and The reference population distribution creation unit 133 calculates a distribution of medical examination items or index values excluding the person being treated. Then, the distribution comparison unit 134 compares the number of people who are at a level that requires treatment but have not received treatment. This makes it easy to determine whether there are more or fewer people who are at a level that requires treatment and are not receiving treatment compared to other organizations (FIG. 30).

  In addition, since the distribution comparison unit 134 calculates the difference in distribution between the current year and the previous year of those who are not receiving treatment at the level that requires treatment in the target group and the reference group, the target group and the reference group Therefore, it can be evaluated whether the number of examinees requiring treatment is increasing or decreasing compared to the reference population (FIG. 31).

  It is one of the important objectives of health checkups to give early treatment to people with poor health checkup results. Whether the number of untreated patients who need diagnosis by a doctor depends on the recommended level of medical checkup. Can be evaluated. In addition, by showing data with a small number of untreated persons or a reduced number of untreated persons, it is possible to show the excellence of the treatment recommendation activities for the examinees in the medical examination organization.

<Extraction of recommended medical examination items>
Next, the recommended medical examination item extraction process in the first embodiment will be described.

  32A and 32B are flowcharts of recommended medical examination item extraction processing according to the first embodiment of this invention.

  First, the control unit 131 of the server 101 receives the designation of the target organization input by the user from the input device 143 of the terminal 103 via the communication interface 115 (S191), and receives the data of the designated target organization as the organization information management unit. 123 (S192).

  Thereafter, the control unit 131 refers to the contract item management unit 128 and selects an item for which the target group has not contracted (S193).

  After that, the control unit 131 acquires background factor adjustment items for the index value from the background factor item management unit 125 (S194), and totals the number of persons by combination of background factor hierarchies for each item of the background factor (S195). ).

  Thereafter, it is determined whether or not the aggregation of all background factor combinations is completed for the target index (S196).

As a result, if the summation of some indexes is not completed, the process returns to step S195 and the next index is tabulated. On the other hand, if the aggregation of all the indicators has been completed, the control unit 131 uses the data other than the target organization as a reference group for the organization that contracts the selected item.
The medical examination information of persons belonging to the reference group is acquired from the medical examination information management unit 121 (S197).

  After that, the index value calculation unit 135 calculates an index value from the medical checkup result of people belonging to the reference group (S198). The details of the index value calculation process are as shown in FIG.

  Thereafter, the reference population distribution creation unit 133 adjusts the data of the reference population using the background factors, and creates an index value distribution (S199). Details of this reference population distribution creation processing are as shown in FIG.

  Thereafter, a distribution in which the background factor is not adjusted is calculated for the reference population (S200).

  After that, the distribution comparison unit 134 calculates an area difference between the distribution of the reference group whose background factor has been adjusted and the distribution of the reference group whose background factor has not been adjusted (S201). The details of this distribution comparison processing are as shown in FIG.

  Thereafter, the control unit 131 determines whether the calculation has been completed for all analysis items (S202).

  As a result, if calculation of some analysis items has not been completed, the control unit 131 returns to step S193 and selects the next analysis item. On the other hand, if the calculation of all analysis items is completed, the control unit 131 determines the priority order of the analysis items from the area difference between the distribution of the target group and the distribution of the reference group (S203).

  FIG. 33 is a diagram for explaining a display of a result of analyzing a medical examination item recommended from the number of abnormal persons estimated from a test result.

  For example, as shown in FIG. 33A, it can be displayed in the form of a bar graph representing the estimated number of abnormal persons. In the bar graph of FIG. 33 (A), each bar in the graph shows how much or less the estimated value of the number of abnormal persons in the target group is compared with the number of abnormal persons in the reference group in each medical examination item. The area is shown.

  Further, as shown in FIG. 33B, the frequency distribution can be displayed in the form of a frequency distribution representing the estimated number of abnormal persons. In the bar graph of FIG. 33 (B), the person whose abnormality is estimated in the test result is compared with the reference group, and in which area how much or how little is less in the area of each distribution in the graph. Show.

  Next, a method of creating a bar graph representing the estimated number of abnormal persons shown in FIG. 33A will be specifically described according to the flowcharts shown in FIGS. 32A and 32B.

  First, in step S191, a certain group (for example, a group whose group ID is J0002 in FIG. 4) is designated.

  Next, in step S192, referring to the personal information management unit 122 (FIG. 3), the personal ID of a person belonging to the target organization (organization having the organization ID J0002) is acquired, and the medical examination information of the acquired personal ID is obtained. Obtained from the medical examination information management unit 121 (FIG. 2).

  Next, in step S193, an item (for example, liver function) that is not contracted by the target group is acquired from the contract item management unit 128 (FIG. 9).

  Next, in step S194, with reference to the background factor adjustment item management unit 125 (FIG. 6), the background factor adjustment item of the non-contract item (“job type”, “hepatitis family history” for liver function (GOT, GPT)) ) To get.

  Next, in steps S195 and S196, from the medical examination information acquired in step S192, the number of persons for each background factor item (for example, the number of persons according to occupation and family history for liver function) is totaled.

  Next, in step S197, the organization ID (J0001, J0004) of the organization that is contracted for the liver function test in the organization (reference group) other than the target organization is acquired from the contract item management unit 128 (FIG. 9). The medical examination information of persons belonging to the organizations (reference groups) having the organization IDs J0001 and J0004 is acquired from the medical examination information management unit 121 (FIG. 2).

  Next, in step S198 (index value calculation process (FIG. 11)), GOT and GPT are acquired from the acquired medical examination information. When the index value calculation logic is defined for the non-contract item (liver function), the non-contract item is calculated according to the index value calculation logic acquired from the index management unit 126 (12603 in FIG. 7).

  Next, in step S199 (reference population distribution creation process (FIG. 13)), the distribution of liver functions (GOT, GPT) of the reference population is obtained. At this time, for the background factor adjustment items (job type, hepatitis family history) of GOT and GPT, the distribution of the reference population is adjusted using the distribution for each job type and hepatitis family history of the target group created in step S195. This makes it possible to estimate the number distribution of the target group.

  Next, in step S200 (target organization distribution creation process (FIG. 12)), the distribution of liver functions (GOT, GPT) of persons belonging to the reference group is obtained. In step S200, the background factor is not adjusted.

  Next, in step S201 (distribution comparison process (FIG. 14)), an area difference between the estimated distribution of the liver function of the target group created in step S199 and the distribution of the liver function of the reference population created in step S200 is calculated. .

  Thereafter, in step S202, it is confirmed that the calculation has been completed for all non-contract items (items included in the contract item management unit 128 and not contracted by the target group (for example, lung cancer, colon cancer, etc.)). If there is a contract item for which calculation has not been completed, the process returns to step S193, the next contract item is selected from the contract item management unit 128 (FIG. 9), and the processing of steps S194 to S201 is repeated.

  Finally, in step S203, for each index (liver function, lung cancer, colon cancer, etc.), the number of reference groups and the number of target groups (estimated values) in each layer when the number of people in the worsening direction is positive. Calculate the difference between The graph is displayed by arranging the target groups in the descending order of the number of people in a state of worse than the reference group.

  The frequency distribution of the estimated value of the number of abnormal persons shown in FIG. 33B is displayed by superimposing the estimated distribution of liver function of the target group created in step S199 and the distribution of liver function of the reference population created in step S200. Can be created by doing.

  The interface for displaying the frequency distribution may display the frequency distribution of the selected item by, for example, clicking a bar graph shown in FIG. 33A and selecting a specific evaluation index.

  As described above, in the recommended medical examination item extraction process of the first embodiment, the distribution of the reference group (estimated distribution of the target group) in which the target group and the background factor are aligned for the items for which the customer group has not contracted. , Calculate the difference in the number of people in a bad state between the distribution of the reference group and the estimated distribution of the target group, and based on this number difference, output items that the target group has not contracted, Of the items that the customer group does not conduct a medical examination, it is possible to extract items that are likely to have many abnormal persons. Thereby, the medical examination organization can propose a medical examination of an item having a possibility of many abnormal persons to the customer group, and it becomes easy to acquire a new medical examination item in the contract negotiation with the customer group.

<Generation of background factor items>
Next, background factor generation processing in the first embodiment will be described.

  FIG. 34 is a flowchart of background factor item determination processing according to the second embodiment of this invention. This background factor item determination process is executed by the background factor item creation unit 138.

  First, the background factor item creation unit 138 selects one evaluation index 12601 from the index management information 126 (S211).

  Thereafter, multiple regression analysis is performed between the index value and the non-variable inquiry item, and the coefficient of the index value for the non-variable inquiry item is calculated (S212).

  Thereafter, non-variable inquiry items for which the coefficient of the index value is determined to be significant are registered in the background factor adjustment items (S213).

  Thereafter, it is determined whether the calculation is completed for all index values (S214).

  As a result, if calculation of some index values has not been completed, the process returns to step S211 to select the next index value. On the other hand, if all the index values have been calculated, this process ends.

  As described above, in the background factor generation process of the first embodiment, the background factor is automatically generated, so that a statistically significant background factor can be accurately generated. That is, since the background factor item creation unit 138 automatically determines the background item to be adjusted for each index, even when the inquiry item is different for each medical examination institution, or when the examination item or the inquiry item is added, The background factor item can be easily determined. For this reason, it is possible to set only the items that contribute to the index as background factors and adjust the background factors appropriately.

  So far, various functions of the medical examination information analysis system according to the first embodiment have been described. However, it is not necessary to implement all these functions, and one or more functions can be implemented in various combinations. .

  When examining whether or not the results of the medical examination are improving as a group, the average value of the medical examination items and the estimated medical expenses shown in Patent Document 1 are the values of the previous year and the current year. A method of determining whether or not an improvement has been made by comparison is conceivable. However, a method for providing detailed information to customer organizations by analyzing the degree of improvement and the degree of deterioration in more detail has not been proposed, but the present invention has improved or deteriorated the previous year and this year. It is possible to analyze the degree of the above in more detail.

  As a method of judging whether the health check result is good or bad, not only the self-organization but also a method of comparing with the health check information of other groups, for example, the method of Patent Document 1 is applied to reduce the medical expenses of other groups. A method can be considered that ranks the quality of the health check result by estimating and comparing it with the own group. However, when the gender ratio and age group of the own group and other groups are different, the average test results and the proportion of diseases that develop are also different, making it difficult to compare the results of medical examinations of both groups. In particular, because the lifestyles differ depending on the type of business and occupation, such as whether the members of the target group are mainly deskwork clerks, outside sales positions, or manufacturing departments, simply compare between groups Although it was not possible, the present invention makes it possible to make a comparison in consideration of the type of business and the type of job.

  In the medical examination, it is important to promote improvement for people with abnormal test values and to encourage people who need treatment to receive medical treatment at an early stage. For this reason, the number of people who have not received a medical examination at a level that requires medical examination is also an important point of view as a result of the medical examination. When a person in need of treatment visits, it is an index indicating that the recommended medical checkup activity is good. According to the present invention, it is possible to evaluate an index indicating the degree of goodness of the consultation recommendation activity.

  Since the medical examination organization contracts with the customer organization in units of medical examination items, it is important to appeal the necessary medical examination items to the customer organization in order to expand the contract. As a method for recommending addition of medical examination items, for example, Patent Document 2 discloses a method of optimizing a combination of medical examination items from a disease risk for each individual. However, if the individual bears the full amount of the medical checkup fee, a combination of individual units may be used. However, if the contract is made with an organization, the amount of the medical checkup varies from individual to individual, making it difficult to actually use it. According to the present invention, it is possible to appeal the necessary medical examination items to the customer group.

  When the health examination organization grasps the health status of the customer organization from the health examination results, it compares the data of the target customer organization with the data of other groups, and for each health examination item, the person with the poor health status Can be found in the target customer groups, and measures can be considered.

  However, there are items that cannot be changed by the efforts of organizations such as companies and health insurance associations, and individual efforts. For example, the type of industry, occupation, family medical history, etc., are difficult to change and will affect the results of medical examinations. In evaluating the level of health status and improvement level, even when compared to groups with different percentages of items that cannot be changed, the health status (badness) of people belonging to the target group, The amount of improvement (amount of deterioration) may not be evaluated correctly.

  For example, in the case of diabetes, when a family such as a parent or sibling is diabetic, there is a high possibility of genetically developing diabetes. However, in other groups compared to the target group, when there are few people with a family history of diabetes, the blood glucose level test result of the target group may be relatively poor. For this reason, it is desirable to compare the target group with other groups after preparing items that cannot be changed depending on the intention or action.

  On the other hand, the related items differ depending on the disease and the index, and the examination items and the inquiry items are different for each medical examination institution. Therefore, in order to set the background item for each index, specialized knowledge and labor are required. In addition, when using multiple items for background adjustment, the background may not be adjusted correctly, such as when there are no people in the background item layer combination, and background items are limited to meaningful items. There is a need to. However, the present invention allows appropriate comparisons between organizations with different backgrounds.

<Embodiment 2>
Next, a second embodiment of the present invention will be described.

  In the second embodiment, an improvement program is proposed based on the calculated index value.

  Note that in the second embodiment, the same reference numerals are given to the same configurations, functions, and processes as those in the first embodiment described above, and detailed description thereof is omitted.

  FIG. 35 is a block diagram illustrating a hardware configuration of a medical examination information analysis system according to the second embodiment of this invention.

  The medical examination information analysis system of this embodiment includes a server 101, a database 102, and a terminal device 103.

  The server 101 and the database 102 are connected so that the server 101 can access data stored in the database 102. The server 101 is connected to the terminal device 103 via the network 104.

  The storage device 114 is, for example, a large-capacity nonvolatile storage device such as a magnetic storage device or a flash memory. Specifically, the storage device 114 includes a control unit 131, a target group distribution creation unit 132, and a reference group distribution. Implementation of the creation unit 133, distribution comparison unit 134, index value calculation unit 135, treatment status determination unit 136, improvement program evaluation unit 231, countermeasure item selection unit 232, improvement program effect estimation unit 233, and improvement program ranking unit 234 Store the program to do.

  The improvement program evaluation unit 231 evaluates the improvement program by executing a predetermined program. The improvement program effect estimation unit 232 estimates the effect of the improvement program by executing a predetermined program. The improvement program ranking unit 233 gives priority to the improvement programs by executing a predetermined program.

  The database 102 is data for the server 101 to analyze the medical examination information, that is, the medical examination information management unit 121 (see FIG. 2), the personal information management unit 122 (see FIG. 3), and the group information management unit 123 (FIG. 4). Reference value management unit 124 (see FIG. 5), background factor item management unit 125 (see FIG. 6), index management unit 126 (see FIG. 7), improvement program information management unit 221 (see FIG. 36), improvement program The history management unit 222 (see FIG. 37) and the improvement program effect management unit 223 (see FIG. 38) are stored.

  FIG. 36 is a diagram illustrating the configuration of data stored in the improvement program information management unit 221 according to the second embodiment of this invention.

  The improvement program information management unit 221 is a database in which information on improvement programs proposed to the examinee is stored, and includes data of program ID 22101, program name 22102, application condition 22103, cost per person 22104, and effect index 22105.

  The program ID 22101 is identification information for uniquely identifying the improvement program proposed to the examinee. The program name 22102 is the name of the improvement program proposed to the examinee, and simply shows the content of the improvement program. The application condition 22103 is a condition of a patient to whom the improvement program is applied. The cost per person 22104 is a cost required when the improvement program is applied to the examinee, and is an amount per predetermined period (for example, one year). The effect index 22105 is an index for evaluating the effect on the implementation of the improvement program.

  Specifically, the program with the program ID “PRG0001” is a “step-up competition” in which the number of steps per day is competing, and everyone is eligible, and the cost is 3600 yen per year, and the effect is evaluated by BMI. can do.

  The program with the program ID “PRG0002” is a “low-calorie meal delivery” that makes meals delivered to low-calorie meals, has a blood glucose level of more than 110 and less than 126, and a BMI of 25 or more. The cost is 12000 yen per year, and the effect can be evaluated by BMI and blood glucose level.

  In addition, the improvement program with the program ID “PRG0003” is “salt reduction guidance” that regularly receives lifestyle guidance to reduce salt, and it is for people with systolic blood pressure of 130 or more, and the cost is one year. It is 20000 yen per, and the effect can be evaluated by blood pressure.

  FIG. 37 is a diagram illustrating the configuration of data stored in the improvement program history management unit 222 according to the second embodiment of this invention.

  The improvement program history management unit 222 is a database that stores information on improvement programs applied to the organization to which the examinee belongs, and includes data of an organization ID 22201, an implementation time 22202, a program ID 22203, and application conditions 22204.

  The organization ID 22201 is identification information for uniquely identifying the organization to which the examinee belongs, and the same value as the organization ID 12301 of the organization information management unit 123 is used.

  The implementation time 22202 is the time (start date and end date) when this program was applied to the organization. The program ID 22203 is identification information for uniquely identifying the improvement program proposed to the examinee, and the same value as the program ID 22101 of the improvement program information management unit 221 is used. The application condition 22204 is a condition of the examinee to which the improvement program is applied, and the same condition as the application condition 22103 of the improvement program information management unit 221 is defined.

  FIG. 38 is a diagram illustrating the configuration of data stored in the improvement program effect management unit 223 according to the second embodiment of this invention.

  The improvement program effect management unit 223 is a database in which an index for improving the effect of the improvement program is stored. The program ID 22301, the program name 22302, the application condition 22303, the target item 22304, the distribution categories 22305, 22307, 22309, and 23231, and The data of effect amounts 22306, 22308, 22310, and 22312 are included.

  The program ID 22301 is identification information for uniquely identifying the improvement program proposed to the examinee, and the same value as the program ID 22101 of the improvement program information management unit 221 is used. The program name 22302 is the name of the improvement program proposed to the examinee, and the same name as the program name 22102 of the improvement program information management unit 221 is defined. The application condition 22303 is a condition of the examinee to which the improvement program is applied, and the same condition as the application condition 22103 of the improvement program information management unit 221 is defined.

  The target item 22304 is a medical examination item used for evaluating the effect of the improvement program. Although one medical examination item is shown in the figure, a plurality of medical examination items may be defined in one entry.

  In the distribution sections 22305, 22307, 22309, and 2311 and the effect amounts 22306, 22308, 22310, and 22312, points of effect amounts corresponding to the distribution sections are defined. The effect amount is the amount of change in the frequency of the category on the frequency distribution, and is calculated from the past application of the program.

  For example, in the “step-up competition” with the program ID = PRG0001, the frequency of the segment with BMI less than 18 does not change, the frequency of the segment with 18 ≦ BMI <22 increases by 2, and the segment with 22 ≦ BMI <25 The frequency is expected to increase by 3 and the frequency in the section 25 ≦ BMI <27 is expected to decrease by 3.

  FIG. 39 is a flowchart of the improvement program proposing process according to the second embodiment of this invention.

  First, the control unit 131 of the server 101 acquires medical examination information before and after the execution of the improvement program from the improvement program history management unit 222 (S221).

  Thereafter, the target group distribution creation unit 132 creates a distribution before the improvement program is implemented and a distribution after the improvement program is implemented (S222).

  Thereafter, the improvement program evaluation unit 231 extracts the effect amount from the difference between the distribution before and after the execution, and stores it in the improvement program effect management unit 223 (S223).

  And the control part 131 determines whether calculation was completed about the performance of all the improvement programs (S224). As a result, if the calculation of the results of some improvement programs is not completed, the process returns to step S222 to calculate the results of the next improvement program. On the other hand, if the calculation has been completed for the results of all the improvement programs, the control unit 131 receives the designation of the target group (S225).

  And the control part 131 extracts the subject item of an object organization by comparing with a reference group (S226). The details of the task item extraction process are as shown in FIG.

  And the control part 131 selects a countermeasure item according to a priority (S227). Then, the improvement program evaluation unit 231 selects an improvement program for which the selected countermeasure item is targeted (S228).

  Thereafter, the improvement program evaluation unit 231 deforms the distribution of the target group based on the improvement program effect management unit 223, and calculates the area difference between the distribution of the target group after the deformation and the distribution of the reference group (S229).

  Thereafter, the improvement program evaluation unit 231 calculates the total cost of the improvement program by multiplying the unit price of the improvement program selected in step S208 by the number of people (S230).

  Thereafter, the control unit 131 determines whether the calculation has been completed for all combinations of improvement programs (S231). As a result, if the calculation has not been completed for some of the improvement program combinations, the process returns to step S208 to calculate the next improvement program combination. On the other hand, if the calculation has been completed for all the combinations of the improvement programs, the improvement program ranking unit 234 relates the residual between the distribution of the target group and the distribution of the reference group when the improvement program is applied, and the total cost. From the above, the distance from the origin is calculated, and the priority is given from the one with the shortest distance (S232).

  FIG. 40 is a diagram illustrating the display of the cost-benefit analysis result of the improvement program derived by the medical examination information analysis system according to the second embodiment of this invention.

  For example, as shown in FIG. 40 (A), the total cost of the improvement program is set on the vertical axis, the deviation of the target group from the reference group is set on the horizontal axis, and the improvement program is plotted. Can be analyzed for cost effectiveness.

  As shown in FIG. 40B, the number of abnormal persons estimated when the improvement program is applied to the target group can be displayed in the form of a frequency distribution. That is, the number of abnormal persons estimated when the improvement program is applied to the target group is compared with the reference group, and how much or how much is smaller or smaller is indicated by the distribution area in the graph.

  Next, a method for creating the cost-effectiveness graph of the improvement program shown in FIG. 40A will be specifically described according to the flowchart shown in FIG.

  First, in step S221, improvement program information is acquired from the improvement program history management unit 222 (FIG. 37). For example, since the improvement program with the program ID PRG0001 is being implemented from April 2009 to March 2010 for the organization with the organization ID J0001, the improvement program for the organization with the organization ID J0001 was started (2009 April 4). 1 year (April 2008 to March 2009) and 1 year after the end of the improvement program (March 2010) (April 2010 to March 2011) Get information. In addition, the improvement program with program ID PRG0001 is also implemented from April 2009 to March 2010 for organizations with an organization ID of J0004, so April 2008 to March 2009, and April 2010 From March 2011, the medical examination information of the group whose group ID is J0004 is acquired. Similarly, for the improvement program whose program ID is PRG0002, the medical examination information of the organization whose organization ID is J0002 from April 2008 to March 2009 and from April 2010 to March 2011 is obtained. Regarding the improvement program of PRG0003, the medical examination information of the organization whose organization ID is J0003 from April 2008 to March 2009 and from April 2010 to March 2011 is acquired.

  Next, in step S222, referring to the improvement program information management unit 221 (FIG. 36), since the effect index of the improvement program whose program ID is PRG0001 is BMI, the medical examination information (group ID is J0001) before the improvement program is implemented. Using the group's height and weight from April 2008 to March 2009 and the group ID of J0004 from April 2008 to March 2009), index value calculation processing (FIG. 11) The BMI is calculated by the above, and the BMI distribution is created by the target group distribution creation process (FIG. 12). In addition, information on medical examinations after the program (height and weight from April 2010 to March 2011 for organizations with an organization ID of J0001 and height from April 2010 to March 2011 for organizations with an organization ID of J0004 And body weight), the BMI is calculated by the index value calculation process (FIG. 11), and the BMI distribution is created by the reference group distribution creation process (FIG. 13).

  Next, in step S223, the distribution comparison process (FIG. 14) subtracts the number of people after the implementation from the number before the implementation for each distribution layer (section) from the distribution before the implementation of the improvement program and the distribution after the implementation. The difference is recorded in the effect amount 22306, 22308, 22310, 22312 of the improvement program effect management unit 223 (see FIG. 38).

  Thereafter, in step S224, it is confirmed that the calculation has been completed for all the improvement programs (all the improvement programs included in the improvement program information management unit 221). If there is an evaluation index that has not been calculated, the process returns to step S222, and the next improvement program (for example, an improvement program with program IDs PRG0002 and PRG0003) is selected from the improvement program information management unit 221 (FIG. 36). Steps S222 to S223 are repeated.

  Next, in step S225, a certain organization (for example, the organization whose organization ID is J0001 in FIG. 4) is designated.

  Next, in step S226, by the assignment item extraction process (FIG. 10), for each item (evaluation index) of the organization whose organization ID is J0001, the number distribution of the target group and the number distribution of the reference group are created. Find the difference in the number of people.

  Next, in step S227, an item having the largest number of people with poor medical examination results is selected as a countermeasure item in the difference between the distribution of the target group and the distribution of the reference group in each evaluation index obtained in step S226. For example, when the BMI of the target group is the item where the bad person is the largest compared to the BMI of the reference group, the BMI is selected.

  Next, in step S228, with reference to the improvement program effect management unit 223 (FIG. 38), one improvement program in which the selected countermeasure item (BMI) is a countermeasure item (for example, a program whose program ID is PRG0001). )select.

  Next, in step S229, the BMI distribution of the target organization created in step S226 is divided into the distribution categories 22305, 22307, 22309, 22231 and the effect amounts 22306, 22308 of the improvement program effect management unit 223 (see FIG. 38). , 22310, and 22312. For example, in the distribution of BMIs of the target organizations, when the number of persons having a BMI of 18 or more and less than 22 is 10, the effect amount is +2, so that 10 + 2 = 12 is set to 10 (10/12 times). Deform. Similarly, calculation is performed on all layers (distribution sections) of the distribution to deform the distribution. Then, an area difference between the deformed distribution and the BMI distribution of the reference group created in step S226 is obtained by distribution comparison processing (FIG. 14).

  Next, in step S230, the improvement program application condition 22103 and the cost 22104 per person are acquired from the improvement program information management unit 221 (FIG. 36), and the total cost is calculated. For example, since the application condition of the improvement program with the program ID PRG0001 is everyone and the cost is 3600 yen / year, the total cost can be calculated by the number of organizations with the organization ID J0001 × 3600.

  Thereafter, in step S231, with reference to the improved program effect management unit 223 (FIG. 38), the calculation is completed for all the programs (PRG0002) whose BMI is a countermeasure item and combinations thereof (PRG0001 and PRG0002). Make sure. If there is an improvement program for which calculation has not been completed, the process returns to step S228, one improvement program is selected from the improvement program effect management unit 223 (FIG. 38), and the processing of steps S228 to S230 is repeated.

  Finally, in step S232, the graph of FIG. 40A is created. Specifically, the area difference (number difference) obtained in step S229 is set on the horizontal axis, the total cost calculated in step S230 is set on the vertical axis, and plotted for each combination of the improvement program and the improvement program. At this time, when the number of improvement programs to be plotted is large, an improvement program having a small distance from the origin may be preferentially displayed.

  The frequency distribution shown in FIG. 40B can be created by superimposing and displaying the distribution of the target group and the reference group obtained in step S226 and the distribution of the target group after the transformation obtained in step S229.

  Note that the interface for displaying the frequency distribution (FIG. 40B) is selected by, for example, clicking on the improvement program plotted in the graph of FIG. 40A and selecting a specific improvement program. The frequency distribution of the improved program may be displayed.

  As described above, in the second embodiment of the present invention, the improvement program effect management unit 223 manages the change in distribution due to the improvement program, and the improvement program effect estimation unit 233 detects the change in distribution due to the execution of the improvement program. Since it calculates, the distribution after applying the improvement program can be calculated.

  Further, the improvement program ranking unit 234 recommends an improvement program from the relationship between the area difference between the estimated distribution after application of the improvement program calculated by the improvement program effect estimation unit 233 and the distribution of the reference group and the instruction cost. Since the ranking is set, the improvement program can be selected with the result that the application result of the improvement program is closest to the reference group and the cost is low.

  Further, the improvement program history management unit 222 manages the organization and the application period to which the improvement program is applied, and the improvement program evaluation unit 231 calculates the distribution change due to the improvement program from the actual improvement program execution result. Based on the results of the improvement program, the effect (change in distribution) of the improvement program can be accurately obtained.

  When the health checkup result of the customer group is worse than that of the other group, the customer group needs a measure for obtaining the same level of checkup result as the other group. According to the present invention, a medical examination institution can provide an improvement method for bringing the distribution of the number of people related to a problem item closer to other organizations.

  The medical examination information analysis system of the second embodiment described above can be implemented alone or in combination with one or more functions of the first embodiment.

101 Server 102 Database 103 Terminal Device 104 Network 111 Input Device 112 Output Device 113 Processor (CPU)
114 Storage device 115 Communication interface 121 Medical examination information management unit 122 Personal information management unit 123 Group information management unit 124 Reference value management unit 125 Background factor item management unit 126 Index management unit 127 Non-variable item management unit 128 Contract item management unit 131 Control Unit 132 target group distribution creation unit 133 reference population distribution creation unit 134 distribution comparison unit 135 index value calculation unit 136 treatment status determination unit 137 output unit 138 background factor item management unit 231 improvement program evaluation unit 232 measure item selection unit 233 improvement program effect Estimation unit 234 Improvement program ranking unit 221 Improvement program information management unit 222 Improvement program history management unit 223 Improvement program effect management unit

Claims (16)

A medical examination information analysis system for analyzing a test result of a medical examinee obtained by a medical examination,
A target group distribution creating unit that creates a distribution of the number of persons for each hierarchy, in which the test results of the target group configured by persons belonging to the group to be evaluated are divided within a predetermined range;
A reference group distribution creating unit for creating a distribution of the number of persons for each of the test results of the reference group constituted by persons who do not belong to the target group;
A distribution comparison unit that compares the distribution of the target group and the distribution of the reference group, and calculates a difference in the number of persons whose test results are worse than a predetermined reference value;
And an output unit that ranks and outputs examination items based on the difference in the number of persons. An index value calculation unit for calculating an index value for evaluation from the inspection result,
The target group distribution creation unit creates a distribution of the number of persons for each hierarchy of the index value of the target group,
The reference group distribution creation unit creates a distribution of the number of people for each hierarchy of the index value of the reference group,
The distribution comparison unit compares the distribution of the target group and the distribution of the reference group, calculates a difference in the number of people whose index value is worse than a predetermined reference value,
The medical examination information analysis system according to claim 1, wherein the output unit ranks and outputs evaluation indexes based on a difference in the number of the index values. In order to affect the test result or the index value, comprising a background factor item management unit for managing background factors to be adjusted for each population,
The target group distribution creation unit obtains a background factor related to the test result or the index value to be calculated from the background factor item management unit, and calculates the number of people of the target group according to the background factor,
The reference group distribution creation unit adjusts the distribution according to the number of background factors of the target group according to the background factor of the target group, the number of people according to the background factor of the test item or index value of the reference group,
The medical examination information analysis system according to claim 2 , wherein the distribution comparison unit compares the distribution of the target group with the distribution of the adjusted reference population, and calculates the difference in the number of people. The target group distribution creation unit creates a distribution of the number of persons related to the test result or index value of the target group for the current year, creates a distribution of the number of persons related to the test result or index value of the target group of the previous year,
The reference group distribution creation unit creates a distribution of the number of persons related to the test result or index value of the reference group for the current year, creates a distribution of the number of persons related to the test result or index value of the previous year of the reference group,
The distribution comparison unit
Compare the distribution of the target group in the previous year with the distribution of the current year, and obtain a first difference in number of persons that is a difference in the number of persons whose test result or the index value is worse than a predetermined reference value,
Comparing the distribution of the reference group in the previous year with the distribution of the current year, and obtaining a second difference in the number of persons in which the test result or the index value is worse than a predetermined reference value;
4. The health according to claim 2 or 3 , wherein the difference between the first number of people and the second number of people is compared, and the amount of improvement or deterioration of the test result or index value of the target group is calculated. Diagnosis information analysis system. For the test result or the index value, a reference value management unit that manages a reference value indicating a level at which medical examination is necessary;
A treatment status determination unit for determining whether the examinee is performing treatment related to the examination result or the index value from the interview result of the examinee,
The target group distribution creation unit and the reference population distribution creation unit exclude the person determined to be in treatment, and create a distribution of the number of persons for each layer of the examination item or the index value,
The distribution comparison unit refers to the reference value management unit for the target group and the reference group, or the previous year and the current year, and calculates the difference in the number of persons in the value indicating the level necessary for the consultation. The medical examination information analysis system according to any one of claims 2 to 4 , wherein the medical examination information analysis system is calculated. It has a contract item management department that manages the contract status of inspection items of customer organizations,
The target group distribution creation unit calculates the number of people according to the background factor that affects the test result or index value of the target group,
The reference group distribution creation unit refers to the contract item management unit, and determines the number of test results or index value background factors of the target group that the target group is not contracted for, Create a second reference population distribution adjusted to the number of people in
The distribution comparison unit compares the distribution of the reference population and the distribution of the second reference population with respect to the inspection item or the index value, and in the second reference population, the inspection result or the index value is 4. The medical examination information analysis system according to claim 3, wherein a difference in the number of persons worse than a predetermined reference value is calculated. A non-variable item management unit that manages inspection items that cannot be changed by one's own intention as non-variable items;
Among the background factors of the test result or the index value, a background factor item creating unit that registers a background factor having a large influence on the test result or the index value as a non-variable item in the background factor item management unit, The medical examination information analysis system according to claim 3, further comprising: An improvement program information management unit for managing application conditions and costs of an improvement program applied to a medical checkup recipient;
An improvement program history management unit for managing the implementation history of the improvement program;
An improvement program effect management unit that manages the amount of change in the distribution of the number of test results or index values improved by the improvement program;
An improvement program evaluation unit for evaluating the effect of the improvement program;
An improvement program effect estimation unit for estimating the effect of the improvement program;
An improvement program ranking unit for ranking the improvement programs,
The target group distribution creation unit creates a distribution of the number of persons for each level of the inspection item or the index value of the target group in the year before and after the implementation of the improvement program, and a background factor related to the index to be calculated is the background factor item Obtain from the management department, calculate the number of people by the background factor of the target group,
The reference group distribution creation unit creates a distribution of the number of persons in each of the inspection items or index values of the reference group in the year before and after the improvement program is implemented, and the distribution of the number of inspection items or index values of the reference group Is adjusted according to the number of people by the background factor of the target group,
The distribution comparison unit compares the distribution of the target group with the distribution of the adjusted reference population,
The improvement program evaluation unit
Obtaining information on the organization implementing the improvement program from the improvement program history management unit,
From the medical examination information before and after the improvement program implementation of the improvement program implementation group created by the target organization distribution creation unit, the inspection item or evaluation index for evaluating the effect of the improvement program, the year before and after the implementation of the improvement program Find the difference in the distribution of people,
Calculate the effect of the improvement program from the difference in the number of people,
Storing the calculated effect in the improvement program effect management unit;
The improvement program effect estimator is
Select an item with a large difference in the number of people in the distribution compared by the distribution comparison unit as a countermeasure required item,
Obtaining an improvement program capable of improving the selected required countermeasure item and an effect amount of the improvement program from the improvement program effect management unit;
When the effect amount of the acquired improvement program is applied to the current distribution of the target group created by the target group distribution creation unit, in the target group to which the improvement program is applied, the inspection item or the index value Seeks changes in the number of people that are worse than the prescribed reference value,
The improvement program ranking unit
The area indicating the number of people in a poor health state by comparing the distribution after change obtained by the improvement program effect estimation unit with the distribution of the reference group in which the stratified number of people is adjusted by the reference group distribution creation unit Find the difference
4. The medical examination information analysis system according to claim 3, wherein the improvement programs are ranked based on the relationship between the area difference and the implementation cost of the improvement program. A medical examination information analysis method for analyzing a test result of a medical examinee obtained by a medical examination using a computer,
The computer has a database that holds the test results of a target group configured by persons belonging to a group to be evaluated,
The method
A target group distribution creation procedure for creating a distribution of the number of persons for each hierarchy in which the test results of the target group configured by persons belonging to the group to be evaluated are divided within a predetermined range;
A reference group distribution creating procedure for creating a distribution of the number of persons for each of the test results of the reference group constituted by persons who do not belong to the target group;
A distribution comparison procedure for comparing the distribution of the target group and the distribution of the reference group, and calculating a difference in the number of persons whose test results are worse than a predetermined reference value;
An operation procedure for ranking and outputting the examination items based on the difference in the number of persons, and an operation method of the medical examination information analysis system. The method includes an index value calculation procedure for calculating an index value for evaluation from the test result,
In the target group distribution creation procedure, create a distribution of the number of persons for each hierarchy of the index value of the target group,
In the reference group distribution creation procedure, create a distribution of the number of persons for each layer of the index value of the reference group,
In the distribution comparison procedure, the distribution of the target group is compared with the distribution of the reference group, and the difference in the number of people whose index value is worse than a predetermined reference value is calculated.
The operation method of the medical examination information analysis system according to claim 9, wherein in the output procedure, the evaluation indexes are ranked and output based on a difference in the number of the index values. The method includes a background factor item management procedure for managing a background factor to be adjusted for each population in order to influence the test result or the index value,
In the target group distribution creation procedure, obtain a background factor related to the test result or the index value to be calculated, calculate the number of people by the background factor of the target group,
In the reference population distribution creating procedure, the number of people according to the background factor of the target group is adjusted according to the number of people according to the background factor of the target group, the number of people according to the background factor of the test item or index value of the reference population,
The operation of the medical examination information analysis system according to claim 10 , wherein in the distribution comparison procedure, the distribution of the target group is compared with the distribution of the adjusted reference population, and the difference in the number of persons is calculated. Method. In the target group distribution creation procedure, create a distribution of the number of persons related to the test result or index value of the target group for the current year, create a distribution of the number of persons related to the test result or index value of the target group of the previous year,
In the reference group distribution creation procedure, create a distribution of the number of people related to the test result or index value of the reference group for the current year, create a distribution of the number of people related to the test result or index value of the previous year of the reference group,
In the distribution comparison procedure,
Compare the distribution of the target group in the previous year with the distribution of the current year, and obtain a first difference in number of persons that is a difference in the number of persons whose test result or the index value is worse than a predetermined reference value,
Comparing the distribution of the reference group in the previous year with the distribution of the current year, and obtaining a second difference in the number of persons in which the test result or the index value is worse than a predetermined reference value;
The health difference according to claim 10 or 11 , wherein the difference between the first number of people and the second number of people is compared, and the amount of improvement or deterioration of the test result or index value of the target group is calculated. Operation method of diagnostic information analysis system. The method includes a treatment status determination procedure for determining whether the examinee is performing treatment related to the examination result or the index value from the interview result of the examinee,
The database manages a reference value indicating a level at which medical examination is necessary for the test result or the index value,
In the target group distribution creation procedure and the reference population distribution creation procedure, except for the person determined to be in treatment , create a distribution of the number of persons for each layer of the examination item or the index value,
In the distribution comparison procedure, with respect to the target group and the reference group, or the previous year and the current year, the reference value is referred to calculate the difference in the number of persons at the value indicating the level necessary for the consultation. The operating method of the medical examination information analysis system according to any one of claims 10 to 12 . The database manages the contract status of inspection items of customer organizations,
In the target group distribution creation procedure, calculate the number of people by the background factor that affects the test results or index value of the target group,
In the reference group distribution creation procedure, referring to the status of the contract, the number of test results or index values of background factors of the target group that are not contracted by the target group are classified according to the background factor of the target group. Create a second reference population distribution adjusted for the number of people,
In the distribution comparison procedure, for the test item or the index value, the distribution of the reference population and the distribution of the second reference population are compared, and in the second reference population, the test result or the index value is 14. The operation method of the medical examination information analysis system according to any one of claims 9 to 13, wherein a difference in the number of persons worse than a predetermined reference value is calculated. The database includes application conditions and costs of an improvement program applied to medical checkup recipients, an implementation history of the improvement program, changes in the distribution of the number of test results or index values improved by the improvement program, Manage
The method
An improvement program evaluation procedure for evaluating the effect of the improvement program;
An improvement program effect estimation procedure for estimating the effect of the improvement program;
An improvement program ranking procedure for ranking the improvement programs;
In the target group distribution creation procedure, the distribution of the number of persons for each hierarchy of the inspection item or the index value of the target group in the year before and after the implementation of the improvement program is created, and background factors relating to the index to be calculated are acquired from the database And calculate the number of people by background factor of the target group,
In the reference group distribution creation procedure, the distribution of the number of people in each of the inspection items or index values of the reference group for the year before and after the improvement program is implemented, and the distribution of the number of inspection items or index values in the reference group Is adjusted according to the number of people by the background factor of the target group,
In the distribution comparison procedure, the distribution of the target group is compared with the distribution of the adjusted reference population,
In the improvement program evaluation procedure,
Obtaining information on the organization implementing the improvement program from the database,
From the medical examination information before and after the improvement program implementation of the improvement program implementation organization created by the target organization distribution creation procedure, the inspection item or evaluation index for evaluating the effect of the improvement program, the year before and after the implementation of the improvement program Find the difference in the distribution of people,
Calculate the effect of the improvement program from the difference in the number of people,
Storing the calculated effect in the database;
In the improvement program effect estimation procedure,
Select an item with a large difference in the number of people in the distribution compared by the distribution comparison procedure as a countermeasure required item,
Obtaining an improvement program capable of improving the selected required countermeasure items and the effect amount of the improvement program from the database;
When the effect amount of the acquired improvement program is applied to the current distribution of the target group created by the target group distribution creation procedure, in the target group to which the improvement program is applied, the inspection item or the index value Seeks changes in the number of people that are worse than the prescribed reference value,
In the improvement program ranking procedure,
The area indicating the number of people in a poor health state by comparing the distribution obtained by the improvement program effect estimation procedure with the distribution of the reference population in which the number of people by stratification is adjusted by the reference population distribution creation procedure. Find the difference
The operation method of the medical examination information analysis system according to claim 11, wherein the improvement programs are ranked from the relationship between the area difference and the implementation cost of the improvement program.   A medical examination information analysis system for analyzing a test result of a medical examinee obtained by a medical examination,
  A target group distribution creating unit that creates a distribution of the number of persons for each hierarchy, in which the test results of the target group configured by persons belonging to the group to be evaluated are divided within a predetermined range;
  A reference group distribution creating unit for creating a distribution of the number of persons for each of the test results of the reference group constituted by persons who do not belong to the target group;
  A distribution comparison unit that compares the distribution of the target group with the distribution of the reference group, and calculates a difference in the number of people on one side of the test result from a predetermined reference value;
  And an output unit that ranks and outputs examination items based on the difference in the number of persons.

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