WO2017057746A1

WO2017057746A1 - Labor management system, labor management method, and labor management method

Info

Publication number: WO2017057746A1
Application number: PCT/JP2016/079152
Authority: WO
Inventors: 稔加村; 建史加村; 慎悟石谷
Original assignee: 日通システム株式会社
Priority date: 2015-09-30
Filing date: 2016-09-30
Publication date: 2017-04-06

Abstract

A labor management system wherein a first group of items includes a group of attendance items and/or a group of personnel items, and a second group of items includes a group of physical checkup items and/or a group of stress check items. First data indicates the result for each first item constituting the first group of items. The first data indicates the result for each first item for an employee as a history. Second data indicates the result for each second item constituting the second group of items. The second data indicates the result for each second item for the employee. An input unit receives, as inputs, at least one first item and at least one second item, as specification items. An output control unit controls outputs to an output unit such that the output unit outputs a graph showing the results for each specification item. The graph includes the first data and the second data. The position of the result for each specification item on a time axis is aligned with the position of the results for the other specification items.

Description

Labor management system, labor management method, and labor management program

The present invention relates to a labor management system, a labor management method, and a labor management program for managing employee health from data such as attendance status, health check results, stress check results, and the like.

Employee attendance management is conducted at each company. In attendance management, a computer system is used to manage total working hours, overtime hours, number of days off work, number of late arrivals, number of early departures, and the like. In addition, companies regularly conduct health examinations to manage employee health. Furthermore, employees who are likely to have a lot of stress in their work are subjected to stress checks, and if necessary, interview guidance is given by an industrial physician or the like. Thus, at present, as a company, in addition to attendance management, it is required to perform employee health management, stress check, and the like for employees to perform labor management.

In this regard, Patent Document 1 describes an employee health management system used in companies and the like. The health management system disclosed in Patent Document 1 manages an employee's health check result and employee's attendance status, evaluates the employee's fatigue status from these data, and if the countermeasure is necessary, the employee himself / herself is required. In addition to the above, the manager is encouraged to take measures.

JP 2003-256578 A

However, in the health management system of Patent Document 1 that evaluates the fatigue state from the health check result and the attendance status, the user of the system easily grasps the relationship between the health check result and the stress check result and the attendance status and personnel. Can not. These relationships are important factors for improving the health and working conditions of employees in the future, so the labor management system described above can support the understanding of this relationship. Longed for.

An object of the present invention is to provide a labor management system, a labor management method, and a labor management program capable of supporting the grasp of the relationship between a medical examination result or a stress check result and attendance status or personnel. It is in.

In order to achieve the above object, a labor management system according to a first aspect of the present invention includes a first item group, a second item group, first data, second data, a storage unit, and an input unit. And an output control unit. The first item group includes at least one of an attendance item group and a personnel item group. The second item group includes at least one of a health check item group and a stress check item group. The first data indicates a result of each first item constituting the first item group. The first data is data indicating the result of each first item in the employee as a history. The second data is second data indicating a result of each second item constituting the second item group. The second data is data indicating the result of each second item in the employee as a history. The storage unit stores the first data and the second data. At least one first item and at least one second item are respectively input to the input unit as designated items. The output control unit controls output to the output unit so that the output unit outputs a graph indicating the result of each specified item. The graph includes the first data and the second data stored in the storage unit. The position of the result of each specified item on the time axis is matched among the specified items.

The labor management method according to the second aspect of the present invention includes defining at least one of the attendance item group and the personnel item group as the first item group. The method further includes defining at least one of a health check item group and a stress check item group as a second item group. The method further includes defining first data indicating a result of each first item constituting the first item group. The first data is data indicating the result of each first item in the employee as a history. The method further includes defining second data indicating a result of each second item constituting the second item group. The second data is data indicating the result of each second item in the employee as a history. The method further includes storing the first data and the second data in a storage unit. The method further includes inputting at least one of the first items and at least one of the second items as designated items by the input unit. The method further includes controlling the output to the output unit by the output control unit so that the output unit outputs a graph indicating the result of each specified item. The graph includes the first data and the second data stored in the storage unit. The position of the result of each specified item on the time axis is matched among the specified items.

The labor management program according to the third aspect of the present invention includes defining at least one of the attendance item group and the personnel item group as the first item group. The program further includes defining at least one of a health examination item group and a stress check item group as a second item group. The program further includes defining first data indicating a result of each first item constituting the first item group. The first data is data indicating the result of each first item in the employee as a history. The program further includes defining second data indicating a result of each second item constituting the second item group. The second data is data indicating the result of each second item in the employee as a history. The program further includes causing a computer to function as means for storing the first data and the second data in a storage unit. The program further includes inputting at least one of the first items and at least one of the second items as designated items by the input unit. The program further includes causing the computer to function as means for controlling output to the output unit so that the output unit outputs a graph indicating the result of each specified item. The graph includes the first data and the second data stored in the storage unit. The position of the result of each specified item on the time axis is matched among the specified items.

The labor management method according to the present invention is executed by the labor management system.
Furthermore, the labor management program according to the present invention is used in the labor management system. The labor management program is expanded via a removable recording medium such as a network or an optical disc, and is installed and executed on a computer such as a server.

1 is a block diagram showing an outline of a system according to an embodiment of the present invention. (A) shows the configuration of the personnel data storage unit of FIG. 1, (b) shows the configuration of the attendance data storage unit of FIG. 1, and (c) shows the configuration of the salary data storage unit of FIG. . (A) shows the configuration of the medical examination data storage unit of FIG. 1, (b) shows the configuration of the stress check data storage unit of FIG. 1, and (c) shows the configuration of the performance data storage unit of FIG. (D) shows the structure of the daily data storage part of FIG. 1, and (e) shows the structure of the medical data storage part of FIG. FIG. 4 is a flowchart illustrating processing for storing data in each storage unit illustrated in FIGS. 2 and 3. FIG. The flowchart which shows a process when it is a case where an employee himself / herself uses, and there is abnormality in a medical examination. The figure which shows the state which displayed on the monitor the report of the 1st output form which the graph of the selected item data aligns vertically. The figure which shows the state which displayed on the monitor the report of the 2nd output form on which the graph of the selected item data is superimposed. The flowchart which shows a process when it is a case where an employee himself / herself uses and there is abnormality in a stress check. The flowchart which shows a process when it is a case where an employee himself uses and confirms a health condition regularly. The flowchart which shows a process when it is a case where the employee himself / herself uses and there is a subjective symptom such as poor physical condition. The flowchart which shows a process when it is a case where a personnel clerk uses and overwork and poor work are detected. The flowchart which shows a process when it is a case where a personnel clerk uses, and a absentee returns. The flowchart which shows a process when it is a case where a personnel manager uses, and examines a business improvement measure. The flowchart which shows a process when it is a case where an occupational physician uses and there exists consultation, such as a poor physical condition. The figure which shows the state which displayed on the monitor the report of the 1st output form which performed the emphasis process with respect to the item which showed abnormality. The figure which shows the modification of the 1st output form (refer FIG. 6) using the icon while the graph of the selected item data aligns vertically. The figure which shows the modification of the 2nd output form (refer FIG. 7) using the icon while the graph of the selected item data is superimposed. The figure which shows the modification of the output form which superimposed the graph of the item for every large item. The figure which shows the output form which switched "total overtime hours" from the year unit to the month unit. (A) is a modified example of an output form using icons while superimposing a graph of selected item data, and (b) is a diagram showing a list of icons used in (a). The flowchart which shows the procedure of the statistical analysis process 1. The flowchart which shows the procedure in case an employee sees a medical examination result. The figure which shows the output form of a report. 10 is a flowchart showing a procedure of statistical analysis processing 2; The figure which shows a multiple regression analysis. The flowchart of the process which estimates the future of an individual employee.

Hereinafter, an embodiment in which a labor management system, a labor management method, and a labor management program are embodied will be described with reference to FIGS. In the present embodiment, information on employee personnel, information on attendance, information on health checkup results, and information on stress check results are used to improve employee health comprehensively, that is, mental and physical health. A labor management system for managing

As shown in FIG. 1, a management server 10 used in a labor management system includes a client terminal 2 used by personnel personnel and

client terminals

3a and 3b used by employees, etc. (hereinafter collectively) via a network 1. Also referred to as a client terminal 3) and a client terminal 4 used by an industrial physician or the like. These

client terminals

2, 3, and 4 include an output unit and an input unit. The output unit is a means for outputting various types of information, and includes a display, a printer, and the like. The input unit is a means for inputting various types of information, and includes a keyboard, a pointing device, a communication interface, and the like. In addition, the client terminal 3 and servers 5 to 8 for inputting various data to the management server 10 serve as input units.

The client terminal 2 for personnel personnel, the client terminal 4 for industrial physicians, and the client terminal 3a for employees display reports such as employee health examination results on a monitor, or can be printed and confirmed by a printer, for example, desktop type Or it is a notebook computer terminal.

The employee's client terminal 3b is a small information processing terminal such as a smartphone, portable phone, notebook computer, glasses-type or watch-type wearable terminal carried by the employee. The client terminal 3b includes a sensor that measures body data such as the number of steps, exercise amount, blood pressure, and pulse, and stores the detected value in a built-in memory or the like. In addition, the client terminal 3b stores activity data such as sleeping time, bedtime, and wake-up time, meal data such as the number of meal intakes, meal intake time, and meal intake calories. In addition, store customs data such as the amount of alcohol and smoking. In addition, medical data such as the timing of medical examinations and examinations, the start of internal use, the onset of illness, the time of healing, and the time of interviews with doctors are stored. The client terminal 3b stores such daily data and medical data of the employee, and the daily data and medical data are regularly or according to the operation of the employee via the client terminal 3a of the employee, or Directly to the management server 10.

Also, the management server 10 is connected via the network 1 to the personnel management management server 5, the medical examination management server 6, the stress check management server 7, and the performance management server 8 that manages the performance of the entire company and employees. Has been. Each employee is uniquely assigned with an employee code, and each of the servers 5 to 8 manages the employee code in association with the employee code.

The HR attendance management server 5 accumulates and manages data relating to employee affairs and attendance. Specifically, the HR attendance management server 5 manages item data relating to company events such as the date of joining, the date of department transfer, and the date of promotion for each employee, and the date of marriage. It manages item data related to private events such as the date of divorce, the date of birth, the date of start of care, and the date of end of care. In addition, the personnel time management server 5 includes time data such as total working hours and total overtime hours, number of days data such as the number of working days and the number of business trips, time data such as working time and working time as time data for each employee. I manage. Furthermore, the personnel attendance management server 5 manages salary data for each employee. The personnel attendance management server 5 periodically receives personnel data such as data relating to corporate events, data relating to private events, attendance data such as the number of days data, attendance time, leaving time, salary data, or It is transmitted to the management server 10 according to the operation of the operator.

The medical examination management server 6 manages medical examination data, which is a result of a medical examination periodically performed for each employee, for each employee. Specifically, the medical examination management server 6 manages item data that is the result of items such as weight, height, BMI, and uric acid value that constitute the medical examination data. The medical examination management server 6 transmits such medical examination data to the management server 10 periodically or according to the operation of the operator.

The stress check management server 7 manages stress check data, which is the employee's stress check result, for each employee. Specifically, the stress check management server 7 constitutes the stress check data, the result of work load judgment, the result of work resource (work level) judgment, the result of work resource (department) judgment, the work resource ( It manages the item data that is the result of items such as the result of determination and the result of comprehensive determination. Note that work resources refer to factors within the organization such as reducing work burdens, mitigating adverse effects of work burdens, and increasing motivation. Specifically, "Do you have support from your boss?" This is a rating (for example, 1 to 4 points) for the question items such as “whether there is support from a colleague” or “whether an individual is respected”. The stress check management server 7 performs a stress check diagnosis periodically for all employees or, for example, for employees exceeding the overtime hours of the regulations, and is transmitted from the client terminal 3 of the employee. Accumulate and manage response data for stress checks. Then, the stress check management server 7 transmits such stress check data to the management server 10 periodically or according to the operation of the operator.

The performance management server 8 manages item data such as sales amount, sales volume, order value, etc. as performance data for the entire company, business units, departments, and employees. Then, the performance management server 8 transmits such performance data to the management server 10 periodically or according to the operation of the operator.

The management server 10 to which the above devices are connected via the network 1 is a normal server, which is a computer system composed of hardware such as a CPU, a ROM, a RAM, a hard disk, and the like. A computer system for performing management. The management server 10 includes a control unit 11, a personnel data storage unit 21, an attendance data storage unit 22, a salary data storage unit 23, a medical examination data storage unit 24, a stress check data storage unit 25, and performance data. A storage unit 26, a daily data storage unit 27, and a medical data storage unit 28 are provided.

The control unit 11 includes a management unit 12, an extraction unit 13, and an output control unit 14. The control unit 11 is realized by, for example, a circuit, that is, one or more dedicated hardware circuits such as an ASIC, one or more processing circuits that operate according to a computer program (software), or a combination of both. Can do. The processing circuit includes a CPU and a memory (such as a ROM and a RAM) that stores a program executed by the CPU. Memory or computer readable media includes any available media that can be accessed by a general purpose or special purpose computer.

The management unit 12 periodically transmits a data transmission request to the personnel attendance management server 5, the medical examination management server 6, the stress check management server 7, and the performance management server 8, and is transmitted from each server. The stored data is stored in each of the storage units 21 to 26 and managed. In addition, the management unit 12 stores the daily data transmitted from the client terminal 3a or the client terminal 3b of the employee in the daily data storage unit 27.

The extraction unit 13 extracts employees whose anomalies have been detected in a health checkup or stress check. The extraction unit 13 performs this extraction process, for example, periodically or in response to an operation by the operator. In addition, the data of the corresponding employee is stored in the personnel data storage unit 21, the attendance data storage unit 22, the salary data storage unit 23, the medical examination data storage unit 24, the stress check data storage unit 25, the performance data storage unit 26, and Extracted from the daily data storage unit 27 and the medical data storage unit 28.

The output control unit 14 generates a report as output data based on information on personnel, information on attendance, information on health check results, and information on stress check results for each employee. This report is composed of visible data such as text data, image data, and video data, and is displayed on the monitor of the

client terminals

2, 3, 4 or connected to the

client terminals

2, 3, 4, or The data is output from a printer connected to the network 1 to printing paper. The output data is output to a portable recording medium such as an optical disc, a USB memory, or a memory card.

The management server 10 is further connected to the data warehouse 30 via a network. Data stored in the storage units 21 to 26 is transmitted from the management server 10 to the data warehouse 30 periodically or in accordance with the operation of the operator. The data warehouse 30 organizes and stores the received data stored in the storage units 21 to 26.

The data warehouse 30 is a normal server and is a computer system composed of hardware such as a CPU, ROM, RAM, and a large-capacity hard disk, and systematically stores and analyzes data transmitted from the management server 10. I do. The data warehouse 30 stores the data transmitted from the management server 10 in the storage unit 31 such as a large-capacity hard disk. The data warehouse 30 includes an analysis unit 32 that performs statistical analysis of data accumulated in the accumulation unit 31. Specifically, the analysis unit 32 calculates a correlation between each item of personnel data, each item of attendance data, and the like with respect to each health check item of the health check and each stress check item of the stress check. Then, for each check item of the health check and each check item of the stress check, each item of personnel data and each item of attendance data with high correlation are extracted as related items. The data warehouse 30 includes a registration unit 33 that registers a combination of items having high correlation.

As shown in FIG. 2 (a), the personnel data storage unit 21 stores a personnel record 21a in which personnel data that is an attribute of each employee is stored. This personnel record 21a is recorded when personal information of an employee is registered. In the personnel record 21a, various personnel item data, which is a personnel history, is recorded in association with the employee code. Specifically, the personnel record 21a stores the name, affiliation, job title, work style, contact information, etc., as well as the company events that occur within the company for each employee and the private part of each employee. Event etc. are stored. The company event is, for example, date / time data such as the date of joining, the date of department transfer, and the date of promotion. The private event is, for example, date / time data such as the date of marriage, the date of divorce, and the date of birth. And each item memorize | stored in the personnel data memory | storage part 21 is a 1st item, a collection of 1st items is a 1st item group, and item data which shows the result of a 1st item as a log | history becomes 1st data. .

As shown in FIG. 2B, the attendance data storage unit 22 stores a attendance record 22a in which attendance data about attendance of each employee is stored. The attendance record 22a is associated with an employee code, and item data as an attendance history is recorded in the attendance record 22a. Specifically, item data such as total working hours, total overtime hours, late-night overtime hours, and holiday work hours are recorded as time data, and the number of working days, overtime days, business trip days, and leave as day / count data Item data such as the number of times and the number of night shifts is recorded. Furthermore, item data such as attendance time, leaving time, and paid digestion rate are recorded as time data. And each item memorize | stored in the attendance data storage part 22 is a 1st item, the collection of 1st items is a 1st item group, and the item data which shows the result of a 1st item as a log | history becomes 1st data. .

As shown in FIG. 2C, the salary data storage unit 23 records a salary record 23a in which salary data of each employee is stored. In the salary record 23a, data as salary history is recorded in association with the employee code. Specifically, item data of salary data such as monthly salary, bonus and annual salary of each employee is recorded in the salary data storage unit 23. And each item memorize | stored in the attendance data storage part 22 is a 1st item, the collection of 1st items is a 1st item group, and the item data which shows the result of a 1st item as a log | history becomes 1st data. .

As shown in FIG. 3A, the medical examination data storage unit 24 stores a medical examination record 24a in which medical examination data that is a result of the medical examination of each employee is stored. In the medical checkup record 24a, data indicating the history of the results of the medical checkup is recorded in association with the employee code. Specifically, itemized medical examination item data such as weight, height, waist circumference, and BMI are recorded. The medical examination data storage unit 24 includes image data of X-ray examinations such as chest X-rays and stomach X-rays, image data of MRI examinations such as pelvic cavities such as brain, spine, limbs, uterus, ovary, and prostate, liver Record video data of echo examination of gallbladder, kidney, pancreas, bladder, prostate, uterus, ovary, etc. In addition, CT examination image data may be recorded. The medical examination record 24a can also record the examination results having such images and moving images. And each item memorize | stored in the medical examination data memory | storage part 24 is a 2nd item, the collection of 2nd items is a 2nd item group, and the item data which shows the result of a 2nd item as log | history are 2nd data and Become.

As shown in FIG. 3B, the stress check data storage unit 25 stores a stress check record 25a in which stress check data that is a stress check result of each employee is stored. In the stress check record 25a, stress check history data is recorded in association with the employee code. Specifically, check item data for each item such as comprehensive judgment, work load judgment, work resource judgment (work level, department, office) is recorded. And each item memorize | stored in the stress check data storage part 25 is a 2nd item, the collection of 2nd items is a 2nd item group, and the item data which shows the result of a 2nd item as a log | history are 2nd data Become.

As shown in FIG. 3C, the performance data storage unit 26 stores item data such as sales amount, sales quantity, order amount, etc. as performance data for the entire company, business unit, department unit, and employee unit. The recorded performance record 26a is recorded. In the performance record 26a, in the case of the employee's achievement, the history data of the achievement is recorded in association with the employee code. Specifically, the performance record 26a records item data such as sales amount, sales quantity, order amount, order quantity, and productivity. And each item memorize | stored in the performance data storage part 26 is a 1st item, the collection of 1st items is a 1st item group, and the item data which shows the result of a 1st item as a log | history becomes 1st data. .

As shown in FIG. 3D, the daily data storage unit 27 stores a daily record 27a in which daily data of each employee is stored. The daily record 27a records item data such as activity data, body data, meal data, and habit data in association with the employee code. The activity data is, for example, the number of steps, the amount of exercise, the calorie consumption, the body data is, for example, the body weight, the body fat percentage, the blood pressure, etc. The meal data is the meal intake time, the number of meal intake, the calorie intake, etc. The habit data includes the amount of drinking and smoking. Thereby, for example, regarding blood pressure and body weight, not only blood pressure and body weight at the time of a medical examination but also daily blood pressure and body weight can be managed. And each item memorize | stored in the daily data memory | storage part 27 is a 2nd item, the collection of 2nd items is a 2nd item group, and the item data which shows the result of a 2nd item as a log | history becomes 2nd data. .

As shown in FIG. 3E, the medical data storage unit 28 stores a medical record 28a in which medical data of each employee is stored. The medical record 28a records item data such as the time of medical checkup and examination as a medical event, the start time of internal medicine, the onset time of a disease, the time of cure, and the time of a doctor interview in association with the employee code. Yes. And each item memorize | stored in the medical data memory | storage part 28 is a 2nd item, the collection of 2nd items is a 2nd item group, and the item data which shows the result of a 2nd item as a log | history becomes 2nd data. .

As described above, the item data of personnel performance / time performance related data such as personnel data, attendance data, and performance data is classified as the first data, and each item of health related data such as medical examination data, stress check data, daily data, medical data, etc. Data is classified as second data. Daily data and medical data may be handled as the first data.

Next, the operation when performing the above-described system labor management will be described.
(Data management process)
With reference to FIG. 4, a method for storing various data in the storage units 21 to 27 of the labor management system will be described.

In step S1, the management unit 12 of the management server 10 receives the item data of the personnel data transmitted from the personnel attendance management server 5, and stores it in the personnel data storage unit 21 in association with the employee code. In step S 2, the management unit 12 receives the item data of time data transmitted from the personnel management server 5 and stores it in the time data storage unit 22 in association with the employee code. In step S3, the management unit 12 receives the item data of the salary data transmitted from the personnel attendance management server 5, and stores it in the salary data storage unit 23 in association with the employee code.

In step S4, the management unit 12 of the management server 10 receives the medical examination item data of the medical examination data transmitted from the medical examination management server 6, and stores it in the medical examination data storage unit 24 in association with the employee code. In step S5, the management unit 12 receives the check item data of the stress check data transmitted from the stress check management server 7, and stores it in the stress check data storage unit 25 in association with the employee code. In step S 6, the management unit 12 receives the item data of the daily data transmitted from the employee's client terminal 3 and stores it in the daily data storage unit 27 in association with the employee code. In step S 7, the management unit 12 receives the item data of the medical data transmitted from the employee's client terminal 3 and stores it in the medical data storage unit 28 in association with the employee code. It should be noted that data such as the time of conducting medical examinations and examinations, the start time of internal use, the onset of illness, the time of healing, the time of doctor interviews, etc. should be obtained from the employee's client terminal 3 and the medical examination management server 6. It may be. In step S 8, the management unit 12 receives the item data of the performance data transmitted from the performance management server 8, and stores the employee data in association with the employee code, for example, in the performance data storage unit 26. In step S9, the management unit 12 transmits various data stored in the storage units 21 to 27 to the data warehouse 30 periodically or according to the operation of the operator. The data warehouse 30 stores the received data in the storage unit 31. The analysis unit 32 analyzes the data accumulated in the accumulation unit 31. Details of the data analysis will be described later.

(When the employee himself / herself uses it)
(If there is an abnormality in the medical examination)
With reference to FIG. 5, a case where the employee himself / herself uses and there is an abnormality in the health examination will be described.

When the employee operates the client terminal 3 to send an employee code or the like to the management server 10, the extraction unit 13 accesses the medical examination data storage unit 24 and searches for a medical examination record 24a of the received employee code. . In step S11, the extraction unit 13 determines whether there is an abnormal value in the individual medical examination item data recorded in the medical examination record 24a. Specifically, some of the health check items have appropriate numerical ranges such as body fat percentage, uric acid level, LDL cholesterol, HL cholesterol, etc. There is something that encourages. In the medical examination data storage unit 24, an appropriate range is stored in the definition record for the medical examination item data, and the extraction unit 13 refers to the definition record to determine whether the medical examination item data is abnormal. .

In step S12, the extraction unit 13 extracts medical examination item data having an abnormality, and in step S13, medical examination item data related to the medical examination item data having an abnormality is extracted. For example, when the body fat percentage is abnormal, LDL cholesterol, HLD cholesterol, total cholesterol, and the like, which are medical examination item data related thereto, are extracted. In the medical examination data storage unit 24, related medical examination items are associated with predetermined medical examination item data. The extraction unit 13 refers to this association and extracts medical examination item data related to the abnormal medical examination item. When there is no abnormality in the medical examination item data, the extraction unit 13 extracts a general predetermined medical examination item defined in advance in step S14.

In step S15, the extraction unit 13 accesses the personnel data storage unit 21, searches the personnel record 21a of the received employee code, and extracts personnel item data of the personnel record 21a. In step S16, the extraction unit 13 accesses the attendance data storage unit 22, searches the attendance record 22a of the received employee code, and extracts attendance item data of the attendance record 22a. In step S17, the extraction unit 13 accesses the daily data storage unit 27, searches the daily record 27a of the received employee code, and extracts each item data of the daily record 27a. In steps S15 to S17, the extraction unit 13 extracts predetermined item data determined in advance from each record, and further extracts items selected by the user. Note that all items to be extracted by the user may be freely selected. Further, the predetermined item data determined in advance may be, for example, items extracted by statistical analysis processing described later.

In step S18, the output control unit 14 of the management server 10 generates a report as output data to be transmitted to the client terminal 3 that requested the report. Specifically, the output control unit 14 outputs either one of a first output form in which the graph of the selected item data is aligned vertically and a second output form in which the graph of the selected item data is superimposed. Select to generate a report. Then, the output control unit 14 transmits the report to the client terminal 3 in the requested output form. At the client terminal 3, the report can be displayed on a monitor or printed by a printer so that an employee can view the report.

In addition, if an abnormality is found in the medical examination, findings from a doctor or the like may be described. Such findings are also stored in the medical examination data storage unit 24 in association with the employee code. In step S11, the extraction unit 13 does not extract the abnormal medical examination item and the medical examination item related to the medical examination item, but the medical examination item having the finding and the medical examination related to the medical examination item. Items can also be extracted. The extraction unit 13 can also extract the item and a medical examination item related to the item when abnormality is found in an MRI examination of a chest X-ray, a stomach X-ray, a brain, or an echo examination of the liver.

(First output form)
FIG. 6 is a diagram showing a state in which a report in the first output form in which the graph of the selected item data is vertically aligned is displayed on the monitor. In this report 41, a radio button 42 is provided. With the radio button 42, either the first output form of the vertically arranged display or the second output form of the superimposed display can be selected. Here, the vertically arranged display is selected. The first output form for displaying is selected. In the report 41, a combination pattern can be selected from a pull-down menu. In this first pull-down menu 43, “confirmation of health check result”, “confirmation of stress check result”, etc. can be selected, and “confirmation of medical check result” is selected here. In addition, a second pull-down menu 44 for selecting target data to be displayed is provided. In the second pull-down menu 44, one of “attendance”, “personnel”, “stress check result”, “health check”, and “daily” can be selected as a large item designation item. Then, with respect to the selected large item, item data can be selected as a small item of the designated item. In the example of FIG. 6, “Attendance”, “Personnel”, and “Medical Examination” are selected, and the output control unit 14 is the extraction unit 13, and the medical examination of the attendance data storage unit 22 and the personnel data storage unit 21 is performed. The data storage unit 24 is accessed, and the data of the selected small item is extracted and added to the report 41. Specifically, “weight”, “total cholesterol”, and “LDL cholesterol” are selected in the “health checkup”, and the output control unit 14 uses the extraction unit 13 to select “weight”, “total cholesterol”, “LDL”. “Cholesterol” item data is extracted and added to the report 41. In “Attendance”, “total overtime hours” is selected as a small item, and the output control unit 14 extracts the item data of “total overtime hours” by the extraction unit 13 and adds it to the report 41.

The related item such as “total overtime” displayed as an item related to “health checkup” may be an item selected by an employee, etc., or an item extracted by statistical analysis processing described later. You can also

Then, in the first output form of the vertical display, the graph of “weight”, the graph of “total cholesterol”, the graph of “LDL cholesterol”, and the graph of “total overtime hours” are generated one by one from the top, The items of “department transfer”, “promotion”, and “relocation” are also arranged vertically. Then, data for a period from 2009 to 2014 is further extracted so that the ranges of the time axis coincide with each other, and the position on the time axis of the horizontal axis is aligned and aligned in this period. In such a report 41, the horizontal axis is the time axis, and a plurality of graphs are aligned in a direction orthogonal to the time axis in a state where the positions of the item data on the time axis are aligned and aligned. From this, for example, it is possible to easily grasp another situation when a change is seen in the medical examination result. In the example of FIG. 6, although the weight decreased in 2012, it can be immediately recognized that the year is a year in which the total overtime is further promoted to a section manager.

Further, an upper limit line 45 of an appropriate range is added as an index to the “total cholesterol” graph and the “LDL cholesterol” graph. Thereby, the graph of “total cholesterol” and the upper limit value of “LDL cholesterol” can be easily grasped. Small items such as “Total overtime hours” that are highly relevant to the health checkup items are automatically displayed by statistical analysis, and “health checkups” such as “time attendance” related to the deterioration of the health checkup results It is possible to suppress missing a small item in a large item different from “”.

(Second output form)
FIG. 7 is a diagram illustrating a state in which a report in the second output form on which the graph of the selected item data is superimposed is displayed on the monitor. In the report 51, the second output form for performing superimposed display is selected by the radio button 42. In FIG. 7, the same items as in FIG. 6 are selected. In the report 51, a radio button 52 for selecting a scale of the vertical scale is provided. Here, “total cholesterol” is selected, and the vertical axis is a scale according to “total cholesterol”. In the example of FIG. 7, the graph of each item is aligned so that the positions on the time axis are aligned, and a plurality of graphs are further superimposed. As a result, although the weight decreased in 2012, it is possible to immediately recognize that the year was promoted to section manager and the total overtime was further increased.

In the first output form shown in FIG. 6 and the second output form shown in FIG. 7, “stress check results” and “daily items” may be further selected as major items. When “stress check result” is selected, an item such as “work load determination” may be selected as a small item. Furthermore, when “daily items” is selected, items such as “number of steps” and “exercise amount” may be selected as small items. Thereby, the

report

41 and 51 can grasp | ascertain the relationship of a medical examination result and another item further. In addition, when the output form of either the first output form shown in FIG. 6 or the second output form shown in FIG. 7 is displayed on the monitor of the client terminal 3, the other is not displayed with the radio button 42. When the output form is selected using an operation unit such as a mouse, the output control unit 14 generates output data of the newly selected output form. Then, the client terminal 3 displays a report on the monitor.

(If there is an abnormality in the stress check)
With reference to FIG. 8, the case where the employee himself uses the labor management system and there is an abnormality in the stress check will be described.

When the employee transmits the employee code to the management server 10 by operating the client terminal 3, the extraction unit 13 accesses the stress check data storage unit 25 and searches for the stress check record 25a of the received employee code. . In step S21, the extraction unit 13 determines whether there is an abnormal value in the individual check item data recorded in the stress check record 25a. Specifically, some check item data has an appropriate numerical value range, and there is a check item data that cautions the user if the specified value range is exceeded. In the stress check data storage unit 25, an appropriate range is defined in the definition record for the check item data, and the extraction unit 13 refers to this to determine whether the check item data is abnormal.

In step S22, the extraction unit 13 extracts check item data having an abnormality. If there is no abnormality in the check item data, general predetermined check item data is extracted in step S23. In step S24, the extraction unit 13 extracts main medical examination item data. In the stress check data storage unit 25, related checkup items are associated with predetermined check item data. The extraction unit 13 refers to the association and extracts medical examination item data related to the check item data having an abnormality. This related medical examination item can be, for example, an item extracted by statistical analysis processing described later.

In step S25, the extraction unit 13 accesses the personnel data storage unit 21, searches the personnel record 21a of the received employee code, and extracts personnel item data of the personnel record 21a. This is because personnel changes and job titles can affect stress. In step S26, the extraction unit 13 accesses the attendance data storage unit 22, searches the attendance record 22a of the received employee code, and extracts attendance item data of the attendance record 22a. This is because, for example, there may be a case where the work over a predetermined predetermined time continues for one month. In step S27, the extraction unit 13 accesses the salary data storage unit 23, searches the salary record 23a of the received employee code, and extracts item data of the salary record 23a. In step S28, the extraction unit 13 accesses the performance data storage unit 26 and extracts the performance item data recorded in the employee performance record 26a. For example, the sales amount, sales amount, order value, order quantity, etc. of each month or year of the employee are extracted. In step S29, the extraction unit 13 accesses the daily data storage unit 27, searches the daily record 27a of the received employee code, and extracts item data of the daily record 27a. In steps S25 to S29, the extraction unit 13 extracts predetermined item data determined in advance from each record, and further extracts an item selected by the user. Note that all items may be freely selected by the user. Further, the predetermined item data determined in advance may be, for example, items extracted by statistical analysis processing described later.

In step S30, the output control unit 14 of the management server 10 generates a report in the first output form or a report in the second output form as output data to be transmitted to the client terminal 3 that has requested the report, and requests the report. The report is transmitted to the client terminal 3 where the error occurred. The client terminal 3 can display the report on a monitor or print it with a printer so that the employee can view the report. Thereby, the employee can confirm what is affecting the stress and how the stress is affecting the physical surface.

(When checking the health status regularly)
With reference to FIG. 9, a case where the employee himself / herself uses the labor management system and regularly checks the health condition will be described.

In step S31, the extraction unit 13 determines whether or not the current date and time is the date and time of confirmation of the health check result desired by each employee. For example, the data of the confirmation date is recorded in the medical examination record 24a. When the confirmation date is reached, the extraction unit 13 accesses the medical examination data storage unit 24 in step S32, and the medical examination of the received employee code. The main medical examination items recorded in the record 24a are extracted. In step S33, the extraction unit 13 accesses the stress check data storage unit 25, and extracts the main check item data recorded in the stress check record 25a of the received employee code. In step S34, the extraction unit 13 accesses the daily data storage unit 27 and extracts item data of the daily record 27a of the received employee code. In steps S32 to S34, the extraction unit 13 extracts predetermined item data determined in advance from each record, and further extracts items selected by the user. Note that all items may be freely selected by the user. Further, the predetermined item data determined in advance may be, for example, items extracted by statistical analysis processing described later.

In step S35, the output control unit 14 of the management server 10 generates a report in the first output form or a report in the second output form as output data to be transmitted to the client terminal 3 that has requested the report, and requests the report. The report is transmitted to the client terminal 3 where there is. The client terminal 3 can display the report on a monitor or print it with a printer so that the employee can view the report. Thereby, the employee can confirm regularly whether there is a change in the aspect of a body or stress.

(When there are subjective symptoms such as poor physical condition)
With reference to FIG. 10, the case where the employee himself / herself uses the labor management system and has subjective symptoms such as poor physical condition will be described.

When the employee operates the client terminal 3 to send an employee code or the like to the management server 10, in step S41, the extraction unit 13 accesses the medical examination data storage unit 24 and receives the medical examination record of the received employee code. The main medical examination items recorded in 24a are extracted. In step S42, the extraction unit 13 accesses the personnel data storage unit 21 and extracts personnel item data in the personnel record 21a of the received employee code. In step S43, the extraction unit 13 accesses the time data storage unit 22 and extracts time item data of the time record 22a of the received employee code. In step S44, the extraction unit 13 accesses the daily data storage unit 27 and extracts item data of the daily record 27a of the received employee code. In steps S41 to S44, the extraction unit 13 extracts predetermined item data determined in advance from each record, and further extracts items selected by the user. Note that all items may be freely selected by the user. Further, the predetermined item data determined in advance may be, for example, items extracted by statistical analysis processing described later.

In step S45, the output control unit 14 of the management server 10 generates a report in the first output form or a report in the second output form as output data to be transmitted to the client terminal 3 that requested the report, and requests the report. The report is transmitted to the client terminal 3 where the error occurred. The client terminal 3 can display the report on a monitor or print it with a printer so that the employee can view the report. Thereby, the employee can confirm which item's numerical value has deteriorated among the medical examination items due to poor physical condition when the physical condition is poor. In addition, the employee can confirm the cause of the deterioration also in relation to personnel items and attendance items. In addition, the employee can determine whether or not it is necessary to take a medical examination by looking at the numerical values of the medical examination items. In addition, the employee can search the cause of poor physical condition by looking at the attendance status.

(When used by personnel personnel)
(When overwork or poor work is detected)
With reference to FIG. 11, a case where the personnel manager uses the labor management system and overwork or poor work is detected will be described.

In step S51, the extraction unit 13 accesses the stress check data storage unit 25, and determines whether there is an abnormal value in the individual check item data recorded in the stress check record 25a for each employee. Moreover, the extraction part 13 accesses the attendance data storage part 22, and judges whether there is an abnormal value in the individual attendance item data recorded on the attendance record 22a for every employee. The extracting unit 13 proceeds to step S52 when an abnormality is detected, and ends the process when no abnormality is detected.

In step S52, the extraction unit 13 extracts check item data including check item data in which an abnormality is detected. In step S53, the extraction unit 13 extracts time item data including time item data in which an abnormality is detected. In step S54, the extraction unit 13 accesses the medical examination data storage unit 24 and extracts main medical examination items recorded in the medical examination record 24a. In step S55, the extraction unit 13 accesses the personnel data storage unit 21 and extracts each personnel item data of the personnel record 21a.

The extraction unit 13 may access the daily data storage unit 27 and extract the daily data recorded in the daily record 27a.
In step S56, the output control unit 14 generates a report in the first output form or a report in the second output form as output data to be transmitted to the client terminal 2 that has requested the report, and the client that has requested the report. A report is transmitted to the terminal 2. The client terminal 2 can display the report on a monitor or print it with a printer so that a personnel officer can view the report. Thereby, the person in charge of personnel can immediately find the employee in which the abnormality is recognized in the attendance item data and the check item data. In addition, the personnel manager can easily confirm whether this abnormality is related to the medical examination result or personnel.

(When a leave of absence returns to work)
With reference to FIG. 12, a case where the personnel manager uses the labor management system and the absentee returns to work will be described.

When the client terminal 2 is operated and the employee code of the employee who is going to return to work is transmitted to the management server 10, the extraction unit 13 accesses the stress check data storage unit 25 in step S61, and the stress check record The check item data recorded in 25a is extracted. In step S62, the extraction unit 13 accesses the medical examination data storage unit 24 and extracts main medical examination items recorded in the medical examination record 24a. In step S63, the extraction unit 13 accesses the attendance data storage unit 22 and extracts attendance item data recorded in the attendance record 22a. In step S64, the extraction unit 13 accesses the personnel data storage unit 21 and extracts personnel item data of the personnel record 21a.

In step S65, the output control unit 14 generates a first output form report or a second output form report as output data to be transmitted to the client terminal 2 that has requested the report, and the client that has requested the report. A report is transmitted to the terminal 2. The client terminal 2 can display the report on a monitor or print it with a printer so that a personnel officer can view the report. Thereby, the person in charge of personnel can grasp the stress state, health condition, personnel affairs, attendance status, etc. before the leave of the employee returning to work. In addition, personnel personnel can use reports including stress and health status as reference materials for determining whether the workplace where returning workers are returning to work is appropriate and whether the support system for returning workers is in place. .

(When considering business improvement measures)
With reference to FIG. 13, a case where a personnel manager uses a labor management system and examines a work improvement measure will be described.

When the personnel terminal operates the client terminal 2 and transmits the employee code or the like of the employee to whom the personnel improvement is to be applied to the management server 10, the extraction unit 13 accesses the performance data storage unit 26 in step S 71. Then, the performance item data recorded in the employee performance record 26a is extracted. For example, the extraction unit 13 extracts the sales amount, the sales amount, the order amount, the order amount, etc. of each month or year of the employee. In step S72, the extraction unit 13 accesses the medical examination data storage unit 24 and extracts main medical examination items recorded in the medical examination record 24a. In step S73, the extraction unit 13 accesses the stress check data storage unit 25 and extracts the check item data recorded in the stress check record 25a. In step S74, the extraction unit 13 accesses the time data storage unit 22 and extracts time item data recorded in the time record 22a. In step S75, the extraction unit 13 accesses the personnel data storage unit 21 and extracts personnel item data of the personnel record 21a. In step S76, the extraction unit 13 accesses the salary data storage unit 23 and extracts salary item data of the salary record 23a.

In step S77, the output control unit 14 generates a report in the first output form or a report in the second output form as output data to be transmitted to the client terminal 2 that has requested the report, and the client that has requested the report. A report is transmitted to the terminal 2. The client terminal 2 can display the report on a monitor or print it with a printer so that a personnel officer can view the report. This makes it easy for HR personnel to check whether the employee's poor performance is due to stress, health, personnel, attendance, salary, etc. can do. In addition, it is possible to grasp the health status, stress status, attendance status, etc. of employees with good performance.

(When used by an industrial physician)
(When there is consultation such as poor physical condition)
Referring to FIG. 14, a case where an industrial physician uses a labor management system and a consultation such as poor physical condition is given will be described.

When operating the client terminal 4 to transmit the employee code or the like of the employee that the industrial physician has consulted to the management server 10, in step S81, the extraction unit 13 accesses the medical examination data storage unit 24 to perform the medical examination. The main medical examination items recorded in the record 24a are extracted. In step S82, the extraction unit 13 accesses the stress check data storage unit 25 and extracts the check item data recorded in the stress check record 25a. In step S83, the extraction unit 13 accesses the time data storage unit 22 and extracts time item data recorded in the time record 22a. In step S84, the extraction unit 13 accesses the personnel data storage unit 21 and extracts personnel item data of the personnel record 21a. In step S85, the extraction unit 13 accesses the daily data storage unit 27 and extracts each item data of the daily record 27a.

In step S86, the output control unit 14 generates a report in the first output form or a report in the second output form as output data to be transmitted to the client terminal 4 that has requested the report, and the client that has requested the report. A report is transmitted to the terminal 2. The client terminal 4 can display the report on a monitor or print it with a printer so that an industrial physician can view the report. Thus, the occupational physician can make an examination by referring to the health status, stress status, attendance, personnel, and daily data of the employee who has come to consult. For example, an occupational physician can search for the cause such as whether the cause of poor physical condition is due to overtime or midnight overtime.

(When high stress, overwork or poor work is detected)
Next, a case where an industrial physician uses a labor management system and high stress, overwork, and poor work are detected will be described. In this case, in the management server 10, after processing similar to that in FIG. 11 is performed, the output control unit 14 outputs the report in the first output form as the output data to be transmitted to the client terminal 4 that requested the report or the first output A two-output report is generated, and the report is transmitted to the client terminal 4 that requested the report. The client terminal 4 can display the report on a monitor or print it with a printer so that an industrial physician can view the report. As a result, occupational physicians can immediately find employees who have anomalies in attendance item data and check item data, and how these abnormalities are related to health checkup results and personnel data. It can be easily confirmed. For example, by looking at the results of the medical examination, it can be confirmed whether or not there is a physical influence due to stress. In addition, it is possible to confirm whether self-care is being appropriately performed through an inquiry or the like.

According to the embodiment, the advantages listed below can be obtained.
(1) As shown in FIG. 6 and FIG. 7, the report that is output data is such that the medical examination item data and check item data are displayed in time alignment with other item data such as attendance item data. The operator can easily grasp the correlation between these data. That is, in FIG. 6, since the graphs of the item data are aligned in a vertical alignment with the time axis aligned, the operator can easily grasp the correlation between these data. In FIG. 7, the graph of each item data is superimposed with the time axis aligned, so that the correlation between these data can be easily grasped. The employee's health can be managed in consideration of various aspects such as attendance status and personnel status as well as health checkup results and stress results.

(2) Furthermore, the medical examination item data and the check item data can be displayed or printed in association with the personnel data.
(3) As shown in FIG. 6, whether or not the item data is normal or abnormal is added to the graph of the data of the item having the appropriate range by adding a line serving as an index indicating the upper limit or the lower limit. It can be easily judged.

In addition, the said embodiment can also be suitably changed and implemented as follows.
-The line used as the parameter | index which shows the upper limit and lower limit of the item data which have an appropriate range may be either an upper limit or a lower limit. Further, as shown in FIG. 15, the item data indicating abnormality may be subjected to emphasis processing 46 using a marker or the like. The emphasis process may be bold, italic, side lines, color characters, etc., and is not particularly limited as long as it is a conspicuous process for other item data. The enhancement processing may be performed in the second output form shown in FIG.

In the example of FIG. 7 as well, when the graph of “total cholesterol” and “LDL cholesterol” are selected on the vertical axis, a line indicating the upper limit or lower limit of the appropriate range may be added.
-You may add the lower limit line which shows the lower limit of an appropriate range to each graph of FIG. 6 and FIG.

・ Alternatively, the output data format may be a side-by-side graph. That is, the operator may be able to select any one of the vertically aligned output, the horizontally aligned output, and the superimposed output, or may be output by a combination of the horizontally aligned output and the superimposed output. Further, it may be possible to output in a combination of side by side output. The output form is not limited to the three exemplified here.

-When the time axis is the vertical axis, the plurality of graphs should be arranged side by side so as to be orthogonal to the time axis.
-You may make it add personal data, such as an employee's name, a birth date, and a family structure, to the report shown in FIG.6, FIG.7 and FIG.15.

The data managed by the management server 10 is not limited to the data shown in FIGS. 2 (a) to (c) and FIGS. 3 (a) to (e). Further, the item data constituting the data of FIGS. 2A to 2C and FIGS. 3A to 3E are not limited to the illustrated data.

・ If at least one of medical checkup data and stress check data is added to the report, and attendance data is selected as the other item, the other added data is not particularly limited.

The management server 10 may not be configured to store data in the data warehouse 30.
(Modification 1 of output form)
FIG. 16 is a modification of the first output form (see FIG. 6) in which the graph of the selected item data is aligned vertically. In FIG. 16, “body weight”, “total cholesterol”, and “LDL cholesterol” are selected, and the output control unit 14 is a polygonal line of “weight”, “total cholesterol”, and “LDL cholesterol” extracted by the extraction unit 13. A report including a graph and a bar graph of “total overtime” provided below is generated. In this example, “department change”, “promotion”, and “transfer” are displayed as icons 47. That is, for “change of department”, icons 47 are displayed in the locations of 2009 and 2011, for “transfer”, the icons 47 are displayed in the locations of 2011, and for “promotion”, the locations of 2012 are displayed. An icon 47 is displayed. In addition, for “starting internal use”, an icon 47 is displayed at the 2013 position. According to such an output form, by using the display by the icon 47, a line graph or a bar graph can be displayed larger than the example of FIG. 6, and more items can be displayed as a graph. . The icon 47 defines a color for each item, and makes the color different for each item for easy viewing. For example, the icons for items related to attendance may be different in color such as yellow for icons related to medical data and red for icons related to medical data.

(Modification 2 of output form)
FIG. 17 is a modification of the second output form (see FIG. 7) in which the graph of the selected item data is superimposed. Also in the example of FIG. 17, icons 47 are displayed for “department transfer”, “promotion”, “transfer”, and “start of internal use”.

(Modification 3 of output form)
FIG. 18 is a modification of the output form in which a graph of item data is superimposed for each large item. As shown in FIG. 18, the output control unit 14 stores the data of the small items in the large items for each of the large items of “checkup result”, “time attendance”, and “daily” for the period from 2009 to 2013. Superimposed display. Specifically, in the “checkup result”, line graphs of BMI, abdominal circumference, systolic blood pressure, diastolic blood pressure, blood glucose, and HDL cholesterol are superimposed and displayed with the time axis aligned. In “Attendance”, bar graphs of overtime hours and holiday attendance are displayed with the time axis aligned. In “Daily”, each bar graph of exercise amount and sleep time is displayed with the time axis aligned.

In this output form, in the superimposed display of the graph in each large item, the lower limit value or the minimum value of each small item is set to 0, the upper limit value or the maximum value is set to 10, and the value of each small item data is converted to each small item. Display item data.

Also in this output form, icons 47 are displayed for “department transfer”, “promotion”, “transfer”, and “start of internal use”.
(Modification 4 of output form)
In the output forms of FIGS. 6, 7, and 15 to 18, for example, the display unit of “total overtime hours” is a year unit. This display unit may be switched in units of 1 month, 3 months, 6 months, 1 year, and the like. FIG. 19 shows an example in which the “total overtime hours” is switched from year units to one month units.

(Variation 5 of output form)
FIG. 20A is a modification of the output form using icons while the graph of the selected item data is superimposed. In FIG. 20A, data for the period from 2013 to 2017 is extracted. In the upper part, the overtime is displayed as a bar graph, and in the lower part, the results of the stress check are displayed in five stages. Note that the result of the stress check can be selected by a radio button 61 in a five-step evaluation or a two-step evaluation. The fineness of the evaluation is not particularly limited, and may be a three-level evaluation or a ten-level evaluation. And the structure which can select the fineness of evaluation from several candidates may be sufficient. In the lower part of the stress check result, a remarks column is provided, and the status of acquisition of paid leave, the date of the health checkup, the date of interview with the public health nurse, etc. are entered. In the lower part of the remarks column, the medical examination result is displayed in a superimposed manner as a line graph. Here, the results of the medical examination display neutral fat, blood glucose level, and uric acid level. The vertical axis of the line graph converts the value of each item data with the lower limit value or the minimum value of each item as 0 and the upper limit value or the maximum value as 10. On the vertical axis, an evaluation criterion for the health check result is provided. The evaluation criteria are five stages from A to E, where A is normal, B is mildly abnormal, C is follow-up, D is treatment required, E is being treated, The range of each rank is displayed in a strip shape parallel to the horizontal axis. The evaluation standard for the health check result can be selected from the standard by the Ningen Dock Society or the in-house standard by the radio button 62. Here, the standard by the Ningen Dock Society is selected. Furthermore, when a medical examination is performed using an image or a moving image such as an MRI examination of a chest X-ray, stomach X-ray or brain, or an echo examination of the liver, etc., the X-ray button 64 is displayed in the year of the examination. , MRI button 65 and echo button 66 are displayed. When the X-ray button 64 is pressed, the X-ray image data is displayed. When the MRI button 65 is pressed, the MRI image data is displayed. When the echo button 66 is pressed, the video data of the echo examination is reproduced. Is displayed. The X-ray button 64, the MRI button 65, and the echo button 66 may be displayed only for the year in which there is an abnormality.

Buttons

64, 65, 66 may be displayed.

Furthermore, the transition of the number of steps is displayed as daily data in the lower part of the medical examination result.
Further, the number of smokers and the amount of alcohol consumed are displayed as icons 63 as the inquiry data.
FIG. 20B shows a list of icons 63 used in the output form of FIG.

(Statistical analysis process 1)
By the way, the data warehouse 30 performs statistical analysis processing for selecting data to be displayed on the output screens shown in FIGS. 6, 7, and 15 to 20, and displays the results of the medical examination and the stress check. It is possible to display attendance data and the like that are highly relevant to these.

Specifically, the analysis unit 32 of the data warehouse 30 performs statistical analysis of data accumulated in the accumulation unit 31 as follows. FIG. 21 is a flowchart showing the procedure of the statistical analysis process 1. Specifically, personnel data items stored in the storage unit 31, attendance data items, salary data items, medical checkup data items, stress check data items, performance data items, daily A first target item included in the first target item group of any one of the data item group and the medical data item group, and a second target item group that is one of the item groups other than the first target item group A correlation with the second target item included is calculated.

In step S101, the analysis unit 32 of the data warehouse 30 sets an analysis unit for performing statistical analysis. For example, the analysis unit 32 sets a period for performing analysis such as one month, three months, six months, one year, and so on.

In step S102, the analysis unit 32 sets the first target item and calculates the correlation coefficient of the second target item with respect to the first target item. The correlation coefficient is calculated based on the first target data of the first target item and the second target data of the second target item stored in the storage unit 31. The correlation coefficient takes a real value between -1 and 1, and when close to 1, there is a positive correlation between the two random variables, and when close to -1, there is a negative correlation. When it is close to 0, there is no correlation.

The analysis unit 32 sets the first target item, sets the second target item for the first target item, and sets the first target data of the first target item and the second target item stored in the storage unit 31. Based on the two target data, the correlation coefficient is calculated for each analysis unit. Further, the analysis unit 32 calculates a correlation coefficient between target items having a one-to-one relationship, that is, a correlation coefficient between one first target item and one second target item. The analysis unit 32 calculates a correlation coefficient for all combinations of the first target item and the second target item.

For example, the relationship between the first target item and the second target item is as follows.
(I) Select each item in the medical examination data item group as the first target item, and select each item in the attendance data item group and personnel data item group as the second target item. Select items, items in the stress check data item group, items in the salary data item group, items in the daily data item group, items in the medical data item group, The correlation coefficient for each combination is calculated.

(Ii) Select each item in the stress check data item group as the first target item, and select each item in the medical check data item group and the attendance data item group as the second target item. Select each item, each item in the personnel data item group, each item in the salary data item group, each item in the daily data item group, each item in the medical data item group, The correlation coefficient for each combination is calculated.

(Iii) Select each item in the item group of the performance data as the first target item, and select each item in the item group of the medical examination data and each item in the item group of the attendance data as the second target item. Items, items in personnel data items, items in stress check data items, items in salary data items, items in daily data items, medical data Each item in the item group is selected, and a correlation coefficient for each combination is calculated.

For items such as promotion, demotion, secondment, seconding, single appointment, single appointment cancellation, leave, reinstatement, marriage, divorce, childbirth, etc. in the HR data item group, the data that indicates whether an event has occurred or not To do.

In step S103, the analysis unit 32 extracts a second target item having a high correlation with the first target item as a related item for the first target item. The analysis unit 32 stores a first threshold value as a positive correlation threshold value in a storage unit such as a memory, and stores a second threshold value as a negative correlation threshold value in a storage unit such as a memory. When calculating the correlation coefficient of the second target item with respect to the first target item, the analysis unit 32 correlates the second target item whose correlation coefficient is larger than the first threshold and the second target item smaller than the second threshold. Are extracted as related items.

As another example, the analysis unit 32 determines whether the calculated absolute value of the correlation coefficient is larger than a threshold value stored in a storage unit such as a memory, and the absolute value of the correlation coefficient is larger than the threshold value. The second target item is extracted as a related item having a high correlation.

For example, in the above examples (i) to (iii), the following second target items are extracted as related items with high correlation with respect to the first target items.
(I) When the first target item is the BMI of the medical examination data item group, as related items, overtime hours in the time data item group, marriage or single assignment in the personnel data item group, stress check The work load in the data item group, the exercise amount, the calorie consumption and the calorie intake in the daily data item are extracted.

(Ii) When the first target item is a comprehensive judgment in the stress check data item group, as related items, the overtime hours and the number of days off in the time data item group, the personnel data item group Department transfer, body weight and blood pressure in the item group of medical examination data, blood pressure, number of steps and sleep time in the item group of daily data are extracted.

(Iii) When the first target item is the sales amount in the performance data item group, as related items, the overtime hours and leave days in the time data item group, the total in the medical examination data item group Total judgment in the item group of cholesterol and stress check data and sleep time in the item group of daily data are extracted.

When the second target item, which is a related item for the first target item, is extracted by the analysis unit 32, in step S104, the registration unit 33 assigns identification data to the combination of the first target item and the second target item. Register in memory. For example, a related item for each health check item used for determination of lifestyle-related diseases is registered as a related item for lifestyle-related diseases. For example, metabolic syndrome is determined from abdominal circumference, BMI, systolic blood pressure, diastolic blood pressure, blood glucose, HDL cholesterol, and the like. Therefore, the registration unit 33 sets the abdominal circumference, BMI, systolic blood pressure, diastolic blood pressure, blood glucose, HDL cholesterol, and the like as the first target items. And the 2nd object item which is a related item with respect to each of abdominal circumference, BMI, blood pressure at the time of contraction, blood pressure at the time of expansion, blood glucose, HDL cholesterol, etc. is related. The registration unit 33 registers a combination of each of the first target items related to the metabolic syndrome and a second target item that is a related item related to each of the first target items as a definition of the metabolic syndrome. The management server 10 acquires the definition of the registration unit 33, and acquires the item data of the first target item and the item data of the second target item of the definition selected according to the operation of the employee from each of the storage units 21 to 28. For example, a personal report having a format similar to that shown in FIGS. 6, 7, and 15 to 20 is output.

(When employees see the results of medical examinations)
FIG. 22 is a flowchart illustrating a procedure when an employee views the health check result.
In step S 111, the employee operates the client terminal 3 to transmit an employee code or the like from the client terminal 3 to the management server 10. At this time, when the employee wants to know information related to the metabolic syndrome, the employee selects the definition of the metabolic syndrome registered by the registration unit 33 and transmits the definition to the management server 10.

In step S112, the extraction unit 13 of the management server 10 extracts data of the first target item according to the received definition. For example, when the metabolic syndrome is selected, the BMI item data related to the metabolic syndrome is extracted as the first target item. Similarly, the extraction unit 13 extracts item data of abdominal circumference, systolic blood pressure, dilated blood pressure, blood glucose, and HDL cholesterol as the first target item.

In step S113, the extraction unit 13 extracts a second target item that is a related item for each first target item. For example, overtime hours in the target item group of attendance data, which is related information of BMI as the first target item, marriage or single assignment in the target item group of personnel data, in the target item group of stress check data Item data of work load, amount of exercise, calorie consumption and calorie intake in the target item group of daily data are extracted.

In addition, you may make it extract the item selected by the user.
In step S114, the output control unit 14 of the management server 10 generates a report as output data to be transmitted to the client terminal 3 that has requested the report. The output control unit 14 transmits the report to the client terminal 3 in the requested output form. The client terminal 3 can display reports in a format similar to that shown in FIGS. 6, 7, and 15 to 20 on a monitor or print it with a printer so that employees can view the reports.

FIG. 23 is a diagram illustrating a report output form.
In the report 41 of FIG. 23, the graph of the selected item data is superimposed and displayed. In the report 41, a combination pattern can be selected from a pull-down menu. In the first pull-down menu 43, in addition to items such as “confirmation of medical checkup result”, “confirmation of stress check result” and the like can be selected. Further, here, the definition selected by the user is “ Metabolic syndrome "is selected. In addition, a second pull-down menu 44 for selecting target data to be displayed is provided. In the second pull-down menu 44, it is possible to select from “Attendance”, “Personnel”, “Stress Check Result”, “Health Checkup”, and “Daily” as the major item designation. The selected large item can further select item data as a small item of the designated item. In the example of FIG. 23, “Attendance”, “Personnel”, “Stress Check”, “Health Checkup”, and “Daily” are selected in accordance with the selected “Metabolic Syndrome”. The output control unit 14 is selected by the extraction unit 13 by accessing the personnel data storage unit 21, the attendance data storage unit 22, the medical examination data storage unit 24, the stress check data storage unit 25, and the daily data storage unit 27. Data of small items is extracted and added to the report 41. In the report 41, the position of each item on the time axis is aligned and aligned, and a plurality of graphs are superimposed, so that each data related to the metabolic syndrome is not only a medical examination result but also personnel and attendance. It can be confirmed together with the item.

As shown in FIG. 23, when the report 41 is displayed on the monitor of the client terminal 3, if the vertical display is selected by the radio button 42 using the operation unit such as a mouse, the output control unit 14 Generates the output data of the output form of the vertically arranged display newly selected. Then, the newly generated output data in the output form is displayed on the monitor of the client terminal 3.

(Statistical analysis process 2)
The analysis unit 32 of the data warehouse 30 performs statistical analysis of data accumulated in the accumulation unit 31 as follows. Specifically, the analysis unit 32 includes an item group in the personnel data accumulated in the accumulation unit 31, an item group in the attendance data, an item group in the salary data, an item group in the medical examination data, a stress The first target item and the second target of the first target item group including the item group in the check data, the item group in the performance data, the item group in the daily data, and the item group in the medical data The correlation between the item group and the second target item is calculated by multiple regression analysis, and a relational expression indicating the relationship between the first target item and the second target item is generated.

FIG. 24 is a flowchart showing the procedure of the statistical analysis process 2.
In step S121, the analysis unit 32 of the data warehouse 30 sets an analysis unit for performing statistical analysis. For example, the analysis unit 32 sets a period for performing analysis such as one month, three months, six months, one year, and so on.

In step S122, the analysis unit 32 sets the first target item (objective variable), sets the second target item (explanatory variable) for the first target item, and stores the first target item stored in the storage unit 31. Based on the first target data and the second target data of the second target item, a multiple regression analysis is performed for each analysis unit, and t between the first target item (objective variable) and the second target item (explanatory variable) Calculate the value. The analysis unit 32 calculates t values of a plurality of second target items (explanatory variables) for one first target item (object variable). The t value is a value indicating that the larger the absolute value, the greater the influence.

Specific examples of the relationship between the first target item and the second target item include the following.
(I) When the first target item (objective variable) is an item in the item group of medical examination data, the second target item (explanatory variable) is an item in the item group of attendance data, an item of personnel data Each item in the group, each item in the stress check data item group, each item in the salary data item group, each item in the daily data item group, each item in the medical data item group item.

(Ii) When the first target item (objective variable) is each stress check item in the stress check data item group, the second target item (explanatory variable) is each item in the medical check data item group, attendance Each item in the data item group, each item in the personnel data item group, each item in the salary data item group, each item in the daily data item group, and each medical data item group Each item in.

(Iii) When the first target item (objective variable) is an item in the item group of performance data, the second target item (explanatory variable) is an item in the item group of medical examination data, an item of attendance data Each item in the group, each item in the personnel data item group, each item in the stress check data item group, each item in the salary data item group, each item in the daily data item group Item, each item in the medical data item group.

In step S123, the analysis unit 32 excludes the second target item (explanatory variable) from which the t value obtained by the multiple regression analysis does not satisfy the condition stored in the storage unit such as a memory. And the analysis part 32 performs a multiple regression analysis again. Specifically, the analysis unit 32 excludes the explanatory variable having a t value of t ² <2 from the target, performs the multiple regression analysis again, and repeats the overlapping until the t values of all the explanatory variables become t ² ≧ 2. Repeat the regression analysis. Accordingly, the second target item having a low correlation with the first target item can be excluded from the target, and the remaining second target item becomes the related item.

In step S124, when the t values of all the explanatory variables become t ² ≧ 2, the analysis unit 32 obtains the slope and the intercept from the result of the multiple regression analysis and generates a relational expression between the objective variable and the explanatory variable. .

FIG. 25 is a diagram showing a multiple regression analysis.
X1 to X8 are explanatory variables, and Y is an objective variable. In the first multiple regression analysis, since the t values of the explanatory variables X1, X5, and X6 are t ² <2, the explanatory variables X1, X5, and X6 are excluded. In the second multiple regression analysis, since the t value of the explanatory variable X7 is t ² <2, the explanatory variable X7 is excluded. The third regression analysis, all explanatory variables X2, X3, X4, t value X8 is ^{t 2} ≧ 2, and the extracted as a related item.

Further, the following expressions are generated as relational expressions.
Y = aX2 + bX3 + cX4 + dX8 + e
* When a, b, c, d are inclined, and e is an intercept, the second analysis item 32 is extracted as a related item for the first target item. In step S124, the registration unit 33 And the combination of the second target item and the relational expression are registered in a storage unit such as a memory. Using the data stored in the data warehouse 30, the analysis unit 32 generates relational expressions of the second target item (explanatory variable) for various first target items (objective variables) and registers them in the storage unit. .

(Individual future prediction)
FIG. 26 is a flowchart of a process for predicting the future of individual employees.
The analysis unit 32 predicts the future value of the first target item (objective variable) of each employee according to the relational expressions generated in FIGS. In step S131, the analysis unit 32 selects, for example, a first target item (object variable Y) of an employee who performs future prediction from a list. For example, the analysis unit 32 selects any of an item in the item group of the medical examination data, an item in the item group of the stress check data, and an item in the item group of the performance data. Then, the analysis unit 32 sets a relational expression of the selected first target item (object variable).

In step S132, the analysis unit 32 extracts the second target item (explanatory variable X) used in the set relational expression.
In step S133, the analysis unit 32 designates a specific date (year / month / day) for performing future prediction. The analysis unit 32 calculates the value of the second target item (explanatory variable X) on a future specific date by the least square method.

In step S133, the analysis unit 32 calculates the first target item (object variable Y) by applying the value of the second target item (explanatory variable X) calculated in step S124 to the calculation formula.
The extraction unit 13 of the management server 10 acquires the second target item (explanation variable X) and the first target item (object variable Y) calculated by the analysis unit 32, and in the report of the format shown in FIG. Report the value of the first target item (objective variable Y) in the future, or comments from experts based on this value to the employee.

According to the statistical analysis processes 1 and 2, the advantages listed below can be obtained.
(1) As shown in FIG. 21, the analysis unit 32 calculates the correlation of the second target item with respect to the first target item, and registers the second target item with high correlation as the related item. Data relating to related items can be included in the report 41. Therefore, the employee or the like can know, for example, a specific medical examination item and a related item highly related thereto.

(2) When extracting the related items, it is possible to give a degree of freedom to the extraction of the related items by specifying the period as the analysis unit. There is no need to set an unnecessarily long period and perform related item extraction processing.

(3) In addition to the medical examination data item group, the stress check data item group, and the attendance data item group, many items such as personnel data items and performance data items are included. A related item for one target item can be extracted. That is, it is possible to widen the range in which related items for the first target item are extracted. Accordingly, the second target item having a high correlation with the first target item can be selected from a wide range of items.

(4) As shown in FIGS. 23 and 24, explanatory variables with high correlation can be extracted by multiple regression analysis.
(5) By generating the relational expression, the future of the first target item (objective variable) can be predicted for each employee, and the employee can be notified of the prediction result.

(6) Since the report to be reported to the employee includes the first target item and a related item having a high correlation with the first target item, the employee who sees this also relates to the relationship between the first target item and the related item. Can be easily grasped.

(7) Since the report displays the first target item and the related item with the same time axis, the correlation between these items can be easily grasped.
Note that the statistical analysis processes 1 and 2 can be implemented with appropriate modifications as follows.

The report may be acquired not only by the employee but also by a personnel officer or an industrial physician by operating each terminal.
-The report may be displayed as a list, not as a graph.

・ Setting of analysis unit may be omitted.
The analysis unit 32 and the registration unit 33 may be provided in the management server 10. Further, the management server 10 may be provided with the function of the storage unit 31 of the data warehouse 30.

Claims

A first item group including at least one of an attendance item group and a personnel item group;
A second item group including at least one of a health checkup item group and a stress check item group;
1st data which shows the result of each 1st item which comprises said 1st item group, Comprising: This 1st data is data which shows the result of each 1st item in an employee as history. When,
The second data indicating a result of each second item constituting the second item group, wherein the second data is data indicating a result of the second item in the employee as a history. Data and
A storage unit for storing the first data and the second data;
An input unit in which at least one first item and at least one second item are respectively input as designated items;
An output control unit that controls output to the output unit so that the output unit outputs a graph indicating the result of each specified item, wherein the graph includes the first data and the second data stored in the storage unit. And a position on the time axis of the result of each specified item is matched between the specified items, and the output control unit.
The output control unit controls the output so that the output unit outputs a graph for each of the specified items one by one, and the time axis ranges of the graphs match each other. Labor management system.
The labor management system according to claim 2, wherein the output control unit controls the output so that the graphs are aligned in a direction orthogonal to the time axis.
The labor management system according to claim 1, wherein the output control unit controls the output so that results of the designated items overlap in one graph.
The output control unit has an appropriate range for the result of each second item, and further adds an index indicating whether or not the result of the second item is within the appropriate range to the graph indicating the result of the second item The labor management system according to any one of claims 1 to 4.
Analyzes whether the correlation of the other item with respect to either one of the first item constituting the first item group and the second item constituting the second item group satisfies a condition indicating a high degree of correlation. An analysis unit,
The labor management system according to any one of claims 1 to 5, wherein the analysis unit extracts the other item as a related item for the one item when the condition is satisfied.
Defining at least one of the time items group and the personnel items group as the first item group;
Defining at least one of a health checkup item group and a stress check item group as a second item group;
Defining first data indicating a result of each first item constituting the first item group, wherein the first data is data indicating a result of the first item in an employee as a history; And
Defining second data indicating a result of each second item constituting the second item group, wherein the second data is data indicating a result of the second item in the employee as a history; , That,
Storing the first data and the second data in a storage unit;
Inputting at least one of the first items and at least one of the second items as designated items by the input unit;
The output control unit controls output to the output unit so that the output unit outputs a graph indicating the result of each specified item, and the graph stores the first data and the second data stored in the storage unit. And a position on the time axis of the result of each specified item is matched between the specified items. A labor management method.
Defining at least one of the time items group and the personnel items group as the first item group;
Defining at least one of a health checkup item group and a stress check item group as a second item group;
Defining first data indicating a result of each first item constituting the first item group, wherein the first data is data indicating a result of the first item in an employee as a history; And defining second data indicating a result of each second item constituting the second item group, wherein the second data is data indicating a result of the second item for the employee as a history. And that
Causing a computer to function as means for storing the first data and the second data in a storage unit;
Inputting at least one of the first items and at least one of the second items as designated items by the input unit;
Causing the output control unit to control the output to the output unit so that the output unit outputs a graph indicating the result of each specified item, wherein the graph is stored in the storage unit. 1. The labor management program comprising: one data and the second data, wherein the position of the result of each specified item on the time axis is matched between the specified items.
An accumulation unit for accumulating data indicating the results of each item constituting the item group of the attendance data, the item group of the health check data, and the item group of the stress check data together with the history;
A first target item group which is one of the item group of the attendance data, the item group of the health check data, and the item group of the stress check data;
A second target item group that is at least one item group other than the first target item group;
First target data which is data indicating a result of each first target item constituting the first target item group as a history;
Second target data which is data indicating a result of each second target item constituting the second target item group as a history;
An labor management system comprising: an analysis unit that extracts the second target item as a related item when the correlation of the second target item with respect to the first target item satisfies a condition indicating a high level of correlation.
The labor management system according to claim 9, wherein the analysis unit sets a period to be an analysis unit and extracts the second target item as the related item in the set period.
The storage unit further stores data indicating a result of each item constituting the item group as a history with respect to at least one item group of the personnel data item group and the performance data item group. Labor management system described in 1.
The labor management system according to any one of claims 9 to 11, wherein the analysis unit excludes the second target item that does not satisfy the condition from the related items by multiple regression analysis.
The analysis unit calculates the second target data on a specific date in the future regarding the second target item extracted as the related item, and the first date on the specific date based on the calculated second target data. The labor management system according to claim 12, wherein target data is calculated.
An output control unit that controls output to the output unit such that the output unit outputs the first target data of the first target item and the second target data of the second target item extracted as the related item. Item 14. The labor management system according to any one of Items 9 to 13.
Storing in the storage unit data indicating the results of each item constituting the item group of the attendance data, the item group of the health check data and the item group of the stress check data together with the history,
Defining one of the item group of the attendance data, the item group of the health check data, and the item group of the stress check data as a first target item group;
Defining at least one item group other than the first target item group as a second target item group;
Defining first target data which is data indicating a result of each first target item constituting the first target item group as a history;
Prescribing second target data that is data indicating a result of each second target item constituting the second target item group as a history;
When the correlation of the second target item with respect to the first target item satisfies a condition indicating a high level of correlation, the second target item is extracted as a related item by the analysis unit;
Labor management method comprising.
Causing the computer to function as means for accumulating in the accumulator the data indicating the results of each item constituting the item group of the attendance data, the item group of the health check data and the item group of the stress check data, together with the history,
Defining one of the item group of the attendance data, the item group of the health check data, and the item group of the stress check data as a first target item group;
Defining at least one item group other than the first target item group as a second target item group;
Defining first target data which is data indicating a result of each first target item constituting the first target item group as a history;
Prescribing second target data that is data indicating a result of each second target item constituting the second target item group as a history;
When the correlation of the second target item with respect to the first target item satisfies a condition indicating a high level of correlation, causing the computer to function as means for causing the analysis unit to extract the second target item as a related item;
Labor management program with