Medical information estimation device and medical information estimation program

Abstract

To provide a medical information estimation device for estimating medical information for an entire population.SOLUTION: A medical information estimation device estimates statistical volumes of a second population for an estimation period by correcting statistical volumes of a first population that matches an outcome condition in first medical data in the estimation period which is a period different from a first period and in which the first medical data is available on the basis of a relation between the statistical volumes of the second population and the statistical volumes of the first population that matches the outcome condition in the first medical data, and estimates statistical volumes of a third population for the estimation period by correcting the statistical volumes of the first population that matches the outcome condition in the first medical data for the estimation period on the basis of a relation between the statistical volumes of the third population and the statistical volumes of the first population that matches the outcome condition in first medical data.SELECTED DRAWING: Figure 5

Description

[Technical Field]

[0001] The present invention relates to a medical information estimation device and a medical information estimation program. [Background technology]

[0002] For patients who have received medical examinations, medication, treatment, etc. at medical institutions, medical fee statements, so-called receipt data, are prepared to bill insurers (health insurance associations, local governments, etc.) for the costs of insured treatment (Non-Patent Document 1).In addition, national and local governments prepare and publish data on the incidence of diseases (Non-Patent Document 2). [Prior art documents] [Non-patent literature]

[0003] [Non-Patent Document 1] https: / / ja.wikipedia.org / wiki / Reception [Non-patent document 2] https: / / www.mhlw.go.jp / stf / seisakunitsuite / bunya / kenkou_iryou / kenkou / kekkaku-kansenshou01 / houdou_00014.html Summary of the Invention [Problem to be solved by the invention]

[0004] Meanwhile, there is a need for technology to estimate the number of patients with specific diseases in order to investigate demand for consultations, medications, treatments, etc. Such estimations can be made based on medical claims data held by health insurance associations and local governments. However, there is a problem in that the period of medical claims data provided by each association and local government varies, and accurate estimation is difficult for periods when medical claims data is missing. [Means for solving the problem]

[0005] One aspect of the present invention includes a medical data acquisition means for acquiring first medical data relating to the medical care of a first population, second medical data relating to the medical care of a second population, and third medical data relating to the medical care of a third population, a condition acquisition means for acquiring a designated period and outcome conditions, a statistics acquisition means for acquiring statistics that meet the outcome conditions for the second population and the third population in a first period as statistics for the second population and the third population, respectively, and a statistics acquisition means for acquiring statistics that meet the outcome conditions for the second population and the third population in the first medical data, based on the relationship between the statistics of the second population and the statistics of the first population that meet the outcome conditions in the first medical data. The medical information estimation device is characterized by comprising an estimation means for correcting the statistics of the first population that meet the outcome condition in the first medical data during an estimation period that is a different period and for which the first medical data is available, to estimate the statistics of the second population for the estimation period, and for correcting the statistics of the first population that meet the outcome condition in the first medical data during the estimation period based on the relationship between the statistics of the third population and the statistics of the first population that meet the outcome condition in the first medical data during the estimation period to estimate the statistics of the third population for the estimation period.

[0006] Another aspect of the present invention is a computer including a medical data acquisition means for acquiring first medical data relating to the medical care of a first population, second medical data relating to the medical care of a second population, and third medical data relating to the medical care of a third population, a condition acquisition means for acquiring a designated period and an outcome condition, a statistics acquisition means for acquiring statistics that meet the outcome condition for the second population and the third population in a first period as statistics for the second population and the third population, respectively, and a statistics acquisition means for acquiring statistics that meet the outcome condition for the second population and the third population in the first medical data, based on a relationship between the statistics of the second population and the statistics of the first population that meet the outcome condition in the first period. The medical information estimation program is characterized by functioning as an estimation means that corrects the statistics of the first population that meet the outcome condition in the first medical data during a different estimation period for which the first medical data is available, to estimate the statistics of the second population for the estimation period, and corrects the statistics of the first population that meet the outcome condition in the first medical data during the estimation period based on the relationship between the statistics of the third population and the statistics of the first population that meet the outcome condition in the first medical data during the estimation period to estimate the statistics of the third population for the estimation period.

[0007] Here, it is preferable that the estimation means estimates the rate at which the outcome condition is met for the second population in the estimation period by dividing the statistical quantity of the second population estimated for the estimation period by the population size of the second population in the estimation period, and estimates the rate at which the outcome condition is met for the third population in the estimation period by dividing the statistical quantity of the third population estimated for the estimation period by the population size of the third population in the estimation period.

[0008] It is also preferable that the estimation means calculates a coefficient by dividing the statistical quantity of the second population by the statistical quantity of the first population that meets the outcome condition in the first medical data for the first time period, multiplies the coefficient by the statistical quantity of the first population that meets the outcome condition in the first medical data for the estimation time period to estimate the statistical quantity of the second population for the estimation time period, calculates a coefficient by dividing the statistical quantity of the third population by the statistical quantity of the first population that meets the outcome condition in the first medical data for the first time period, and multiplies the coefficient by the statistical quantity of the first population that meets the outcome condition in the first medical data for the estimation time period to estimate the statistical quantity of the third population for the estimation time period.

[0009] Preferably, the second medical data is health insurance claim data and ledger information of health insurance association subscribers, and the third medical data is local government claim data and ledger information of national health insurance subscribers.

[0010] Furthermore, it is preferable that the medical data acquisition means acquires fourth medical data relating to the medical care of a fourth population, and the estimation means estimates the statistical quantities of the fourth population for the estimation period by correcting the statistical quantities of the first population that meet the outcome conditions in the first medical data during the estimation period based on the relationship between the statistical quantities of the fourth population and the statistical quantities of the first population that meet the outcome conditions in the first medical data.

[0011] In addition, the fourth medical data is preferably receipt data and subscriber ledger information under the medical care system for the elderly. [Effects of the Invention]

[0012] According to the present invention, it is possible to provide a medical information estimation device and a medical information estimation program for estimating medical information for an entire population. Other objects of the embodiments of the present invention will become apparent by reference to the entire specification. [Brief explanation of the drawings]

[0013] [Figure 1] 1 is a diagram showing a configuration of a medical information estimation system according to an embodiment of the present invention. [Figure 2] FIG. 2 is a diagram illustrating a configuration of a server according to an embodiment of the present invention. [Figure 3] FIG. 2 is a diagram illustrating a configuration of a client according to an embodiment of the present invention. [Figure 4] FIG. 10 is a diagram showing an example of a period during which medical data is available for use in the embodiment of the present invention. [Figure 5] 10 is a flowchart showing a medical information estimation process according to an embodiment of the present invention. [Figure 6] This is a diagram showing an example of the national population by age in five-year increments. [Figure 7] This is a diagram showing an example of the national population by age in one-year increments. [Figure 8] FIG. 1 is a diagram showing an example of the number of people enrolled in insurance schemes by age in five-year increments. DETAILED DESCRIPTION OF THE INVENTION

[0014] [System Configuration] As shown in Fig. 1, a medical information estimating system 100 according to an embodiment of the present invention includes a server 102 and a client 104. The client 104 may be a single client or multiple clients. The server 102 and the client 104 are connected to each other via an information and communication network 106 such as the Internet so that they can exchange information with each other.

[0015] The information and communication network 106 is not limited to the Internet, but may be anything that can connect the server 102 and the client 104 to each other so that they can communicate with each other. For example, it may be a dedicated line, a public line (telephone line, mobile communication line, etc.), a wired LAN (Local Area Network), a wireless LAN, etc., or it may be a combination of the Internet and these.

[0016] As shown in FIG. 2, the server 102 includes a processing unit 10, a storage unit 12, an input unit 14, an output unit 16, and a communication unit 18. The processing unit 10 includes a means for performing arithmetic processing, such as a CPU. The processing unit 10 executes a medical information estimation server program stored in the storage unit 12, thereby realizing the function of performing medical information estimation in the medical information estimation system 100 of this embodiment. The storage unit 12 includes storage means, such as a semiconductor memory or a memory card. The storage unit 12 is accessible and connected to the processing unit 10, and stores information necessary for the medical information estimation process, such as the medical information estimation server program and medical prescription data. The input unit 14 includes a means for inputting information. The input unit 14 includes, for example, a keyboard, a touch panel, buttons, etc., for receiving input from an administrator. The output unit 16 includes a means for outputting the processing results of the server 102, such as a user interface screen (UI) for receiving input information from the administrator. The output unit 16 includes, for example, a display for presenting images to the administrator. The communication unit 18 is configured to include an interface for communicating information with the client 104 via the information communication network 106. Communication by the communication unit 18 may be wired or wireless. The communication unit 18 may also receive information necessary for estimating medical information, such as medical receipt data, from computers located in medical institutions, national institutions, local governments, health insurance associations, information providers, etc.

[0017] The server 102 accepts access via the information and communication network 106 from the client 104 of a user who wishes to receive information on medical information estimation, estimates the medical information requested by each user, and transmits the results to the client 104 of that user.

[0018] As shown in FIG. 3 , the client 104 includes a processing unit 20, a storage unit 22, an input unit 24, an output unit 26, and a communication unit 28. The client 104 is also referred to as a communication terminal. The processing unit 20 includes a means for performing arithmetic processing, such as a CPU. The processing unit 20 executes a medical information estimation client program stored in the storage unit 22, thereby realizing the function of the client terminal in the medical information estimation system 100 of this embodiment. The storage unit 22 includes storage means, such as a semiconductor memory or a memory card. The storage unit 22 is accessible and connected to the processing unit 20 and stores the medical information estimation client program and information required for its processing. The input unit 24 includes a means for inputting information. The input unit 24 includes, for example, a keyboard, a touch panel, buttons, etc. for receiving input from a user. The output unit 26 includes a means for outputting information required for processing in the client 104, such as a screen for receiving input information from a user and a display for displaying an image when presenting the medical information estimation result. The communication unit 28 includes an interface for communicating information with the server 102 via the information and communication network 106. The communication by the communication unit 28 may be wired or wireless.

[0019] Various information processing devices capable of executing a client program for providing medical information estimation can be applied as the client 104. For example, the client 104 can be a stationary or portable medical information providing terminal installed in a medical institution or the like, a personal computer (PC), a tablet computer, a smartphone, a mobile phone terminal, a PHS (Personal Handy-phone System) terminal, a personal digital assistant (PDA), a multi-function television receiver with information processing capabilities (so-called smart TV), or the like.

[0020] [Medical information estimation processing] The medical information estimation process is performed by the medical information estimation system 100. The statistical quantities of medical information estimated by the medical information estimation system 100 can be the number of patients, the number of medical examinations, treatments, and medications, and the amount used, and financial information (amounts) related to medical care. However, the present invention is not limited to these, and any information related to medical care can be used.

[0021] The medical information estimation process is performed using first medical data related to the medical care of a first population, which is a part of the entire population. The entire population can be, for example, a country. However, the entire population is not limited to this and can also be, for example, a local administrative division (such as a prefecture, city, town, or village).

[0022] The first group may be a set of patients diagnosed with influenza in press releases on influenza published by the Ministry of Health, Labor and Welfare. In this case, the first medical data may be the number of patients diagnosed with influenza, the number of patients admitted to ICUs, the number of patients using ventilators, etc., in the press releases. Furthermore, for example, the first group may be a set of patients diagnosed with heatstroke in heatstroke information published by the Fire and Disaster Management Agency of the Ministry of Internal Affairs and Communications. In this case, the first medical data may be the number of patients diagnosed with heatstroke, the number of patients by age, the number of patients by injury level, etc., in the press releases.

[0023] In this embodiment, second medical data relating to medical care of a second population, third medical data relating to medical care of a third population, and fourth medical data relating to medical care of a fourth population are used.

[0024] The second group can be, for example, a group whose elements are members of a health insurance association. In this case, the second medical data includes health insurance receipt data submitted by medical institutions to the health insurance association and ledger information for the health insurance association's members. The second medical data may also include health checkup data that collects the health checkup results of the health insurance association's members. The health insurance receipt data can be health insurance receipt data related to a portion of the members who are members of the health insurance association.

[0025] The third group may be, for example, a group whose elements are members of the National Health Insurance. In this case, the third medical data includes municipal receipt data submitted by medical institutions to local governments and ledger information for National Health Insurance members. The municipal receipt data may be municipal receipt data related to a portion of the members enrolled in the National Health Insurance. The third medical data may also include health checkup data that compiles the health checkup results of National Health Insurance members.

[0026] The fourth group may be, for example, a group whose elements are members of the Medical Care System for the Elderly. In this case, the fourth medical data includes medical receipt data for the Medical Care System for the Elderly submitted by medical institutions to local governments and ledger information for those members. The medical receipt data may be medical receipt data for a portion of members enrolled in the Medical Care System for the Elderly. The fourth medical data may also include health checkup data that compiles the health checkup results of members of the Medical Care System for the Elderly.

[0027] However, the populations and their medical data used are not limited to these, and other populations, such as other insurance systems, may also be included.

[0028] The second, third, and fourth medical data include information necessary to estimate medical information such as prescribed medications, examination results (disease name, etc.), and medical procedures (types and results of tests performed, details of treatments (procedures) and surgeries, etc.) The ledger information also includes the subscriber's gender, age, and subscription period.

[0029] The server 102 acquires the medical receipt data relating to the second, third, and fourth groups, and stores them in the storage unit 12 as second medical data, third medical data, and fourth medical data, respectively.

[0030] Furthermore, the second group, health insurance societies, the third group, national health insurance, and the fourth group, the medical system for the elderly, are collections of members of these organizations. In other words, these groups are collections of populations that include not only members who have visited medical institutions as patients, but also healthy members. Therefore, by using the second, third, and fourth medical data, it is possible to estimate medical information per member (element) of a population that includes healthy people.

[0031] There may be differences in the period of availability between the medical receipt data included in the secondary, tertiary, and quaternary medical data, and the primary medical data, which is the public data published by the Ministry of Health, Labor and Welfare. For example, as shown in Figure 4, there is a delay before these medical receipt data become available; only data older than approximately seven months is available for health insurance medical receipt data, and only data older than approximately nine months is available for local government medical receipt data and medical receipt data for the late-stage elderly medical system. On the other hand, influenza data from the Ministry of Health, Labor and Welfare can be used from approximately one week ago.

[0032] The medical information estimation system 100 performs a process of estimating medical information using the first medical data. Hereinafter, the process of estimating medical information by the medical information estimation system 100 will be described with reference to the flowchart shown in FIG. 5. In this embodiment, a mode of estimating medical information for each combination of gender and age will be described. However, this is not limited to this, and the gender and age for estimating medical information may be set in the outcome conditions described below.

[0033] In step S10, an initial setting process is performed. Through the process in this step, the medical information estimating system 100 functions as an initial setting means (including a medical data acquisition means).

[0034] The server 102 acquires the data from the Ministry of Health, Labour and Welfare and stores it in the storage unit 12 as first medical data.

[0035] Furthermore, a login process is performed from the client 104 used by the user requesting estimation of medical information. The user uses the input unit 24 of the client 104 to input information required to log in to the medical information provision service, such as a user ID and password. The client 104 transmits the information required to log in to the server 102 via the communication unit 28 and the information communication network 106. When the server 102 receives the information required to log in via the communication unit 18, it permits the client 104 to log in if the information satisfies the conditions for permitting login.

[0036] In step S12, a process is performed to acquire a designated period for estimating medical information. Through the process in this step, the medical information estimation system 100 functions as part of a condition acquisition means. In step S10, the output unit 26 of the logged-in client 104 displays a screen prompting the user to input the period for estimating medical information. The user inputs the period for estimating medical information using the input unit 24 of the client 104. The client 104 transmits the period for estimating medical information input to the server 102 via the information communication network 106 via the communication unit 28. When the server 102 receives the period for estimating medical information via the communication unit 18, it stores the period in the memory unit 12 as a designated period.

[0037] In this embodiment, the designated period is a period during which the first medical data is available and the second to fourth medical data are unavailable.

[0038] In step S14, a process for acquiring outcome conditions is performed. Through the process in this step, the medical information estimation system 100 functions as part of a condition acquisition means. The outcome conditions are conditions for performing extraction processing from medical data. The outcome conditions can be information that can be extracted from the first medical data, such as the name of the disease, the prescribed medication, the type of medical treatment, gender, and age. The outcome condition may be a single condition or a combination of multiple conditions.

[0039] For example, if one wishes to estimate the number of patients diagnosed with "diabetes" as medical information, the disease name "diabetes" is set as the outcome condition. Furthermore, if one wishes to estimate the number of patients prescribed a specific medication as medical information, the name of the medication is set as the outcome condition. Similarly, other outcome conditions such as the type of medical procedure, gender, and age may also be set. Furthermore, multiple conditions may be combined to set an outcome condition, such as combining the disease name with the prescribed medication.

[0040] In step S10, a screen prompting the user to enter outcome conditions is displayed on the output unit 26 of the client 104 that has logged in. The user enters the outcome conditions using the input unit 24 of the client 104. The client 104 transmits the entered outcome conditions to the server 102 via the communication unit 28 and the information communication network 106. When the server 102 receives the outcome conditions via the communication unit 18, it stores them in the memory unit 12 as outcome conditions.

[0041] Furthermore, if you want to estimate medical information related to a new drug or a new medical treatment or treatment, you can simply set the existing drug that replaces the new drug or the existing medical treatment or treatment that replaces the new drug as the outcome condition. This makes it possible to estimate the number of patients to whom the new drug or new medical treatment or treatment can be applied, the number of medical treatments, treatments, and medications, the amount used, and financial information (amount).

[0042] In step S16, a process of acquiring statistics is performed. Through the process in this step, the medical information estimation system 100 functions as a statistics acquisition means. Here, the statistics of medical information in a first period t1 are acquired. The first period t1 is set to a period during which the first to fourth medical data relating to the first to fourth populations are all available.

[0043] The server 102 acquires statistics relating to the first population, the second population, the third population, and the fourth population in the first period t1, and stores them in the memory unit 12 as statistics of the first population, the second population, the third population, and the fourth population, respectively.

[0044] In the medical data held for the population set, the number of people of sex and age belonging to the first period t1 is L set (sex,age,t1) This is called the "number of data subscribers in the set." set (sex,age,t1)The total number of people who have data that meets outcome condition O (which may be the number of medications or the amount of money, depending on the outcome condition) is N. set (O,sex,age,t1) We call this the "number of data outcomes in the population set."

[0045] For example, in the medical data held for the first group set1, the number of people of sex sex and age age belonging to the first period t1 is L set1 (sex,age,t1) This is called the "number of data subscribers of the first group set1." set1 (sex,age,t1) The total number of people who have data that meets outcome condition O (which may be the number of medications or the amount of money, depending on the outcome condition) is N. set1 (O,sex,age,t1) This will be called the "number of data outcomes for the first population, set1."

[0046] Similarly, in the medical data held for the second group set2, the number of people of sex sex and age age belonging to the first period t1 is L set2 (sex,age,t1) This is called the "number of data subscribers of the second group set2." set2 (sex,age,t1) The total number of people who have data that meets outcome condition O (which may be the number of medications or the amount of money, depending on the outcome condition) is N. set2 (O,sex,age,t1) This will be called the "number of outcomes in the data for the second population, set2." The number of outcomes per person is calculated by dividing the number of outcomes in the data for the second population, set2, by the number of data subscribers in set2, and the number of outcomes for all health insurance societies is estimated by multiplying this by the number of people in the population for all health insurance societies. This will be called the number of outcomes for the second population, SET2.

[0047] In the medical data held for the third group set3, the number of people of sex sex and age age belonging to the first period t1 is L set3 (sex,age,t1)This will be called the "number of data subscribers of the third group, set3." set3 (sex,age,t1) The total number of people who have data that meets outcome condition O (which may be the number of medications or the amount of money, depending on the outcome condition) is N. set3 (O,sex,age,t1) This will be called the "number of outcomes in the data for the third population, set3." The number of outcomes in the data for the third population, set3, is divided by the number of data subscribers for set3 to calculate the number of outcomes per person, and then multiplied by the number of people in the national health insurance population to estimate the number of outcomes for the national health insurance system. This will be called the number of outcomes for the third population, SET3.

[0048] In the medical data held for the fourth group set4, the number of people of sex sex and age age belonging to the first period t1 is L set4 (sex,age,t1) This will be called the "number of data subscribers for the fourth group, set4." set4 (sex,age,t1) The total number of people who have data that meets outcome condition O (which may be the number of medications or the amount of money, depending on the outcome condition) is N. set4 (O,sex,age,t1) This will be called the "number of outcomes in the data for the fourth cohort, set4." The number of outcomes in the data for the fourth cohort, set4, is divided by the number of data subscribers for set4 to calculate the number of outcomes per person, and then multiplied by the number of people in the population of all elderly people to estimate the number of outcomes for all elderly people. This will be called the number of outcomes for the fourth cohort, SET4.

[0049] In addition, a process of calculating a coefficient k for estimating medical information for a specified period is performed. The coefficient k is calculated by multiplying the number of outcomes N in the second to fourth groups by the following formula (1): SETn (O,sex,age,t1) (where n = an integer between 2 and 4) and the number of data outcomes in the first group, N set1 (O,sex,age,t1) It is expressed as a ratio of

number

[0050] For example, the coefficient k for the second group SET2 that meets the outcome condition O for sex and age in the first period t1 SET2 (sex,age,t1) is the number of outcomes in the second population SET2, N SET2 (O,sex,age,t1) The number of data outcomes in the first group is N set1 (O,sex,age,t1) Similarly, the coefficient k for the third group SET3 that meets the outcome condition O for sex and age in the first period t1 is SET3 (sex,age,t1) is the number of outcomes in the third population SET3, N SET3 (O,sex,age,t1) The number of data outcomes in the first group is N set1 (O,sex,age,t1) In addition, the coefficient k for the fourth group SET4 that meets the outcome condition O for sex and age in the first period t1 is SET4 (sex,age,t1) is the number of outcomes in the fourth population SET4, N SET4 (O,sex,age,t1) The number of data outcomes in the first group is N set1 (O,sex,age,t1) It is calculated by dividing by

[0051] In step S18, an estimation period is set. Through the processing in this step, the medical information estimation system 100 functions as an estimation period setting means. The server 102 divides the specified period specified in step S12 into estimation periods t2, which are predetermined time units. The time unit can be one month, three months, six months, one year, etc.

[0052] For example, if the specified period is from 6 months ago (the beginning of the month 6 months ago) to 3 months ago (the end of the month 3 months ago) and the time unit is set to 1 month, the estimated period t2 will be set in order of 1 month, such as 7 months ago (the beginning to the end of the month 7 months ago), 6 months ago (the beginning to the end of the month 6 months ago), ... 3 months ago (the beginning to the end of the month 3 months ago).

[0053] In this embodiment, an example will be described in which the specified period is set to one month. However, this is not limiting, and even if another time unit is set, the estimation process can be performed in the same manner using the set time unit.

[0054] In step S20, a process of acquiring statistics for the estimation period is performed. Through the process in this step, the medical information estimation system 100 functions as a statistics acquisition means. Here, statistics of medical information for the estimation period t2 are acquired.

[0055] The server 102 acquires statistics related to the first population for the estimation period t2 and stores them as statistics for the first population in the storage unit 12. In this embodiment, the specified period is set to a period during which the first medical data is available and the second to fourth medical data are unavailable, and the second to fourth medical data are also unavailable during the estimation period t2.

[0056] In the medical data held for the first group set1, the number of people of sex sex and age age belonging to the estimation period t2 is expressed as the number of data subscribers L of the first group set1. set1 (sex,age,t2) Also, the above L set1 (sex,age,t2) The total number of people who have data that matches outcome condition O (which may be the number of medications or amounts depending on the outcome condition) is the number of data outcomes N of the first group set1. set1 (O,sex,age,t2) Obtain as.

[0057] In step S22, a process of estimating medical information is performed. Through the process in this step, the medical information estimation system 100 functions as a medical information estimation means.

[0058] For the estimated period t2, during which the second to fourth medical data are unavailable, the number of outcomes N SETn (O,sex,age,t2) (where n is an integer between 2 and 4) is estimated.

number

[0059] For example, if the first medical data is available and the second medical data is unavailable in the estimation period t2, then, according to formula (2), the number of data outcomes N that meet the outcome condition O for the combination of sex and age in the estimation period t2 for the set of first medical data set1 is set1 (O,sex,age,t2) with a constant k SET2 (O,sex,age) Multiplying by , we obtain the number of outcomes N that meet the outcome condition O for the combination of sex and age in the estimation period t2 for the second medical data set SET2. SET2 (O,sex,age,t2) Calculate.

[0060] Similarly, for the first medical data set set1, the number of data outcomes N that meet the outcome condition O for the combination of gender sex and age age in the estimation period t2 is set1 (O,sex,age,t2) with a constant k SET3 (O,sex,age) Multiplying by , we obtain the number of outcomes N that meet the outcome condition O for the combination of sex and age in the estimation period t2 for the third medical data set SET3. SET3 (O,sex,age,t2) In addition, for the first medical data set set1, the number of outcomes N that meet the outcome condition O for the combination of sex and age in the estimation period t2 is calculated. set1 (O,sex,age,t2) with a constant k SET4 (O,sex,age) Multiplying by , we obtain the number of outcomes N that meet the outcome condition O for the combination of sex and age in the estimation period t2 for the fourth medical data set SET4. SET4 (O,sex,age,t2) Calculate.

[0061] The estimated number of outcomes for the second to fourth populations is N SETn(O,sex,age,t2) (where n is an integer between 2 and 4) to estimate statistics, which are medical information about the entire population.

[0062] Furthermore, for the estimated period t2, during which the second to fourth medical data are unavailable, the number of outcomes per person in the population, P SETn (O,sex,age,t2) (where n is an integer between 2 and 4) is estimated. Here, the number of people of sex and age belonging to the second to fourth groups in the estimation period t2 is L SETn (sex,age,t2) (where n is an integer from 2 to 4).

number

[0063] For example, according to formula (3), the number of outcomes per person in the second population that meets the outcome condition O for the combination of sex and age in the estimation period t2 is P SET2 (O,sex,age,t2) is the number of outcomes in the second population that meet the outcome condition O for the combination of sex and age in the estimation period t2, N SET2 (O,sex,age,t2) The estimated value of L is used to estimate the number of subscribers of the second group in the estimation period t2. SET2 (sex,age,t2) It is calculated by dividing by

[0064] Similarly, the number of outcomes per person in the third group that meets the outcome condition O for the combination of sex and age in the estimation period t2 is P SET3 (O,sex,age,t2) is the number of outcomes in the third group that meet the outcome condition O for the combination of sex and age in the estimation period t2, N SET3 (O,sex,age,t2) The estimated value of L is the number of subscribers of the third group in the estimation period t2. SET3 (sex,age,t2)In addition, the number of outcomes per person in the fourth group that meets the outcome condition O for the combination of sex and age in the estimation period t2 is P SET4 (O,sex,age,t2) is the number of outcomes in the fourth group that meet the outcome condition O for the combination of sex and age in the estimation period t2, N SET4 (O,sex,age,t2) The estimated value of L is the number of subscribers of the fourth group in the estimation period t2. SET4 (sex,age,t2) It is calculated by dividing by

[0065] Here, if the second, third, and fourth groups are groups of subscribers to a health insurance association, national health insurance, and the medical insurance system for the elderly, respectively, the number of subscribers by sex and age in the estimation period t2, L SETn (sex,age,t2) (where n is an integer between 2 and 4) has not been made public.

[0066] Therefore, by combining the "Population Trends" published by the Ministry of Internal Affairs and Communications and the "Basic Data on Medical Insurance" published by the Ministry of Health, Labor and Welfare, we can estimate the number of subscribers L by sex and age for the group of subscribers of health insurance associations, national health insurance, and the medical insurance system for the elderly in the estimated period t2. SETn (sex,age,t2) is estimated.

[0067] The Ministry of Internal Affairs and Communications' "Population Estimates" are available in two types: approximate and final figures. As shown in Figure 6, the approximate figures (updated monthly) show the national population by age in five-year increments, while the final figures (updated annually) show the national population by age in one-year increments, as shown in Figure 7. Furthermore, as shown in Figure 8, the Ministry of Health, Labor and Welfare's "Basic Data on Medical Insurance" shows the number of people enrolled in insurance systems by age in five-year increments.

[0068] Therefore, using equation (4), we calculate the number of subscribers L by sex and age for the group of subscribers of health insurance societies, national health insurance, and the medical insurance system for the elderly in the estimation period t2. SETn (sex,age,t2)Here, the estimated national population by age in five-year increments in the "Population Estimates" of the Ministry of Internal Affairs and Communications for period t is L SET (sex,age,t) , the ratio of the confirmed national population by age in 1-year increments to the confirmed national population by age in 5-year increments M SET (sex,age,t) , the proportion of people enrolled in the health insurance system by age in five-year increments in the Ministry of Health, Labor and Welfare's "Basic Information on Health Insurance" SETn (age,t) is.

number

[0069] For example, for the second group (health insurance association) aged 70 years in the estimation period t2, the number of subscribers by gender (male) is L SET2 (male,70,t2) is the approximate national population by age in 5-year increments, L SET (male,70~74,t2) , the ratio of the confirmed national population by age in 1-year increments to the confirmed national population by age in 5-year increments M SET (male,70,t2) , Q: Percentage of people enrolled in health insurance associations by age in 5-year increments SET2 (70~74,t2) Similarly, the number of men enrolled in the third group (National Health Insurance) aged 70 in the estimation period t2 is L SET3 (male,70,t2) is the approximate national population by age in 5-year increments, L SET (male,70~74,t2) , the ratio of the confirmed national population by age in 1-year increments to the confirmed national population by age in 5-year increments M SET (male,70,t2) , National Health Insurance enrollment rate by age in 5-year increments Q SET3 (70~74,t2) In addition, the number of enrollees by sex (male) for the fourth group (medical care system for the elderly) aged 70 in the estimation period t2 can be estimated by multiplying L SET4 (male,70,t2) is the approximate national population by age in 5-year increments, L SET (male,70~74,t2) , the ratio of the confirmed national population by age in 1-year increments to the confirmed national population by age in 5-year increments M SET (male,70,t2), the proportion of people enrolled in the medical care system for the elderly by age in 5-year increments Q SET4 (70~74,t2) The same can be done for other genders and ages.

[0070] In step S24, it is determined whether the medical information estimation process has been completed for the entire specified period. If the entire specified period specified in step S12 has been set as the estimated period in step S18, the server 102 proceeds to step S24, and if the entire period has not been set as the estimated period, the server 102 returns to step S18 to set the next estimated period and repeats the medical information estimation process in steps S20 and S22.

[0071] In step S26, the result of the medical information estimation process is output. Through the process in this step, the medical information estimation system 100 functions as an estimation result output means. The server 102 transmits the medical information estimation result obtained by the medical information estimation process via the communication unit 18 and the information communication network 106 to the client 104 used by the user who requested the medical information estimation. The client 104 receives the medical information estimation result via the communication unit 28 and presents the medical information estimation result to the user using the output unit 26.

[0072] In the above embodiment, the process of estimating the number of patients as medical information was explained as an example, but if the number of medical examinations, treatments, or medications that meet the outcome conditions and financial information (amounts) related to medical care are extracted as the number of outcomes, it is possible to similarly estimate the number of medical examinations, treatments, or medications and financial information (amounts) related to medical care.

[0073] [Configuration of the invention] [Configuration 1] a medical data acquisition means for acquiring first medical data relating to the medical care of a first group, second medical data relating to the medical care of a second group, and third medical data relating to the medical care of a third group; A condition acquisition means for acquiring a specified period and outcome conditions; a statistics acquisition means for acquiring statistics that meet the outcome condition for the second population and the third population during a first period as statistics for the second population and the third population, respectively; based on the relationship between the statistics of the second population and the statistics of the first population that meet the outcome condition in the first medical data, during an estimation period that is different from the first period and for which the first medical data is available, correcting the statistics of the first population that meet the outcome condition in the first medical data, and estimating the statistics of the second population for the estimation period; an estimation means for estimating the statistics of the third population for the estimation period by correcting the statistics of the first population that meets the outcome condition in the first medical data during the estimation period based on the relationship between the statistics of the third population and the statistics of the first population that meets the outcome condition in the first medical data; A medical information estimation device comprising: [Configuration 2] 1. A medical information estimation device according to claim 1, The estimation means estimating the rate of conformance to the outcome condition for the second population during the estimation period by dividing the statistic for the second population estimated for the estimation period by the population size of the second population during the estimation period; estimating the rate of conformance to the outcome condition for the third population during the estimation period by dividing the statistic of the third population estimated for the estimation period by the population size of the third population during the estimation period; A medical information estimation device characterized by: [Configuration 3] 3. The medical information estimation device according to claim 1, The estimation means Calculating a coefficient by dividing the statistic of the second population by the statistic of the first population that meets the outcome condition in the first medical data during the first period; multiplying the coefficient by the statistic of the first population that meets the outcome condition in the first medical data for the estimation period to estimate the statistic of the second population for the estimation period; Calculating a coefficient by dividing the statistical quantity of the third population by the statistical quantity of the first population that meets the outcome condition in the first medical data during the first period; A medical information estimation device characterized by multiplying the coefficient by the statistics of the first population that meet the outcome condition in the first medical data for the estimation period to estimate the statistics of the third population for the estimation period. [Configuration 4] The medical information estimation device according to any one of configurations 1 to 3, The second medical data is health insurance receipt data and ledger information of health insurance association members, A medical information estimation device characterized in that the third medical data is local government prescription data and national health insurance subscriber ledger information. [Configuration 5] The medical information estimation device according to any one of configurations 1 to 4, the medical data acquisition means acquires fourth medical data relating to medical care of a fourth group; A medical information estimation device characterized in that the estimation means estimates the statistics of the fourth population for the estimation period by correcting the statistics of the first population that meets the outcome condition in the first medical data during the estimation period based on the relationship between the statistics of the fourth population and the statistics of the first population that meets the outcome condition in the first medical data. [Configuration 6] 6. A medical information estimation device according to configuration 5, A medical information estimation device characterized in that the fourth medical data is prescription data and subscriber ledger information under the Long-Term Care Insurance System for the Elderly. [Configuration 7] Computer, a medical data acquisition means for acquiring first medical data relating to the medical care of a first group, second medical data relating to the medical care of a second group, and third medical data relating to the medical care of a third group; A condition acquisition means for acquiring a specified period and outcome conditions; a statistics acquisition means for acquiring statistics that meet the outcome condition for the second population and the third population during a first period as statistics for the second population and the third population, respectively; based on the relationship between the statistics of the second population and the statistics of the first population that meet the outcome condition in the first medical data, during an estimation period that is different from the first period and for which the first medical data is available, correcting the statistics of the first population that meet the outcome condition in the first medical data, and estimating the statistics of the second population for the estimation period; an estimation means for estimating the statistics of the third population for the estimation period by correcting the statistics of the first population that meets the outcome condition in the first medical data during the estimation period based on the relationship between the statistics of the third population and the statistics of the first population that meets the outcome condition in the first medical data; A medical information estimation program characterized by functioning as follows. [Explanation of symbols]

[0074] 10 processing unit, 12 memory unit, 14 input unit, 16 output unit, 18 communication unit, 20 processing unit, 22 memory unit, 24 input unit, 26 output unit, 28 communication unit, 100 medical information estimation system, 102 server, 104 client, 106 information communication network.

Claims

1. a medical data acquisition means for acquiring first medical data relating to medical care of a first group, second medical data relating to medical care of a second group, and third medical data relating to medical care of a third group; A condition acquisition means for acquiring a specified period and outcome conditions; a statistics acquisition means for acquiring statistics that meet the outcome condition for the second population and the third population during a first period as statistics for the second population and the third population, respectively; based on the relationship between the statistics of the second population and the statistics of the first population that meet the outcome condition in the first medical data, during an estimation period that is different from the first period and for which the first medical data is available, correcting the statistics of the first population that meet the outcome condition in the first medical data, and estimating the statistics of the second population for the estimation period; an estimation means for estimating the statistics of the third population for the estimation period by correcting the statistics of the first population that meet the outcome condition in the first medical data during the estimation period based on the relationship between the statistics of the third population and the statistics of the first population that meet the outcome condition in the first medical data; A medical information estimation device comprising:

2. The medical information estimation device according to claim 1, The estimation means estimating the rate of conformance to the outcome condition for the second population during the estimation period by dividing the statistic for the second population estimated for the estimation period by the population size of the second population during the estimation period; estimating the rate of conformance to the outcome condition for the third population during the estimation period by dividing the statistic of the third population estimated for the estimation period by the population size of the third population during the estimation period; A medical information estimation device characterized by:

3. The medical information estimation device according to claim 1, The estimation means Calculating a coefficient by dividing the statistic of the second population by the statistic of the first population that meets the outcome condition in the first medical data during the first period; multiplying the coefficient by the statistic of the first population that meets the outcome condition in the first medical data for the estimation period to estimate the statistic of the second population for the estimation period; Calculating a coefficient by dividing the statistical quantity of the third population by the statistical quantity of the first population that meets the outcome condition in the first medical data during the first period; A medical information estimation device characterized by multiplying the coefficient by the statistics of the first population that meet the outcome condition in the first medical data for the estimation period to estimate the statistics of the third population for the estimation period.

4. The medical information estimation device according to claim 1, The second medical data is health insurance receipt data and ledger information of health insurance association members, A medical information estimation device characterized in that the third medical data is local government prescription data and national health insurance subscriber ledger information.

5. The medical information estimation device according to any one of claims 1 to 4, the medical data acquisition means acquires fourth medical data relating to medical care of a fourth group; A medical information estimation device characterized in that the estimation means corrects the statistical quantities of the first population that meet the outcome conditions in the first medical data during the estimation period based on the relationship between the statistical quantities of the fourth population and the statistical quantities of the first population that meet the outcome conditions in the first medical data, and estimates the statistical quantities of the fourth population for the estimation period.

6. 6. The medical information estimation device according to claim 5, A medical information estimation device characterized in that the fourth medical data is prescription data and subscriber ledger information under the Long-Term Care Insurance System for the Elderly.

7. Computer, a medical data acquisition means for acquiring first medical data relating to medical care of a first group, second medical data relating to medical care of a second group, and third medical data relating to medical care of a third group; A condition acquisition means for acquiring a specified period and outcome conditions; a statistics acquisition means for acquiring statistics that meet the outcome condition for the second population and the third population during a first period as statistics for the second population and the third population, respectively; based on the relationship between the statistics of the second population and the statistics of the first population that meet the outcome condition in the first medical data, during an estimation period that is different from the first period and for which the first medical data is available, correcting the statistics of the first population that meet the outcome condition in the first medical data, and estimating the statistics of the second population for the estimation period; an estimation means for estimating the statistics of the third population for the estimation period by correcting the statistics of the first population that meet the outcome condition in the first medical data during the estimation period based on the relationship between the statistics of the third population and the statistics of the first population that meet the outcome condition in the first medical data; A medical information estimation program characterized by functioning as follows.

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