JP2012212252A - Detection method and detection server - Google Patents

Abstract

PROBLEM TO BE SOLVED: To prevent failure to detect an infectious disease.SOLUTION: In a detection method, multiple retrieval devices in medical institutions which store electronic medical charts are caused to search for information input in electronic medical charts as retrieval object with a first keyword. When the number of retrieval objects retrieved with the first keyword reaches a specified number or a specified proportion in a specified number of retrieval devices, the following processing is executed. Specifically, in the method, each of the multiple retrieval devices is caused to search for information input in the electronic medical charts as retrieval object with a second keyword which is different from the first keyword, and an alert is output based on the retrieval results obtained with the first and second keywords.

Description

  The present invention relates to a detection method and a detection server.

  Conventionally, there are techniques for predicting the epidemic of infectious diseases. For example, there is a technique for detecting an infectious virus existing in each region using a terminal that detects a virus, and notifying the risk of an infectious disease epidemic based on the detection result.

  Also, in general, it is possible to grasp the epidemic status of infectious diseases by counting the number of patients with infectious diseases reported within a certain period at fixed-point medical institutions in each region selected in advance. . Then, when the number of patients with infectious diseases reaches a predetermined number, it is considered that the infectious diseases have become epidemic.

Japanese Patent Laying-Open No. 2005-275708

  By the way, the inventor may be able to grasp the epidemic status of infectious diseases by accumulating medical chart information input by doctors at a plurality of medical institutions and searching for infectious disease keywords from the accumulated medical chart information. Thought. However, even if a patient with the same infectious disease is examined, the descriptions in the medical chart vary depending on the doctor. Therefore, even if a keyword for an infectious disease is searched from the medical record information, it is expected that an infectious disease detection failure will occur. .

  The disclosed technology has been made in view of the above, and an object thereof is to provide a detection method and a detection server that can prevent omission of detection of an infectious disease.

  In the detection method disclosed in the present application, each search device of a plurality of medical institutions that stores an electronic medical record performs a search using a first keyword with information input to the electronic medical record as a search target. Further, the detection method performs the following process when the number of search objects searched by the first keyword reaches a second predetermined number or a predetermined ratio in the first predetermined number of search devices. That is, in the detection method, at least one of the plurality of medical institution search devices executes a search using a second keyword different from the first keyword, using information input to the electronic medical record as a search target. . The detection method outputs a warning based on the search result by the first keyword and the search result by the second keyword.

  According to one aspect of the technology disclosed in the present application, there is an effect that omission of detection of an infectious disease can be prevented.

FIG. 1 is a block diagram illustrating a functional configuration of the detection server according to the embodiment. FIG. 2 is a diagram illustrating an example of the data structure of the free description table. FIG. 3 is a diagram illustrating an example of a data structure of the inspection result table. FIG. 4 is a diagram illustrating an example of the data structure of the prescription table. FIG. 5 is a diagram illustrating an example of a data structure of the patient table. FIG. 6 is a diagram illustrating an example of the data structure of the position table. FIG. 7 is a flowchart illustrating the processing procedure of the detection server according to the embodiment. FIG. 8 is a diagram illustrating an example of a computer that executes a detection program.

  Hereinafter, embodiments of a detection method and a detection server disclosed in the present application will be described in detail with reference to the drawings. Note that the present invention is not limited to the embodiments. Each embodiment can be appropriately combined within a range in which processing contents do not contradict each other.

  A functional configuration of the detection server according to the embodiment will be described. FIG. 1 is a block diagram illustrating a functional configuration of the detection server according to the embodiment. As shown in FIG. 1, the detection server 100 is connected to a medical institution 10a, a medical institution 10b, and a medical institution 10c. In addition, although the case where the detection server 100 is connected to the medical institutions 10a to 10c will be described here, the present invention is not limited to this. For example, in a case where information of each medical institution is centrally managed in a regional medical management center in which a plurality of medical institutions in each region are bundled, the detection server 100 may be connected to the medical management center.

  The medical institution 10a includes an electronic medical record device 20a and a search device 30a. The medical institution 10a corresponds to a facility where a medical service is provided, for example, a hospital or a clinic. Below, for convenience of explanation, a functional configuration of the medical institution 10a will be described. The functional configuration of the medical institutions 10b and 10c is the same as the functional configuration of the medical institution 10a, and thus the description thereof is omitted.

  The electronic medical record device 20a stores an electronic medical record. For example, the electronic medical record device 20a stores a free description table 21a, a test result table 22a, and a prescription table 23a as electronic medical records. This electronic medical record is information recorded for each medical institution by medical personnel such as doctors and nurses. The electronic medical record device 20a is connected to an input device and an output device (not shown). The input device is a device that receives input of various types of information, and corresponds to, for example, a keyboard and a mouse. The output device is an output device that outputs various types of information, and corresponds to, for example, a display or a monitor. The electronic medical record is not limited to the free description table 21a, the inspection result table 22a, and the prescription table 23a. For example, the electronic medical record may include a vital table that stores vital data such as blood pressure and body temperature, an accounting table that stores accounting records, and the like.

  The free description table 21a stores the contents of documents freely described by medical personnel such as doctors and nurses when a patient visits a medical institution. FIG. 2 is a diagram illustrating an example of the data structure of the free description table. As shown in FIG. 2, the free description table 21 a stores, for example, “local patient ID”, “medical treatment date”, “document type”, and “document content” in association with each other. Among these, local patient ID (Identification) shows the identification information of the patient who consulted the medical institution 10a. The medical treatment date indicates the date when the patient visited the medical institution 10a. The document type indicates the type of the document such as the description of the examination order or doctor. The document content indicates the content of a document that is freely described by medical personnel such as doctors and nurses. The document content of the free description table 21a describes different keywords depending on the doctor even when a patient with the same symptom is examined. For example, when a patient whose body temperature is 38.5 degrees is examined, the doctor describes “38 degrees or more” or “high fever”. In this way, the contents of the free description table 21a vary depending on the person who fills it.

  As shown in FIG. 2, for example, the free description table 21 a includes a local patient ID “00000001101”, a medical treatment date “2010/1/17”, a document type “examination order”, and a document content “ABC | 0000000019”. Are stored in association with each other. That is, the free description table 21a indicates that a document “ABC | 0000000019 |” was described as an examination order when a patient with an ID “0000000101” visited on January 17, 2010. The free description table 21a stores other document contents in the same manner.

  The test result table 22a stores the results of tests performed when the patient visits a medical institution. FIG. 3 is a diagram illustrating an example of a data structure of the inspection result table. As shown in FIG. 3, the examination result table 22a corresponds to, for example, “local patient ID”, “medical treatment date”, “field”, “examination”, “examination result”, and “unit”. Then remember. Of these, the field indicates a field related to the inspection performed. The inspection indicates the name of the inspection that was performed. The test result indicates the result of the test performed. The unit indicates a unit corresponding to the numerical value of the inspection result. In addition, since the fixed information is described in the test result table 22a unlike the free description table 21a, even when a patient with the same symptom is examined, the description contents are unlikely to vary. On the other hand, since the amount of data contained in the inspection result table 22a is large, when a search is executed by accessing this table, the load on the search is higher than that of the free description table 21a.

  As illustrated in FIG. 3, for example, the test result table 22 a includes a local patient ID “00000001101”, a medical treatment date “2010/1/17”, a field “blood”, a test “TP”, and a test result “7”. .51 ”and the unit“ g / dl ”are stored in association with each other. That is, in the test result table 22a, when the patient with ID “0000000101” visited on January 17, 2010, a TP test in a field related to blood was performed, and the result was 7.51 g / dl. It shows that. The inspection result table 22a also stores other inspection results in the same manner.

  The prescription table 23a stores information on medicines prescribed when a patient visits a medical institution. FIG. 4 is a diagram illustrating an example of the data structure of the prescription table. As shown in FIG. 4, the prescription table 23a includes, for example, “local patient ID”, “medical treatment date”, “medicine”, “quantity”, “unit”, “usage”, and “number of days”. Are stored in association with each other. Among these, the medicine indicates the name of the prescribed medicine. The quantity indicates the quantity per dose of prescribed medicine. The unit indicates a unit corresponding to the quantity of the prescribed medicine. The usage indicates the usage of the prescribed medicine. The number of days indicates the number of days on which the medicine is prescribed. In addition, since the fixed information is described in the prescription table 23a unlike the free description table 21a, the description contents are less likely to vary even when a patient having the same symptom is examined. On the other hand, since the amount of data contained in the prescription table 23a is large, when a search is executed by accessing this table, the load on the search is higher than that of the free description table 21a.

  As shown in FIG. 4, for example, the prescription table 23 a includes a local patient ID “00000001101”, a medical treatment date “2010/1/17”, a medicine “AA”, a quantity “1”, and a unit “tablet”. The usage “after three meals a day” and the number of days “7” are stored in association with each other. In other words, the prescription table 23a shows that when a patient with ID “0000000101” visited on January 17, 2010, the medicine “AA” to be taken one tablet after meal three times a day was prescribed for seven days. Show. Further, the prescription table 23a similarly stores information on other prescription drugs.

  The detection server 100 includes a communication control unit 101, a storage unit 110, and a control unit 120. The communication control unit 101 is an interface having at least one communication port. For example, the communication control unit 101 controls communication related to various types of information exchanged between the detection server 100 and the search devices 30a to 30c. For example, the communication control unit 101 receives a search program 111 (described later) from an information processing terminal (not shown), and stores the received search program 111 in the storage unit 110.

  The storage unit 110 includes a search program 111, first search result data 112, a patient table 113, a position table 114, second search result data 115, and third search result data 116. The storage unit 110 corresponds to, for example, a semiconductor memory device such as a random access memory (RAM), a read only memory (ROM), and a flash memory, and a storage device such as a hard disk or an optical disk.

  The search program 111 is a program defined for searching information input to the electronic medical record. For example, the search program 111 defines for each infectious disease the screening conditions to be executed by the search device 30a by the first search unit 121, the second search unit 122, and the third search unit 123 described later. For example, for each infectious disease, the search program 111 defines a timing for executing screening, a keyword for screening, and an electronic medical record to be searched.

  The first search result data 112 is data indicating a search result of the primary screening. For example, the first search result data 112 is data in which “medical institution”, “date and time”, “keyword”, “period”, “ratio”, and “local patient ID” are associated with each other. is there. Among these, a medical institution shows the identification information which shows the medical institution by which screening was performed. The date and time indicate the date and time when screening was executed. The keyword indicates a keyword related to screening. The period indicates the period of the medical treatment date to be searched. The ratio indicates the ratio of the number of patients including the keyword in the contents of the electronic medical record among the number of patients included in the electronic medical record to be searched. The local patient ID indicates a local patient ID of a patient whose keyword is included in the contents of the electronic medical record.

  For example, the first search result data 112 includes “medical institution 10a”, “2010/2/20”, “cough” and “nets”, and “2010/2 / 13-2010 / 2/20”. “11%” and “0000000101,...” Are associated with each other. In other words, the first search result data 112 is obtained when screening is performed on February 20, 2010 with patients who have visited the medical institution 10a between February 13, 2010 and February 20, 2010 as search targets. Shows the following results. That is, the first search result data 112 includes “cough” and “net” in the document content of the free description table 21a of 11% of the patients to be searched, and the local patient ID of the patient is “000001011...” In addition, although the case where the first search result data 112 indicates the search result using a ratio has been described here, the present invention is not limited to this. For example, the first search result data 112 may indicate a search result using “number of patients”. That is, the first search result data 112 may indicate the number of patients whose keywords are included in the document content of the free description table 21a among the patients included in the free description table 21a to be searched.

  The patient table 113 stores the local patient IDs of patients who have visited a plurality of medical institutions in association with each other. FIG. 5 is a diagram illustrating an example of a data structure of the patient table. As illustrated in FIG. 5, the patient table 113 stores, for example, “regional patient ID”, “medical institution”, and “local patient ID” in association with each other. Among these, local patient ID shows the identification information allocated to the patient who consulted several medical institutions.

  As illustrated in FIG. 5, for example, the patient table 113 stores a local patient ID “0000000019”, a medical institution “A”, and a local patient ID “0000000101” in association with each other. Further, the patient table 113 stores the regional patient ID “0000000019”, the medical institution “B”, and the local patient ID “0000000209” in association with each other. In addition, the patient table 113 stores a regional patient ID “0000000019”, a medical institution “D”, and a local patient ID “000000000333” in association with each other. That is, in the patient table 113, the patient with the ID “0000000101” of the medical institution “A”, the patient with the ID “0000000209” of the medical institution “B”, and the patient with the ID “0000000333” of the medical institution “D” are the same. It shows that it is a patient. The patient table 113 indicates that the local patient ID of the patient is “0000000019”. In addition, the patient table 113 also stores the patients who have visited a plurality of medical institutions in association with other regional patient IDs.

  The position table 114 stores medical institution coordinates. FIG. 6 is a diagram illustrating an example of the data structure of the position table. As illustrated in FIG. 6, the position table 114 stores, for example, “medical institution”, “longitude”, and “latitude” in association with each other. For example, the position table 114 stores the medical institution “A”, the latitude “153 ° 59′11 ″”, and the longitude “24 ° 16′59 ″” in association with each other. That is, the position table 114 stores that the medical institution “A” exists at the position of latitude “153 degrees 59 minutes 11 seconds” and longitude “24 degrees 16 minutes 59 seconds”.

  Returning to the description of FIG. The second search result data 115 is data indicating the result of the secondary screening. The data structure of the second search result data 115 is the same as the data structure of the first search result data 112, for example.

  The third search result data 116 is data indicating the result of the tertiary screening. The data structure of the third search result data 116 is the same as the data structure of the first search result data 112, for example.

  The control unit 120 includes a first search unit 121, a second search unit 122, a third search unit 123, and an output unit 124. The function of the control unit 120 can be realized by an integrated circuit such as an application specific integrated circuit (ASIC) or a field programmable gate array (FPGA). Further, the function of the control unit 120 can be realized, for example, by a CPU (Central Processing Unit) executing a predetermined program.

  The first search unit 121 causes the search devices of a plurality of medical institutions that store electronic medical records to execute a search using the first keyword with information input to the electronic medical records as a search target. The first keyword is, for example, one or a plurality of keywords whose search target is one table included in the electronic medical record.

  For example, the first search unit 121 executes the search program 111 and generates a primary screening search instruction. This search instruction is, for example, information for instructing to search every day for patients whose two free keywords “cough” and “net” are included in the free description table 21a of patients who have visited within one week. . These two keywords are keywords that are easily input to the free description table 21a when a patient is diagnosed with influenza. The first search unit 121 transmits the generated primary screening search instruction to each of the search devices 30a to 30c.

  Further, for example, the first search unit 121 warns together with the search result of the primary screening from the search device in which the number of patients searched by the primary screening reaches a predetermined number or a predetermined ratio among the search devices 30a to 30c. Receive. This predetermined number or predetermined ratio is a threshold value that defines the epidemic state of an infectious disease, and is, for example, “10%”. For example, when the ratio of patients searched in the primary screening in the search device 30a is “11%”, a warning is received from the search device 30a together with the search result of the primary screening. The search result of this primary screening shows that, for example, the percentage of patients whose two keywords “cough” and “net” are included in the free description table 21a of patients who have visited the medical institution 10a within one week is 11%. It is information indicating that there is. The search result of the primary screening includes the local patient ID of the patient detected by the primary screening. Then, the first search unit 121 stores the received primary screening search result as the first search result data 112 in the storage unit 110. Note that the predetermined number or the predetermined ratio is not limited to this example, and a person using the detection server 100 may set an arbitrary value such as “15%” or “100 people”, for example.

  The second search unit 122 executes the following process when the number of search targets searched by the first keyword reaches a predetermined number or a predetermined ratio in a predetermined number of search devices. In other words, the second search unit 122 searches the information input to the electronic medical record for at least one of the search devices of a plurality of medical institutions using a second keyword that is different from the first keyword. Is executed. The second keyword is, for example, one or a plurality of keywords different from the first keyword with a plurality of tables included in the electronic medical record as search targets.

  Here, there are three patterns for the keyword selected as the second keyword. The first pattern is a case where a keyword whose search target is the free description table 21a is selected as the second keyword. The second pattern is a case where a keyword for which a table other than the free description table 21a, such as the examination result table 22a and the prescription table 23a, is selected as the second keyword is selected. A 3rd pattern is a case where a some keyword is selected as a 2nd keyword so that tables other than the free description table 21a and the free description table 21a may be straddled. In any pattern, detection omission can be prevented. In addition, the second pattern and the third pattern are characterized by a higher load than the first pattern.

  Hereinafter, the secondary screening executed by the second search unit 122 will be described. The secondary screening executed by the second search unit 122 includes secondary screening A and secondary screening B.

  Here, the secondary screening A will be described. For example, when receiving a warning from the search device 30a, the second search unit 122 executes the search program 111 and generates a secondary screening A search instruction for the search device 30a. This search instruction for secondary screening A is, for example, information for instructing to search for patients for whom the drug “AA” is prescribed among the patients searched in the primary screening. This pharmaceutical “AA” is a pharmaceutical that is easily prescribed when a patient is diagnosed with influenza, and corresponds to the second pattern. Then, the second search unit 122 transmits a search instruction for the generated secondary screening A to the search device 30a. Although the case where the keyword corresponding to the second pattern is selected has been described here, the keyword corresponding to the first pattern or the third pattern may be selected.

  For example, the second search unit 122 receives the search result of the secondary screening A. The search result of the secondary screening A is information indicating that, for example, the ratio of patients prescribed for the pharmaceutical “AA” is 8% among the patients searched in the primary screening. The search result of the secondary screening A includes the local patient ID of the patient detected by the secondary screening A. Then, the second search unit 122 stores the received search result of the secondary screening A in the storage unit 110 as the second search result data 115.

  The secondary screening B will be described. For example, when the second search unit 122 receives a warning from a predetermined number of search devices, the second search unit 122 executes the search program 111 and calculates the distance of each search device from the predetermined number of search devices. The predetermined number of search devices is a threshold value that suggests an epidemic of an infectious disease in a search device that has not transmitted a warning, and is “one”, for example. For example, when receiving a warning from one search device 30a, the second search unit 122 executes the search program 111 and calculates the distance of each search device from the search device 30a.

  For example, the second search unit 122 refers to the position table 114 shown in FIG. 6 and calculates the distance of each search device from the search device 30a using the following equation (1). In Formula (1), d shows the angle between two points seen from the center of the earth. Let the latitude and longitude of the search device 30a be δ1 and λ1, and the latitude and longitude of the other search device be δ2 and λ2. Note that the latitude and longitude of each medical institution corresponds to the latitude and longitude of the search device of each medical institution.

  cos d = (sin δ1) × (sin δ2) + (cos δ1) × (cos δ2) × cos (λ1-λ2) (1)

  The second search unit 122 obtains the angle d using an inverse trigonometric function from cos d calculated using the equation (1). The second search unit 122 calculates the distance from the search device 30a to each search device by multiplying the obtained angle d by the average radius 6370 km of the earth. Note that the method for calculating the distance between two points from the latitude and longitude of the two points is not limited to the above method. For example, the second search unit 122 can apply any conventional method in order to calculate the distance between two points from the latitude and longitude of the two points.

  The second search unit 122 refers to the calculated distance from the search device 30a to each search device, and selects a search device existing within a radius of 5 km from the search device 30a. Here, when the search device existing within a radius of 5 km from the search device 30a is the search device 30b, the second search unit 122 selects the search device 30b. The second search unit 122 generates a secondary screening search instruction for the selected search device 30b. The search instruction for the secondary screening B is, for example, information for instructing to search for a patient whose keyword “the throat hurts” is included in the free description table 21a of patients who have visited within one week. This keyword is a keyword that is easily input to the free description table 21a when a patient is diagnosed with influenza, and corresponds to the first pattern. Then, the second search unit 122 transmits a search instruction for the generated secondary screening B to the search device 30b. Although the case where the keyword corresponding to the first pattern is selected has been described here, the keyword corresponding to the second pattern or the third pattern may be selected.

  For example, the second search unit 122 receives the search result of the secondary screening B. The search result of this secondary screening B shows that, for example, in the search device 30b, the percentage of patients whose keyword “sore throat” is included in the free description table 21b of patients who have visited within one week is 15%. It is information to show. The search result of the secondary screening B includes the local patient ID of the patient detected by the secondary screening B.

  In addition, for example, when the same patient is included in both the search result of the secondary screening A and the search result of the secondary screening B, the second search unit 122 displays the information about the patient as a secondary. Delete from the search result of screening B. For example, the second search unit 122 refers to the patient table 113 illustrated in FIG. 5, and the local patient ID of the patient detected in the secondary screening A and the local patient ID of the patient detected in the secondary screening B Are converted into regional patient IDs. The second search unit 122 compares the local patient ID of the patient detected in the secondary screening A with the local patient ID of the patient detected in the secondary screening B, and when there is an overlapping local patient ID. The information about the patient is deleted from the search result of the secondary screening B. Then, the second search unit 122 stores the received search result of the secondary screening B in the storage unit 110 as the second search result data 115. In addition, the process which deletes the information about this overlapping patient does not necessarily need to be performed.

  When the number of patients detected by the secondary screening B reaches a predetermined number or a predetermined ratio, the third search unit 123 executes the search program 111 and generates a tertiary screening search instruction. This predetermined number or predetermined ratio is a threshold value that defines the epidemic state of an infectious disease, and is, for example, “10%”. For example, when the ratio of patients detected in the secondary screening B is 15%, the third search unit 123 executes the search program 111 and generates a tertiary screening search instruction. The search instruction of this tertiary screening includes, for example, “cough” and “nets” or “throat ache” in the electronic medical record of a patient who visited within one week. "Is information for instructing to search for patients including" ". Among these, “cough”, “nets”, and “throat hurts” are retrieved from the free description table 21b. The test “TP” is easily tested when the patient is diagnosed with influenza, and is searched from the test result table 22b. The medicine “AA” is a medicine that is easily prescribed when a patient is diagnosed with influenza, and is retrieved from the prescription table 23b. That is, the keyword selected here corresponds to the above third pattern. Then, the third search unit 123 transmits the generated tertiary screening search instruction to the search device 30b. Note that the predetermined number or the predetermined ratio is not limited to this example, and a person using the detection server 100 may set an arbitrary value such as “15%” or “100 people”, for example. Although the case where the keyword corresponding to the third pattern is selected has been described here, the keyword corresponding to the first pattern or the second pattern may be selected.

  For example, the third search unit 123 receives the search result of the tertiary screening. The search result of this tertiary screening includes, for example, “cough” and “nets” or “throat ache” in the electronic medical record of a patient who visited within one week, and further, the test “TP” and the drug “AA” ”Is information indicating that the ratio of patients including“ 4 ”is 4%. The search result of the tertiary screening includes the local patient ID of the patient detected by the tertiary screening. Then, the third search unit 123 stores the received tertiary screening search result as third search result data 116 in the storage unit 110.

  The output unit 124 outputs a warning based on the search result based on the first keyword and the search result based on the second keyword. For example, when the number of search targets searched by the first keyword reaches a predetermined number or a predetermined ratio, the output unit 124 outputs a warning indicating that fact. This predetermined number or predetermined ratio is a threshold value that defines the epidemic state of an infectious disease, and is, for example, “10%”. For example, the output unit 124 refers to the first search result data 112, and outputs a warning indicating that if the ratio of patients detected by the primary screening is “11%”. Note that the predetermined number or the predetermined ratio is not limited to this example, and a person using the detection server 100 may set an arbitrary value such as “15%” or “100 people”, for example.

  Further, for example, when the number of search targets searched by the second keyword reaches a predetermined number or a predetermined ratio, the output unit 124 outputs a warning indicating that fact. The predetermined number or the predetermined ratio is a threshold value that defines the epidemic state of the infectious disease, and is “12%”, for example. For example, the output unit 124 refers to the second search result data 115, and outputs a warning indicating that if the ratio of patients detected in the secondary screening B is “15%”. Note that the predetermined number or the predetermined ratio is not limited to this example, and a person using the detection server 100 may set an arbitrary value such as “15%” or “100 people”, for example.

  Further, for example, the output unit 124 outputs the first search result data 112, the second search result data 115, and the third search result data 116 in response to a request from the user.

  The search device 30a performs a search using information input to the electronic medical record as a search target. For example, the search device 30a corresponds to a gateway server, a center router, or the like.

  For example, the search device 30a receives a primary screening search instruction from the detection server 100, and executes primary screening using information input to the electronic medical record stored in the electronic medical record device 20a as a search target. For example, the search device 30a periodically searches for patients whose two free keywords “cough” and “nets” are included in the free description table 21a of patients who have visited within one week every day. The search device 30a transmits a warning to the detection server 100 when the number of patients searched by the primary screening reaches a predetermined number or a predetermined ratio. This predetermined number or predetermined ratio is a threshold value that defines the epidemic state of an infectious disease, and is, for example, “10%”. When the ratio of patients searched by the primary screening is “11%”, the search device 30a transmits a warning to the detection server 100 together with the search result of the primary screening. Note that the predetermined number or the predetermined ratio is not limited to this example, and a person using the detection server 100 may set an arbitrary value such as “15%” or “100 people”, for example.

  Further, for example, the search device 30a receives a search instruction for secondary screening A from the detection server 100, and executes the secondary screening A using information input to the electronic medical record stored in the electronic medical record device 20a as a search target. . For example, the search device 30a searches for a patient whose medicine “AA” is included in the patient prescription table 23a searched in the primary screening. The search device 30a transmits the search result of the secondary screening A to the detection server 100.

  Further, for example, the search device 30a receives a search instruction for the secondary screening B from the detection server 100, and executes the secondary screening B with the information input to the electronic medical record stored in the electronic medical record device 20a as a search target. . For example, the search device 30a searches for a patient whose keyword “the throat hurts” is included in the free description table 21a of the patient who visited within one week. The search device 30a transmits the search result of the secondary screening B to the detection server 100.

  Further, for example, the search device 30a receives a search instruction for tertiary screening from the detection server 100, and executes tertiary screening using information input to the electronic medical record stored in the electronic medical record device 20a as a search target. For example, the search device 30a includes “cough” and “nettle” or “throat hurts” in the electronic medical record of a patient who visited within one week, and further includes a test “TP” and a medicine “AA”. Search for patients. The search device 30a transmits the search result of the tertiary screening to the detection server 100.

  Next, a processing procedure of the detection server 100 according to the embodiment will be described. FIG. 7 is a flowchart illustrating the processing procedure of the detection server according to the embodiment. The medical chart shown in FIG. 7 corresponds to an electronic medical chart. The process shown in FIG. 7 is executed at predetermined time intervals, for example, while power is supplied from the power source to the illustrated devices.

  As illustrated in FIG. 7, the search device 30a periodically performs primary screening using information input to the electronic medical record stored in the electronic medical record device 20a as a search target (step S1a). Then, the search device 30a determines whether or not the condition is matched (step S2a). That is, the search device 30a determines whether or not the number of patients searched by the primary screening has reached a predetermined number or a predetermined ratio. Note that the search device 30a periodically repeats the process of step S1a and the process of step S2a in accordance with a search instruction for primary screening until a condition is matched. In addition, the search device 30b executes the process of step S1b and the process of step S2b in the same manner as the process of step S1a and the process of step S2a executed by the search device 30a. In addition, the search device 30c executes the process of step S1c and the process of step S2c in the same manner as the process of step S1a and the process of step S2a executed by the search device 30a. Here, the screening executed by each of the search devices 30a to 30c may be executed at the same timing or may be executed at different timings.

  If the search device 30a determines that the condition is met (step S2a, Yes), the search device 30a notifies the detection server 100 to that effect (step S3). That is, for example, when the ratio of patients searched by the primary screening is “11%”, the search device 30a transmits a warning to the detection server 100 together with the search result of the primary screening. In the following, the case where the search device 30a is determined to match the condition will be described. However, the same processing is executed when the search device 30b or the search device 30c is determined to match the condition, and thus the description is omitted. To do.

  The detection server 100 searches for an instruction target (step S4). That is, when the detection server 100 receives a warning from a predetermined number of search devices, the detection server 100 executes the search program 111 and calculates the distance of each search device from the predetermined number of search devices. The detection server 100 refers to the calculated distance from the search device 30a to each search device, and selects a search device existing within a radius of 5 km from the search device 30a. Here, when the search device existing within a radius of 5 km from the search device 30a is the search device 30b, the second search unit 122 selects the search device 30b.

  The detection server 100 instructs secondary screening (step S5). That is, the detection server 100 generates a secondary screening search instruction for the selected search device 30b, and transmits the generated secondary screening B search instruction to the search device 30b. Further, the detection server 100 executes the search program 111, generates a search instruction for secondary screening A to the search apparatus 30a, and transmits the generated search instruction for secondary screening A to the search apparatus 30a.

  The search device 30a executes the secondary screening A with the information input to the electronic medical record stored in the electronic medical record device 20a as a search target (step S6). For example, the search device 30a searches for a patient whose medicine “AA” is included in the patient prescription table 23a searched in the primary screening. The search device 30a notifies the result (step S7). That is, the search device 30a transmits the search result of the secondary screening A to the detection server 100.

  The search device 30b executes the secondary screening B with the information input to the electronic medical record stored in the electronic medical record device 20b as a search target (step S8). For example, the search device 30b searches for a patient whose keyword “the throat hurts” is included in the free description table 21b of the patient who consulted within one week. The search device 30b notifies the result (step S9). That is, the search device 30a transmits the search result of the secondary screening B to the detection server 100.

  The detection server 100 performs duplicate deletion (step S10). That is, when the same patient is included in both the search result of the secondary screening A and the search result of the secondary screening B, the detection server 100 uses the search result of the secondary screening B as information about the patient. Delete from.

  The detection server 100 determines whether or not tertiary screening is necessary (step S11). That is, the detection server 100 determines whether or not the number of patients detected in the secondary screening B has reached a predetermined number or a predetermined ratio. When it is determined that the tertiary screening is necessary (step S11, Yes), the detection server 100 instructs the tertiary screening (step S12). That is, the detection server 100 executes the search program 111, generates a search instruction for tertiary screening, and transmits the generated search instruction for tertiary screening to the search device 30b.

  The search device 30b performs tertiary screening using information input to the electronic medical record stored in the electronic medical record device 20b as a search target (step S13). For example, the search device 30a includes “cough” and “nettle” or “throat hurts” in the electronic medical record of a patient who visited within one week, and further includes a test “TP” and a medicine “AA”. Search for patients. The search device 30b notifies the result (step S14). That is, the search device 30b transmits the search result of the tertiary screening to the detection server 100.

  The detection server 100 reports the result (step S15). That is, the detection server 100 outputs the first search result data 112, the second search result data 115, and the third search result data 116 in response to a request from the user.

  On the other hand, when the detection server 100 determines that the tertiary screening is not necessary (step S11, No), the detection server 100 reports the result (step S16). That is, the detection server 100 outputs the first search result data 112, the second search result data 115, and the third search result data 116 in response to a request from the user.

  Note that, in the processing procedure described above, the process of step S10 that is a process of performing duplicate deletion may not necessarily be executed. That is, after the process of step S9 is performed, the process of step S11 may be performed.

  In the processing procedure described above, the secondary screening A process is executed after the secondary screening A process is executed. However, the present invention is not limited to this. For example, the secondary screening A process may be executed after the secondary screening B process. Further, the secondary screening A process and the secondary screening B process may be executed simultaneously.

  Next, effects of the detection server 100 according to the embodiment will be described. The detection server 100 causes each of the search devices of a plurality of medical institutions that store the electronic medical record to execute a search using the first keyword with information input to the electronic medical record as a search target. The detection server 100 performs the following process when the number of search targets searched by the first keyword reaches a predetermined number or a predetermined ratio in a predetermined number of search devices. That is, the detection server 100 causes at least one of the search devices of a plurality of medical institutions to perform a search using a second keyword that is different from the first keyword, using information input to the electronic medical record as a search target. . The detection server 100 outputs a warning based on the search result based on the first keyword and the search result based on the second keyword. For this reason, the detection server 100 can prevent omission of detection of an infectious disease even if the contents described in the medical record are different depending on the doctor.

  For example, in the primary screening, the detection server 100 searches using three keywords “38 degrees or more”, “joint pain”, and “chills” that are typical symptoms of influenza. When a predetermined number of medical institutions in which the number of patients detected by the primary screening has reached a predetermined number exist in the same area, the detection server 100 performs the following process. That is, the detection server 100 performs primary such as “37 degrees or more”, “throat pain”, and “headache” with respect to a medical institution where the number of patients detected by the primary screening in the same region has not reached the predetermined number. Search again using keywords that are different from screening. This different keyword is a possible flu symptom. For this reason, the detection server 100 can detect the presence of a symptom that may be influenza even if a typical symptom of influenza is not described in the electronic medical record.

  Further, the detection server 100 executes a search with a low processing load on the search device as compared with the second keyword as a search using the first keyword. Further, the detection server 100 executes a search with a higher processing load on the search device as compared with the first keyword as a search by the second keyword. In this way, the detection server 100 does not first execute a search using the second keyword having a high processing load, but performs a search using the first keyword having a low processing load, thus reducing the load on detection. be able to. In addition, as described above, there are three patterns for the keyword selected as the second keyword. Among these, the second pattern and the third pattern have a higher processing load than the first pattern. The detection server 100 executes a search that only loads a predetermined search device when the number of search targets searched by the first keyword reaches a predetermined number or a predetermined ratio in a predetermined number of search devices. Therefore, it is possible to reduce the load required for detecting an infectious disease.

  In addition, the detection server 100 performs a search by the second keyword as a search by the second keyword with respect to a search device in which the number of search objects searched by the first keyword does not reach a predetermined number or a predetermined ratio. Let it run. In this way, the detection server 100 does not cause the search by the second keyword for all search devices, but selectively causes the search device to execute the search by the second keyword. The load related to the detection of infectious diseases can be reduced.

  For example, when the free description table 21a is set as a search target, the load on the search can be reduced as compared with other electronic medical records as search targets, but there are variations in the keywords described in the free description table 21a by the doctor. It was. On the other hand, when the test result table 22a and the prescription table 23a are to be searched, there is no variation in the keywords to be described, but when searching together with the free description table 21a for use in detecting an infectious disease, the search is performed. Such a load was large. For this reason, the detection server 100 stores the test result table 22a and the prescription table 23a only when the number of search targets searched by the keyword described in the free description table 21a reaches a predetermined number or a predetermined ratio. Search target. For this reason, the detection server 100 can reduce the load concerning the detection of an infectious disease.

  By the way, in the above-described embodiment, the case where the primary screening to the tertiary screening are executed has been described. However, the tertiary screening is not necessarily required, and the primary screening and the secondary screening may be executed. Moreover, although the case where the secondary screening A and the secondary screening B were performed as a secondary screening was demonstrated, any one secondary screening should just be performed. Further, the keyword selected in the secondary screening may correspond to any one of the three patterns described above. That is, the detection server 100 illustrated in FIG. 1 does not necessarily have to include all the processing units illustrated in FIG. For example, the detection server 100 only has to include the first search unit 121, the second search unit 122, and the output unit 124.

  In other words, the first search unit 121 causes the search devices of a plurality of medical institutions that store electronic medical records to execute a search using the first keyword with information input to the electronic medical records as a search target. The second search unit 122 performs the following process when the number of search objects searched by the first keyword reaches a predetermined number or a predetermined ratio in a predetermined number of search devices. That is, the second search unit 122 causes each of the plurality of search devices to execute a search using a second keyword that is different from the first keyword, using information input to the electronic medical record as a search target. The output unit 124 outputs a warning based on the search result based on the first keyword and the search result based on the second keyword. For this reason, the detection server 100 can prevent omission of detection of an infectious disease even if the contents described in the medical record are different depending on the doctor.

  Also, among the processes described in the embodiments, all or part of the processes described as being performed automatically can be performed manually, or all of the processes described as being performed manually are performed. Alternatively, a part can be automatically performed by a known method. For example, it has been described that the output unit 124 outputs the first search result data 112, the second search result data 115, and the third search result data 116 in response to a request from the user. However, the output unit 124 is not limited to this, and the output unit 124 automatically performs every time the first search result data 112, the second search result data 115, and the third search result data 116 are stored in the storage unit 110. May be output automatically. In addition, the processing procedures, control procedures, specific names, and information including various data and parameters shown in the above-described document and drawings can be arbitrarily changed unless otherwise specified. For example, the free description table 21a does not necessarily store the document type.

  Each component of the detection server 100 shown in FIG. 1 is functionally conceptual and does not necessarily need to be physically configured as illustrated. That is, the specific form of distribution / integration of the detection server 100 is not limited to that shown in the figure, and all or part of the detection server 100 is functionally or physically distributed in arbitrary units according to various loads or usage conditions. -Can be integrated and configured. For example, the first search result data 112, the second search result data 115, and the third search result data 116 shown in FIG. 1 may be included as the same data.

  The detection server 100 is not limited to a server device, and can be realized by mounting each function of the detection server 100 in a known information processing device. Known information processing apparatuses correspond to apparatuses such as personal computers and workstations, for example.

  FIG. 8 is a diagram illustrating an example of a computer that executes a detection program. As illustrated in FIG. 8, the computer 300 includes a CPU 301 that executes various arithmetic processes, an input device 302 that receives data input from a user, and a monitor 303. The computer 300 also includes a medium reading device 304 that reads a program or the like from a storage medium, an interface device 305 for connecting to another device, and a wireless communication device 306 for connecting to another device wirelessly. The computer 300 also includes a RAM (Random Access Memory) 307 that temporarily stores various types of information and a hard disk device 308. Each device 301 to 308 is connected to a bus 309.

  The hard disk device 308 stores an update program having the same functions as the processing units of the first search unit 121, the second search unit 122, and the output unit 124 illustrated in FIG. The hard disk device 308 stores various data of the search program 111 and the position table 114 in order to implement a detection program.

  The CPU 301 reads each program stored in the hard disk device 308, develops it in the RAM 307, and performs various processes. In addition, these programs can cause the computer to function as the search unit 121, the second search unit 122, and the output unit 124 illustrated in FIG.

  Note that the above detection program does not necessarily have to be stored in the hard disk device 308. For example, the computer 300 may read and execute a program stored in a computer-readable recording medium. As the computer-readable recording medium, for example, a portable recording medium such as a CD-ROM, a DVD disk, and a USB memory, a semiconductor memory such as a flash memory, a hard disk drive, and the like are supported. Further, the program may be stored in a device connected to a public line, the Internet, a LAN (Local Area Network), a WAN (Wide Area Network), etc., and the computer 300 may read and execute the program therefrom. good.

  The following supplementary notes are further disclosed with respect to the embodiments including the above examples.

(Supplementary note 1)
With respect to each of the search devices of a plurality of medical institutions that store the electronic medical record, the search by the first keyword is executed with the information input in the electronic medical record as a search target,
In the first predetermined number of search devices, when the number of search objects searched by the first keyword reaches a second predetermined number or a predetermined ratio, at least one of the search devices of the plurality of medical institutions In response to the information input to the electronic medical record as a search target, a search using a second keyword different from the first keyword is executed,
A detection method comprising: executing a process for outputting a warning based on a search result by the first keyword and a search result by the second keyword.

(Additional remark 2) The process which performs the search by the said 1st keyword performs the search with a low processing load in the said search apparatus compared with the said 2nd keyword,
The detection method according to appendix 1, wherein the process of executing the search by the second keyword executes a search having a higher processing load on the search device than the first keyword.

(Additional remark 3) The process which performs the search by the said 2nd keyword is with respect to the search apparatus in which the number of the search objects searched with the said 1st keyword did not reach said 2nd predetermined number or a predetermined ratio. The detection method according to appendix 1 or 2, wherein a search by the second keyword is executed.

(Additional remark 4) The 1st search part which performs the search by a 1st keyword by making into search object the information input into the said electronic medical record with respect to each of the search device of the some medical institution which memorize | stores an electronic medical record,
In the first predetermined number of search devices, when the number of search objects searched by the first keyword reaches a second predetermined number or a predetermined ratio, at least one of the search devices of the plurality of medical institutions On the other hand, a second search unit that executes a search using a second keyword different from the first keyword, with the information input in the electronic medical record as a search target;
A detection server comprising: an output unit that outputs a warning based on a search result based on the first keyword and a search result based on the second keyword.

(Additional remark 5) The said 1st search part performs the search with a low processing load in the said search device compared with the said 2nd keyword,
The detection server according to appendix 4, wherein the second search unit executes a search that has a higher processing load on the search device than the first keyword.

(Additional remark 6) The said 2nd search part is a said 2nd keyword with respect to the search device in which the number of the search objects searched with the said 1st keyword did not reach said 2nd predetermined number or a predetermined ratio. The detection server according to appendix 4 or 5, wherein the search according to claim 4 is executed.

100 detection server 101 communication control unit 110 storage unit 111 search program 112 search result data 113 patient table 114 position table 115 search result data 116 search result data 120 control unit 121 first search unit 122 second search unit 123 third Search unit 124 Output unit 300 Computer 301 CPU
302 Input Device 303 Monitor 304 Medium Reading Device 305 Interface Device 306 Wireless Communication Device 307 RAM
308 Hard disk device 309 Bus

Claims (4)

The detection server
With respect to each of the search devices of a plurality of medical institutions that store the electronic medical record, the search by the first keyword is executed with the information input in the electronic medical record as a search target,
In the first predetermined number of search devices, when the number of search objects searched by the first keyword reaches a second predetermined number or a predetermined ratio, at least one of the search devices of the plurality of medical institutions In response to the information input to the electronic medical record as a search target, a search using a second keyword different from the first keyword is executed,
A detection method comprising: executing a process for outputting a warning based on a search result by the first keyword and a search result by the second keyword. The process of executing the search by the first keyword executes a search with a low processing load in the search device as compared with the second keyword,
2. The detection method according to claim 1, wherein the process of executing a search by the second keyword executes a search having a higher processing load on the search device than the first keyword.   The process of executing the search by the second keyword is performed by using the second keyword for a search device in which the number of search objects searched by the first keyword has not reached the second predetermined number or a predetermined ratio. The detection method according to claim 1, wherein a search based on a keyword is executed. A first search unit that executes a search using a first keyword, with the information input in the electronic medical record as a search target, for each of a plurality of medical institution search devices that store the electronic medical record;
In the first predetermined number of search devices, when the number of search objects searched by the first keyword reaches a second predetermined number or a predetermined ratio, at least one of the search devices of the plurality of medical institutions On the other hand, a second search unit that executes a search using a second keyword different from the first keyword, with the information input in the electronic medical record as a search target;
A detection server comprising: an output unit that outputs a warning based on a search result based on the first keyword and a search result based on the second keyword.

Images