JP6493753B2 - Medical data analysis system and medical data analysis program - Google Patents

Description

  The present invention relates to a medical data analysis system and a medical data analysis program for analyzing an acute medical hospital based on medical data (DPC data) submitted from and collected by an acute medical hospital.

  Conventionally, a system for grasping the position of a medical institution based on analysis of medical data or the like has been proposed.

For example, Patent Document 1 (Japanese Patent Application Laid-Open No. 2011-209851) describes inpatient information indicating whether a patient is hospitalized at a medical institution or another hospital, and whether the discharge destination is the hospital. Refers to a medical database that stores discharge information indicating whether it is another hospital as a medical record in which one patient is hospitalized as a unit, and the rate of hospitalization from the hospital or other hospital, The medical institution is classified into medical cooperation system classifications indicating the nature of the medical institution in the medical cooperation system according to a combination of the calculating means for calculating the discharge rate, and the calculated hospitalization rate and discharge rate. There is disclosed a medical information processing apparatus comprising a classification means for outputting.
JP2011-209851A

  Although it is possible to analyze the position of the conventional technology that indicates the nature of the medical institution in the medical cooperation system, it is not possible to grasp the position of the own hospital with the surrounding competing hospitals, and in the future There was a problem that it was not possible to obtain information useful for formulating a plan to expand the medical function of the hospital.

  By the way, at present, a major medical care system according to DPC (Diagnosis Procedure Combination) is adopted in major acute hospitals. In this medical fee system, DPC data for receiving medical fees is collected for medical institutions targeted for acute medical care. If such data can be used, it may serve as a guideline for positioning the hospital, but accurate information could not be obtained even if a large amount of data was analyzed.

This invention solves the said subject, The medical data analysis system which concerns on this invention performs analysis of an acute medical hospital based on the medical data which are submitted from an acute medical hospital, and are totaled and announced A medical data analysis system, an acute medical hospital database that stores acute medical hospital data, a medical database that stores medical data of acute medical hospitals, an area setting unit that sets a predetermined arbitrary area, The acute medical hospital selection unit for selecting an arbitrary acute medical hospital from the acute medical hospitals in the area set by the area setting unit, and the acute medical hospital selected by the acute medical hospital selection unit Based on the medical data acquisition unit for acquiring medical data, the acute medical hospital database, and the medical data acquired by the medical data acquisition unit, In the acute care hospital to the eye, characterized in that it has a bed occupancy calculation unit for calculating whether dealing with what admissions per bed for one month, the.

In the medical data analysis system according to the present invention, the bed use calculation unit calculates how many hospitalizations are handled per bed in one month for all acute medical hospitals in the setting area. Features.

  In addition, the medical data analysis system according to the present invention has a disease rate calculation unit that calculates a disease rate in an acute medical hospital of interest based on the medical data acquired by the medical data acquisition unit. To do.

  The medical data analysis system according to the present invention is characterized in that the disease ratio of all acute medical hospitals in a set area is calculated by the disease ratio calculation unit.

  In addition, the medical data analysis system according to the present invention includes a display unit that displays the number of cases per bed calculated by the bed use calculation unit in one month and the disease rate calculated by the disease rate calculation unit. It is characterized by having.

  In the medical data analysis system according to the present invention, the predetermined area set by the area setting unit is a secondary medical area.

  In the medical data analysis system according to the present invention, the predetermined area set by the area setting unit is a secondary medical area and an area adjacent to the secondary medical area.

The medical data analysis program according to the present invention is a medical data analysis program for causing a computer to analyze an acute medical hospital based on medical data submitted from an acute medical hospital and aggregated and published. An acute medical hospital database that stores medical data for the acute care period, and a medical database that stores medical data for the acute medical care hospital, and an area setting step for setting a predetermined arbitrary area, and the area setting step An acute medical hospital selection step for selecting an arbitrary acute medical hospital from acute medical hospitals in the set area, and medical data of the acute medical hospital selected by the acute medical hospital selection step are acquired. Acquired in the medical data acquisition step, the acute medical hospital database, and the medical data acquisition step On the basis of the and medical data, in acute care hospitals of interest, characterized in that it execution and bed occupancy calculation step of calculating whether dealing with what admissions per bed for one month, the.

  In addition, the medical data analysis program according to the present invention calculates, by the bed use calculation step, how many hospitalizations are handled per bed in one month for all acute medical hospitals in the setting area. Features.

  Further, the medical data analysis program according to the present invention executes a disease ratio calculation step of calculating a disease ratio in an acute medical hospital of interest based on the medical data acquired in the medical data acquisition step. And

  The medical data analysis program according to the present invention is characterized in that the disease ratios of all acute medical hospitals in the set area are calculated by the disease ratio calculation step.

  In addition, the medical data analysis program according to the present invention includes a display step of displaying the number of cases per bed calculated in the bed use calculation step and the disease ratio calculated in the disease ratio calculation step in one month. It is characterized by performing.

  The medical data analysis program according to the present invention is characterized in that the predetermined area set in the area setting step is a secondary medical area.

The medical data analysis program according to the present invention is characterized in that the predetermined area set in the area setting step is a secondary medical area and an area adjacent to the secondary medical area.

  According to the medical data analysis system and the medical data analysis program according to the present invention, it is possible to grasp the position of the own hospital with the surrounding competing hospitals, etc. Effective information can be obtained.

It is a figure which shows an example of the computer which can perform the medical data analysis system which concerns on embodiment of this invention. It is a figure which shows the data structure in each database used with the medical data analysis system which concerns on embodiment of this invention. It is a figure explaining the mesh used with the medical data analysis system which concerns on embodiment of this invention. It is a figure which shows the flowchart of the process process by the medical data analysis system which concerns on this invention. It is a figure explaining the setting pattern at the time of setting the predetermined area containing a target acute medical hospital. It is a figure explaining each setting in the medical data analysis system which concerns on this invention. It is a figure which shows an example of area population distribution and area prediction population distribution. It is a figure which shows an example of the patient generation number according to age. It is a figure which shows notionally the calculation method of a demand growth rate. It is a figure which shows the example of an output of the result in the medical data analysis system which concerns on this invention. It is a figure which shows the flowchart of the process process by the medical data analysis system which concerns on other embodiment of this invention. It is a figure which shows the example of an output of the result in the medical data analysis system which concerns on other embodiment of this invention. It is a figure which shows the flowchart of the process process by the medical data analysis system which concerns on other embodiment of this invention. It is a figure which shows the example of an output of the result in the medical data analysis system which concerns on other embodiment of this invention.

  Hereinafter, embodiments of the present invention will be described with reference to the drawings. FIG. 1 is a diagram showing an example of a computer constituting a medical data analysis system according to an embodiment of the present invention. In FIG. 1, 10 is a system bus, 11 is a CPU (Central Processing Unit), 12 is a RAM (Random Access Memory), 13 is a ROM (Read Only Memory), 14 is a communication control unit that controls communication with an external information device, 15 is an input control unit such as a keyboard controller, 16 is an output control unit, 17 is an external storage device control unit, 18 is an input unit composed of input devices such as a keyboard, pointing device, and mouse, 19 is an output unit such as a printing device, Reference numeral 20 denotes an external storage device such as an HDD (Hard Disk Drive), 21 denotes a graphic control unit, and 22 denotes a display device.

In FIG. 1, the CPU 11 retrieves and acquires data by communicating with an external device in accordance with a program ROM stored in the ROM 13 or a program stored in the large-capacity external storage device 20. Processing of output data in which graphics, images, characters, tables, etc. are mixed is executed, and management of a database stored in the external storage device 20 is further executed.

  Further, the CPU 11 comprehensively controls each device connected to the system bus 10. The program ROM in the ROM 13 or the external storage device 20 stores an operating system program (hereinafter referred to as OS) that is a basic program for controlling the CPU 11. The ROM 13 or the external storage device 20 stores various data used when performing output data processing or the like. The RAM 12 as a main memory functions as a main memory, work area, and the like for the CPU 11.

  The input control unit 15 controls the input unit 18 from a keyboard or a pointing device (not shown). The output control unit 16 performs output control of the output unit 19 such as a printer.

  The external storage device control unit 17 is an external storage device 20 such as an HDD (Hard Disk Drive) or a floppy disk (FD) that stores a boot program, various applications, font data, user files, editing files, printer drivers, and the like. Control access to. A system program for realizing the medical data analysis system of the present invention is stored in the external storage device 20 as described above. The graphic control unit 21 is configured to perform drawing processing on information to be displayed on the display device 22.

  Further, the communication control unit 14 controls communication with an external device via a network, thereby acquiring data required by the system from a database held by an external device on the Internet or an intranet, It is configured to be able to send information to an external device.

  In addition to an operating system program (hereinafter referred to as OS) that is a control program for the CPU 11, the external storage device 20 is installed with a system program for operating the medical data analysis system of the present invention on the CPU 11, data used in the system program, and the like. Saved and remembered.

  The data used in the system program for realizing the medical data analysis system of the present invention is basically assumed to be stored in the external storage device 20, but in some cases, these data may be It is also possible to configure to acquire from an external device on the Internet or an intranet via the communication control unit 14. The data used in the system program for realizing the medical data analysis system of the present invention can also be obtained from various media such as a USB memory, a CD, and a DVD.

  Next, a medical data analysis system according to the present invention that can be executed by a computer having the above system configuration will be described.

  First, a database used in the medical data analysis system according to the present invention will be described. FIG. 2 is a diagram showing a data structure in each database used in the medical data analysis system according to the embodiment of the present invention, and FIG. 2A is a diagram schematically showing a data structure of the acute medical hospital database. 2 (b) is a diagram schematically showing the data structure of the medical database, FIG. 2 (c) is a diagram schematically showing the data structure of the population distribution database, and FIG. 2 (d) is the patient age. It is a figure which shows the data structure of a database typically. It is assumed that these data are stored in the external storage device 20, but the external storage device 20 may be configured to acquire from an external device on the Internet or an intranet via the communication control unit 14.

The acute medical hospital database shown in FIG. 2 (a) includes “hospital name data” relating to the name of the acute medical hospital, “location data” relating to the location of the acute medical hospital, and possessed by the acute medical hospital. The “bed number data” relating to the number of beds to be stored is stored. In particular, the “location data” makes it possible to grasp in which mesh the acute care medical hospital will be described later.

  In the medical data analysis system according to the present invention, data related to DPC (Daignosis Procedure Combination) compiled and published by the Ministry of Health, Labor and Welfare is referred to as “medical data”.

  The medical data analysis system according to the present invention uses the medical data related to DPC as described above, and the relationship between the target acute medical hospital of interest and other competing hospitals around the target acute medical hospital By clarifying the gender, the position of the target acute care hospital is grasped.

  As part of the medical system reform, DPC has been introduced as a medical fee compensation system for acute care hospitals that are responsible for acute care, such as university hospitals. Etc.). Hospitals participating in this system are obliged to submit DPC data (medical data) to the Ministry of Health, Labor and Welfare, and some of them are compiled and published on the Ministry of Health, Labor and Welfare website.

  In the medical database shown in FIG. 2 (b), at least the data of the items “submission source hospital name data”, “main diagnosis group data”, “disease data”, “average hospitalization date data”, and “number of cases data” Is remembered.

  “Submission hospital name data” is data relating to which acute hospital submitted to the Ministry of Health, Labor and Welfare. The “main diagnosis group data” is data that records which main diagnosis group the treatment is performed. There are a total of 18 main diagnosis groups. The “disease data” is data that records which disease has been treated. The disease type is about 2900. The “average hospital stay data” is data in which the average number of days hospitalized for the treatment of diseases in the main diagnosis group is recorded. The “number data” is data indicating the number of cases where the submitting hospital deals with the diseases of the main diagnosis group.

  The population distribution database shown in FIG. 2C is a database based on the ground surface divided into square meshes based on latitude and longitude. Here, the concept of mesh is the same as that conventionally known. FIG. 3 is a diagram for explaining a mesh used in the medical data analysis system according to the embodiment of the present invention.

  The population distribution database stores at least data of items of “mesh number”, “population data by age group”, and “assumed value data”. Each mesh is assigned a unique number, and this number is recorded in the “mesh number”. Further, the “population data by age group” records the population by age group living in the corresponding mesh. Further, in the “assumed value data”, assumed values (survival rate, birth rate, transfer rate) for each prefecture relating to the transition of the population living in the corresponding mesh are recorded.

  In the patient age database shown in FIG. 2D, patient age classes are defined as shown in the figure. As patient age classes, "0-5 years old" class, "6-15 years old" class, "16-20 years old" class, "21-40 years old" class, "41 years old-" Seven classes are defined: a class of “60 years old”, a class of “61 years old to 80 years old”, and a class of “81 years old”.

In the item of “disease data” in the patient age database, which disease is the disease type of the target disease is recorded. And in the patient age database, “disease data”
The number of patients counted in each of the seven classes for the disease recorded in (1) is converted into data for each class.

  Next, the flow of processing by the medical data analysis system according to the present invention will be described. FIG. 4 is a diagram showing a flowchart of processing steps by the medical data analysis system according to the present invention. FIG. 6 is a diagram for explaining each setting in the medical data analysis system according to the present invention. Note that the settings shown in FIG. 6 are merely exemplary, and the present invention is not limited to this.

  In the flowchart of FIG. 4, first, in step S101, the target acute medical hospital to be analyzed is set by the medical data analysis system according to the present invention. Such setting is made by referring to the acute medical hospital database shown in FIG. 2A by the user of the medical data analysis system.

  This target acute medical hospital corresponds to A in FIG. That is, the process of step S101 is a process in which A of the target acute medical hospital is set on the mesh.

  Next, in step S102, a predetermined area including the target acute medical hospital is set. Such setting is made by the user of the medical data analysis system. The size and shape of the area set in this step is arbitrary, but it may be based on the secondary medical area in the maintenance plan prepared by the local government to secure the medical care normally required in the daily life area. preferable.

  Here, in step S102, the setting pattern for setting a predetermined area including the target acute medical hospital is reduced according to FIG. In FIG. 5, the area surrounded by the dotted line indicates the area set in step S102.

  FIG. 5A shows, for example, a case where the user arbitrarily sets an area as the predetermined area. FIG. 5B shows an example in which the secondary medical area as described above is set as the predetermined area. FIG. 5C shows an example in which a secondary medical area and an area adjacent to the secondary medical area are set. Area setting like FIG.5 (C) is suitable when the acute medical hospital (for example, F hospital in a figure) which should be considered exists in an adjacent area.

  In FIG. 6, the dotted box indicates the area set in step S102 (this setting area is the same as that in FIG. 5B), but when such an area is set. In the subsequent step S103, the acute medical hospital database shown in FIG. 2A is referred to, and other acute medical hospitals in the set area are extracted as candidates. In the example of FIG. 6, it is assumed that B, C, D, and E are extracted as such other acute medical hospitals.

  In the next step S104, an arbitrary acute medical hospital is selected from the acute medical hospitals extracted in step S103. Here, it is assumed that all of B, C, D, and E extracted as other acute care hospitals are selected by the user.

  In subsequent step S105, the medical database shown in FIG. 2B is referred to, and medical data of the target acute medical hospital (A) is acquired. The acquired medical data of the target acute medical hospital (A) is referred to as target medical data, and this amount is represented by Ho.

In subsequent step S106, the medical database shown in FIG. 2B is referred to, and medical data of all acute medical hospitals (A, B, C, D, E) are acquired. The acquired medical data of all acute medical hospitals (A, B, C, D, E) will be referred to as all medical data, and this amount will be expressed as Ht.

  In subsequent step S107, classified target medical data obtained by classifying the target medical data (Ho) for each main diagnosis group is acquired. There are a total of 18 main diagnostic groups. Therefore, n (n = 1, 2, 3,..., 18) is used as a suffix to indicate the main diagnosis group. The classified target medical data classified in this step is represented by Hon (n = 1, 2, 3,..., 18).

  In subsequent step S108, all classified medical data obtained by classifying all medical data (Ht) for each main diagnosis group is acquired. There are a total of 18 main diagnostic groups. Therefore, n (n = 1, 2, 3,..., 18) is used as a suffix to indicate the main diagnosis group. All classified medical data classified in this step is represented by Htn (n = 1, 2, 3,..., 18).

  In subsequent step S109, a share in the set area for each main diagnosis group of the target acute care medical hospital is calculated. This share can be expressed as Hon / Htn (n = 1, 2, 3,..., 18).

  In the subsequent step S110, the population for each age group in the setting area is calculated. For such calculation, the population distribution database shown in FIG. 2 (c) is referred to, and integration is performed for all meshes in the setting area and meshes at the boundary of the setting area, so that the age-specific classification is performed. Population can be calculated. That is, the population by age group is integrated for the mesh in the thick line in FIG.

  For meshes that exist at the boundary of the setting area, calculate the population within the mesh according to the ratio of the area inside the setting area to the area outside the setting area, and integrate only the calculated population within the mesh. May be corrected.

  The population distribution calculated in step S110 is referred to as an area population distribution. FIG. 7A shows an example of the area population distribution calculated in step S110. Here, as the calculated population distribution, according to the patient age database, a class of “0 to 5 years”, a class of “6 to 15 years”, a class of “16 to 20 years”, “21 The class is divided into seven classes: a class of “ages 40 to 40”, a class of “41 to 60 years”, a class of “61 to 80 years”, and a class of “81 to”.

  In the subsequent step S111, the area population distribution and the population distribution database shown in FIG. 2C are referred to, and the future predicted population distribution for each age group in the area is calculated. Assumed value data (survival rate, birth rate, transfer rate) is recorded in the population distribution database, and based on this, the predicted population distribution in the set area is calculated by the cohort method. The population distribution calculated in step S111 is referred to as an area predicted population distribution. FIG. 7B shows an example of the area predicted population distribution calculated in step S111.

In subsequent step S112, the population distribution database shown in FIG. 2 (c) and the patient age database shown in FIG. 2 (d) are referred to, and the age-specific patient incidence for each main diagnosis group is calculated. . (Incidentally, since the number of age-specific patients calculated in step S111 is a nationwide value, the age-specific patient incidence is calculated by dividing by the nationwide age group population.)
FIG. 8 shows age-specific patient incidence rates by taking one main diagnosis group out of 18 main diagnosis groups as an example. Therefore, in step S112, the same age-specific patient incidence rate is calculated 17 in addition.

  In subsequent step S113, a demand growth rate for each main diagnosis group of the target acute care medical hospital is calculated from the area population distribution, the area predicted population distribution, and the age-specific patient incidence. FIG. 9 is a diagram conceptually illustrating a method for calculating the demand growth rate. FIG. 9 shows the calculation of the demand growth rate for each main diagnostic group, and the same calculation is performed for each of the 17 main diagnostic groups.

  In FIG. 9, (a) and (b) constitute the denominator, and (c) and (d) represent the numerator.

  First, calculation of the denominator will be described. The product of the area population distribution in a given age class and the age-specific patient incidence in similar age classes is taken. For example, a population of 0 to 5 years old takes a product with an age-specific patient incidence rate of 0 to 5 years, and a population of 6 to 15 years old takes a product of an age-specific patient incidence rate of 6 to 15 years. Such a product is taken for all age groups, and the sum (Σ) of all products is taken. This is the denominator when calculating the demand growth rate. This denominator is calculated from the current demand for each main diagnosis group of the target acute care hospital.

  Next, calculation of molecules will be described. In the calculation of the numerator, the product of the area-predicted population distribution in a predetermined age group and the age-specific patient incidence in the same age group is taken. For example, a population of 0 to 5 years old takes a product with an age-specific patient incidence rate of 0 to 5 years, and a population of 6 to 15 years old takes a product of an age-specific patient incidence rate of 6 to 15 years. Such a product is taken for all age groups, and the sum (Σ) of all products is taken. This is the numerator when calculating the demand growth rate. This numerator calculates the predicted demand for each major diagnosis group of the target acute care hospital.

  The demand growth rate for each main diagnosis group of the target acute medical hospital is obtained by dividing the predicted demand for the numerator in FIG. 9 by the current demand for the denominator in FIG.

  In the subsequent step S114, the result of the demand growth rate calculated in the previous step is displayed on the display device 22. FIG. 10 is a diagram showing an output example of the result in the medical data analysis system according to the present invention.

  In FIG. 10, among the 18 main diagnosis groups, “01 nerve”, “04 respiratory organ”, “05 circulatory organ”, “06 digestive organ”, “07 musculoskeletal”, “10 endocrine”, “11 kidneys” -Shows an example of analysis of 8 main diagnostic groups of "Urine tract" and "16 trauma". The horizontal axis shows the share, the vertical axis shows the demand growth rate, and the position of the target acute care hospital is plotted. The size of the circle is proportional to the total number of medical data for each main diagnosis group in the setting area. That is, the size of the circle is proportional to the market size in the set area.

  By such analysis by the medical data analysis system according to the present invention, among the medical treatment areas by the main diagnosis group performed by the target acute care medical hospital, which area has a relatively high or low share, that is, the target Identify the main medical functions of acute care hospitals. In addition, future market growth and market size in that area can be judged at the same time, and information that can be used as a reference when making decisions on future capital investment and resource input can be obtained.

  As described above, according to the medical data analysis system and the medical data analysis program according to the present invention, it is possible to grasp the position of the own hospital between the neighboring competing hospitals, the formulation of the future medical function expansion plan of the own hospital, etc. It is possible to obtain effective information.

Next, another embodiment of the present invention will be described. Other embodiments are different from the previous embodiment only in the algorithm of the processing steps, and thus such differences will be described below. FIG. 11 is a diagram showing a flowchart of processing steps by a medical data analysis system according to another embodiment of the present invention. Reference is also made to FIG. 6 as appropriate.

  In step S201, a predetermined area to be analyzed is set. Such setting is made by the user of the medical data analysis system. The size and shape of the area set in this step is arbitrary, but it may be based on the secondary medical area in the maintenance plan prepared by the local government to secure the medical care normally required in the daily life area. preferable.

  In FIG. 6, a dotted box indicates an area set in step S <b> 102 (this setting area is the same as that in FIG. 5B). When such an area is set, in the subsequent step S202, the acute medical hospital database shown in FIG. 2A is referred to, and all acute medical hospitals in the set area are extracted as candidates. In the example of FIG. 6, it is assumed that A, B, C, D, and E are extracted as such other acute medical hospitals.

  In the next step S203, an arbitrary acute medical hospital is selected from the acute medical hospitals extracted in step S202. Here, it is assumed that all of A, B, C, D, and E extracted as acute medical hospitals are selected by the user.

  In subsequent step S204, medical data of all selected acute medical hospitals (A, B, C, D, E) is acquired with reference to the medical database shown in FIG. The acquired medical data of all acute medical hospitals (A, B, C, D, E) will be referred to as all medical data, and this amount will be expressed as Ht.

  In subsequent step S205, all classified medical data obtained by classifying the medical data for each main diagnosis group is acquired. There are a total of 18 main diagnostic groups. Therefore, n (n = 1, 2, 3,..., 18) is used as a suffix to indicate the main diagnosis group. All classified medical data classified in this step is represented by Htn (n = 1, 2, 3,..., 18).

In subsequent step S206, the share in the set area for each main diagnosis group of the acute medical hospital to which attention is paid (here, attention is focused on hospital A) is calculated. This share is H _A n / Htn (n
= 1, 2, 3,..., 18). Here, H _A n represents a number of medical data A hospital.

In the subsequent step S207, a share in the set area for each main diagnosis group of all acute medical hospitals in the set area is calculated. That is, other than A hospital B, C, D, for even E _{hospitals, H B n / Htn, H} C n / Htn, H D n / Htn, H E n / Htn (n = 1,2,3, · .., 18) is obtained. H _B n to H _E n indicates the number of medical data of the hospital B to E Hospital.

  In the subsequent step S208, the share calculated in the previous step is displayed on the display device 22. FIG. 12 is a diagram showing an output example of a result in the medical data analysis system according to another embodiment of the present invention.

  In FIG. 12, among the 18 main diagnostic groups, there are 6 main groups of “01 nerve”, “04 respiratory organ”, “05 circulatory organ”, “06 digestive organ”, “07 musculoskeletal”, and “16 trauma”. The example in which the diagnostic group was analyzed is shown. The horizontal axis represents the share, and the vertical axis represents the main diagnosis group. The position of the acute care hospital in the set area is plotted.

By such analysis by the medical data analysis system according to the present invention, the share of which area of which hospital is relative among the diagnosis areas by main diagnosis group performed by the acute medical hospital in the set area. It is possible to determine what is the main medical function of the acute medical hospital in the area.

  As described above, according to the medical data analysis system and the medical data analysis program according to the present invention, it is possible to grasp the position of the own hospital between the neighboring competing hospitals, the formulation of the future medical function expansion plan of the own hospital, etc. It is possible to obtain effective information.

  Next, another embodiment of the present invention will be described. Other embodiments are different from the previous embodiment only in the algorithm of the processing steps, and thus such differences will be described below. FIG. 13 is a diagram showing a flowchart of processing steps by a medical data analysis system according to another embodiment of the present invention. Reference is also made to FIG. 6 as appropriate.

  In step S301, a predetermined area to be analyzed is set. Such setting is made by the user of the medical data analysis system. The size and shape of the area set in this step is arbitrary, but it may be based on the secondary medical area in the maintenance plan prepared by the local government to secure the medical care normally required in the daily life area. preferable.

  In FIG. 6, a dotted box indicates an area set in step S <b> 102 (this setting area is the same as that in FIG. 5B). When such an area is set, in the subsequent step S302, the acute medical hospital database shown in FIG. 2A is referred to, and all acute medical hospitals in the set area are extracted as candidates. In the example of FIG. 6, it is assumed that A, B, C, D, and E have been extracted as such an acute medical hospital.

  In the next step S303, an arbitrary acute medical hospital is selected from the acute medical hospitals extracted in step S302. Here, it is assumed that all of A, B, C, D, and E extracted as acute medical hospitals are selected by the user.

  In subsequent step S304, referring to the medical database shown in FIG. 2B, medical data of all selected acute medical hospitals (A, B, C, D, E) are acquired.

  In the subsequent step S305, based on the acquired medical data, the number of hospitalizations handled per bed in one month of the acute care hospital (for example, hospital A) of interest is calculated.

  In the subsequent step S306, for hospitals B, C, D, and E other than hospital A, it is calculated how many hospitalizations were handled per bed for one month based on the acquired medical data.

  In the subsequent step S307, a disease ratio is calculated in an acute medical hospital of interest (for example, hospital A). Here, in this example, the diseases are classified into “cancer”, “stroke”, “myocardial infarction”, “diabetes”, and “others”, and the ratio thereof is calculated.

  In the subsequent step S308, the disease ratio is also calculated for B, C, D, and E hospitals other than A hospital. In this step as well, the same classification as the previous step is performed, and the respective ratios are calculated.

  In the subsequent step S309, the number of hospitalizations per hospital bed and the disease ratio calculated in the previous step are displayed on the display device 22. FIG. 14 is a diagram illustrating an output example of a result in a medical data analysis system according to another embodiment of the present invention.

FIG. 14 is a bar graph showing the number of hospitalizations per hospital bed during one month from A hospital to E hospital. In a hospital, when the number of hospitalizations per bed in a month is 1, this indicates that hospitalized patients are replaced in about 30 days. Further, in the bar graph of FIG. 14, it is shown as a guideline what kind of disease an inpatient of the hospital was hospitalized.

  By such an analysis by the medical data analysis system according to the present invention, it is possible to evaluate whether or not the hospital bed in each hospital is operated efficiently.

  As described above, according to the medical data analysis system and the medical data analysis program according to the present invention, it is possible to grasp the position of the own hospital between the neighboring competing hospitals, the formulation of the future medical function expansion plan of the own hospital, etc. It is possible to obtain effective information.

10 ... System bus 11 ... CPU (Central Processing Unit)
12 ... RAM (Random Access Memory)
13 ... ROM (Read Only Memory)
DESCRIPTION OF SYMBOLS 14 ... Communication control part 15 ... Input control part 16 ... Output control part 17 ... External storage device control part 18 ... Input part 19 ... Output part 20 ... External storage device 21 ... Interface unit 21 ... Graphic control unit 22 ... Display device

Claims (14)

A medical data analysis system for analyzing an acute medical hospital based on medical data submitted, aggregated and published by an acute medical hospital,
An acute care hospital database for storing acute care hospital data;
A medical database for storing medical data of acute medical hospitals;
An area setting section for setting a predetermined arbitrary area;
From acute care hospitals in the area set by the area setting unit, and the acute care hospital selector for selecting any acute care hospitals,
A medical data acquisition unit for acquiring medical data of an acute medical hospital selected by the acute medical hospital selection unit;
Based on the acute medical hospital database and the medical data acquired by the medical data acquisition unit, the hospital bed calculates how many hospitalizations are treated per hospital bed in one month in the acute medical hospital of interest. A usage calculator,
A medical data analysis system comprising: The medical data analysis according to claim 1, wherein the hospital bed usage calculation unit calculates how many hospitalizations are handled per hospital bed in a month for all acute medical hospitals in a setting area. system. The medical treatment according to claim 1 or 2, further comprising a disease ratio calculation unit that calculates a disease ratio in an acute medical hospital of interest based on the medical data acquired by the medical data acquisition unit. Data analysis system. The medical data analysis system according to claim 3, wherein the disease ratio calculation unit calculates disease ratios of all acute medical hospitals in a setting area. 5. The display device according to claim 4, further comprising: a display unit configured to display the number of cases per bed calculated for one month calculated by the bed use calculation unit and the disease rate calculated by the disease rate calculation unit. Medical data analysis system. The medical data analysis system according to any one of claims 1 to 5, wherein the predetermined area set by the area setting unit is a secondary medical area. The medical area according to any one of claims 1 to 5, wherein the predetermined area set by the area setting unit is a secondary medical area and an area adjacent to the secondary medical area. Data analysis system. A medical data analysis program that causes a computer to perform an analysis of an acute medical hospital based on medical data submitted, aggregated and published by an acute medical hospital,
An acute care hospital database for storing acute care hospital data;
A medical database that stores medical data of acute medical hospitals ,
An area setting step for setting a predetermined arbitrary area;
From acute care hospitals in the area set by the area setting step, the acute care hospital selection step of selecting any acute care hospitals,
Medical data acquisition step for acquiring medical data of the acute medical hospital selected by the acute medical hospital selection step;
Based on the acute medical hospital database and the medical data acquired in the medical data acquisition step, the hospital bed calculates how many hospitalizations are treated per hospital bed in one month in the acute medical hospital of interest. Usage calculation step;
A medical data analysis program characterized by executing 9. The medical data analysis according to claim 8, wherein the hospital bed usage calculation step calculates how many hospitalizations are handled per hospital bed in a month for all acute medical hospitals in a set area. program. The disease ratio calculation step of calculating a disease ratio in an acute medical hospital of interest based on the medical data acquired in the medical data acquisition step is performed according to claim 8 or 9, Medical data analysis program. The medical data analysis program according to claim 10, wherein the disease ratios of all acute medical hospitals in the set area are calculated by the disease ratio calculation step. The display step of displaying the number of cases per bed calculated in the bed use calculation step and the disease rate calculated in the disease rate calculation step in one month is executed. The medical data analysis program described. The medical data analysis program according to any one of claims 8 to 12, wherein the predetermined area set in the area setting step is a secondary medical area. The medical device according to any one of claims 8 to 12, wherein the predetermined area set in the area setting step is a secondary medical area and an area adjacent to the secondary medical area. Data analysis program.

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