JP6919540B2 - Interview support program, disease estimation program, interview support method, disease estimation method and information processing device - Google Patents

Description

The present invention relates to a medical inquiry support program, a disease estimation program, a medical inquiry support method, a disease estimation method, and an information processing device.

Conventionally, when visiting a hospital, it is required to fill out a questionnaire at the reception desk of the hospital at the time of the first visit or the first visit to the department. However, when filling out the questionnaire, the question content may be vague and you may not be able to write what you want to convey, or you may not be able to properly answer the questions of nurses and doctors. On the other hand, when a specific interview item is linked to the patient's identification information, an interview that includes additional questions associated with the specific inquiry item, information about the drug, etc. before displaying the medical record information. It has been proposed to display support information.

Japanese Unexamined Patent Publication No. 2015-001876

However, displaying additional questions about a particular question or information about a drug may not be what the patient wants to sue. For this reason, nurses and doctors want to make a complaint by changing the question content flexibly according to the information such as the medical examination in the hospital that there is an epidemic illness at the time of medical examination. I try to hear it. However, it is difficult to ask questions according to such epidemic diseases using the questionnaire.

One aspect is to provide a medical inquiry support program, a disease estimation program, a medical inquiry support method, a disease estimation method, and an information processing device that can support the input of symptoms according to the epidemic of the disease.

In one aspect, the interview support program causes the computer to execute a process of receiving the answer result to the predetermined inquiry from the information processing terminal. The interview support program causes the computer to execute a process of identifying a disease candidate based on the received answer result. When there are a plurality of the identified disease candidates, the interview support program causes the computer to execute a process of determining a search range in the storage unit in which the medical examination results are recorded according to the degree of epidemic of the disease candidates. The medical inquiry support program searches the medical examination results within the determined range, and causes the computer to execute a process of identifying additional medical examination information that can further narrow down the disease from the disease candidates. The interview support program causes the computer to execute a process of transmitting the specified additional interview information to the information processing terminal.

It can support the input of symptoms according to the epidemic of the disease.

FIG. 1 is a block diagram showing an example of the configuration of the interview support system of the embodiment. FIG. 2 is a diagram showing an example of a symptom DB. FIG. 3 is a diagram showing an example of the first medical examination result DB. FIG. 4 is a diagram showing an example of the second medical examination result DB. FIG. 5 is a diagram showing an example of the third medical examination result DB. FIG. 6 is a diagram showing an example of a score storage unit. FIG. 7 is a diagram showing an example of a disease prediction table. FIG. 8 is a diagram showing an example of a questionnaire storage unit. FIG. 9 is a diagram showing an example of the interview screen. FIG. 10 is a diagram showing another example of the interview screen. FIG. 11 is a diagram showing another example of the interview screen. FIG. 12 is a flowchart showing an example of the interview support process of the embodiment. FIG. 13 is a diagram showing an example of a computer that executes an interview support program or a disease estimation program.

Hereinafter, examples of the medical inquiry support program, the disease estimation program, the medical inquiry support method, the disease estimation method, and the information processing apparatus disclosed in the present application will be described in detail based on the drawings. The disclosed technology is not limited by the present embodiment. In addition, the following examples may be appropriately combined as long as they do not contradict each other.

FIG. 1 is a block diagram showing an example of the configuration of the interview support system of the embodiment. The interview support system 1 shown in FIG. 1 includes a mobile terminal 10 and an information processing device 100. The number of mobile terminals 10 is not limited in the interview support system 1, and an arbitrary number of mobile terminals 10 may be provided. The mobile terminal 10 and the information processing device 100 are connected to each other so as to be able to communicate with each other via the network N.

As the network N, any kind of communication network such as LAN (Local Area Network) and VPN (Virtual Private Network) can be adopted as well as the Internet regardless of whether it is wired or wireless. Further, the communication between the mobile terminal 10 and the information processing device 100 via the network N is encrypted by, for example, TLS (Transport Layer Security) / SSL (Secure Sockets Layer) or the like.

The interview support system 1 is an example of a system for filling out a questionnaire in advance on the mobile terminal 10. The mobile terminal 10 is, for example, various terminals such as a mobile communication terminal such as a smartphone and a portable personal computer, and is, for example, an information processing terminal in which a patient outside the hospital such as a home fills out a questionnaire. ..

For example, the mobile terminal 10 activates a reservation application by the operation of a patient, and accepts a medical examination reservation and an input of a questionnaire. In the input of the questionnaire, the mobile terminal 10 accepts the input of the patient's identification information and also accepts the selection of the clinical department to be examined by the patient. The mobile terminal 10 transmits the received patient identification information and the clinical department information indicating the selected clinical department to the information processing device 100. The mobile terminal 10 receives the patient's electronic medical record information and the questionnaire information according to the patient's identification information and the examination department information from the information processing device 100. The mobile terminal 10 presents the questionnaire to the patient based on the patient's electronic medical record information and the questionnaire information, and prompts the patient to input the questionnaire. When the main complaint is input among the input items of the questionnaire, the mobile terminal 10 transmits the entered main complaint as the main complaint information to the information processing device 100.

Further, the mobile terminal 10 receives the interview information from the information processing device 100 after transmitting the chief complaint information. The mobile terminal 10 asks the patient a question based on the received interview information, and transmits the answer to the question to the information processing device 100 as new chief complaint information. When the mobile terminal 10 receives the input completion information from the information processing device 100, it determines that the input of the questionnaire has been completed, and stores the input contents of the questionnaire. When the mobile terminal 10 detects arrival at the hospital based on, for example, reception of a beacon installed in the hospital or position information measured by a GPS (Global Positioning System) receiver or the like, the input contents of the stored questionnaire are stored. Is transmitted to the information processing device 100.

The information processing device 100 receives an answer result to a predetermined inquiry from the mobile terminal 10 which is an information processing terminal. The information processing device 100 identifies a disease candidate based on the received response result. When there are a plurality of identified disease candidates, the information processing device 100 determines a range to be searched from the storage unit in which the medical examination results are recorded according to the degree of epidemic of the disease candidates. The information processing device 100 searches the medical examination results within a determined range, and identifies additional medical examination information that can further narrow down the disease from the disease candidates. The information processing device 100 transmits the specified additional inquiry information to the mobile terminal 10. Thereby, the information processing apparatus 100 can support the input of the symptom according to the epidemic of the disease.

Next, the configuration of the information processing device 100 will be described. As shown in FIG. 1, the information processing device 100 includes a communication unit 110, a storage unit 120, and a control unit 130. In addition to the functional units shown in FIG. 1, the information processing device 100 may have various functional units of a known computer, for example, various functional units such as various input devices and audio output devices.

The communication unit 110 is realized by, for example, a NIC (Network Interface Card) or the like. The communication unit 110 is a communication interface that is connected to the mobile terminal 10 by wire or wirelessly via the network N and controls information communication with the mobile terminal 10. The communication unit 110 outputs the patient identification information, the clinical department information, and the chief complaint information received from the mobile terminal 10 to the control unit 130. In addition, the communication unit 110 transmits the patient's electronic medical record information, questionnaire information, questionnaire information, and input completion information input from the control unit 130 to the mobile terminal 10.

The storage unit 120 is realized by, for example, a semiconductor memory element such as a RAM (Random Access Memory) or a flash memory (Flash Memory), or a storage device such as a hard disk or an optical disk. The storage unit 120 has a symptom database 121, a medical examination record database 122, a score storage unit 123, a disease prediction table 124, and a questionnaire storage unit 125. In the following description, the database will be referred to as DB. Further, the storage unit 120 stores information used for processing by the control unit 130.

The symptom DB 121 stores the disease name and the symptom in association with each other. FIG. 2 is a diagram showing an example of a symptom DB. As shown in FIG. 2, the symptom DB 121 has items such as "disease name", "age of onset", "gender", and "symptom". The symptom DB 121 is stored as one record for each disease name, for example.

The "disease name" is information indicating the name of the disease. The "age of onset" is information indicating the age at which the person is likely to suffer from the disease. “Gender” is information indicating the gender that may cause the disease. "Symptom" is information indicating a symptom in the disease. For "symptoms", if there are multiple symptoms, each symptom is arranged in order. The shaded cells in FIG. 2 indicate those that match the complaint information in the specific examples described later.

Returning to the description of FIG. 1, the medical examination record DB 122 stores the electronic medical record of the patient and also stores various medical examination record DBs according to the purpose. The medical examination result DB 122 has, for example, a first medical examination result DB 122a, a second medical examination result DB 122b, and a third medical examination result DB 122c as various medical examination result DBs.

The first medical examination result DB 122a is, for example, a combination of the number of patients and the contents of the symptom DB 121 for a disease having a large number of patients within a predetermined period. FIG. 3 is a diagram showing an example of the first medical examination result DB. As shown in FIG. 3, the first medical examination result DB122a has items such as "disease name", "number of patients", "age of onset", "gender", and "symptom". The first medical examination result DB122a is stored as one record for each disease name, for example.

The "disease name" is information indicating the name of the disease. The "number of patients" is information indicating the number of patients examined within a predetermined period. The predetermined period includes, for example, a period of 3 months, 6 months, and 1 year, but is not limited to this. The "age of onset" is information indicating the age at which the person is likely to suffer from the disease. “Gender” is information indicating the gender that may cause the disease. "Symptom" is information indicating a symptom in the disease. For "symptoms", if there are multiple symptoms, each symptom is arranged in order. The shaded cells in FIG. 3 indicate those that match the complaint information in the specific examples described later.

The second medical examination result DB122b shows the number of patients by month for diseases with a large number of patients. FIG. 4 is a diagram showing an example of the second medical examination result DB. As shown in FIG. 4, the second medical examination result DB122b has items such as "disease name", "type", "current month", "-January" to "-November", and "total".

The "disease name" is information indicating the name of the disease. The "type" is information indicating whether the number of patients is the number of patients or the percentage (%). The percentage (%) is, for example, the percentage of the total number of patients in the month. "Current month" is information indicating the number or percentage (%) of patients in the current month. "-January" to "-November" are information indicating the number or percentage (%) of patients in each month from 1 month ago to 11 months ago, respectively. "Total" is information indicating the total number of patients from the current month to 11 months ago.

The third medical examination result DB122c is obtained by extracting patient data from the electronic medical record after the month when the disease epidemic started. FIG. 5 is a diagram showing an example of the third medical examination result DB. As shown in FIG. 5, the third medical examination result DB122c has items such as "disease name", "examination date", "gender", "age", and "symptom". The third medical examination result DB 122c stores the patient data corresponding to one medical examination as one record.

The "disease name" is information indicating the name of the disease. The "consultation date" is information indicating the consultation date of a patient diagnosed with the disease. "Gender" is information indicating the gender of a patient diagnosed with the disease. "Age" is information indicating the age of a patient diagnosed with the disease. The "symptom" is information indicating a symptom complained by a patient diagnosed with the disease. In FIG. 5, the symptoms 20a and 20b indicate that the symptoms are not in the symptom DB 121 in the specific example described later.

Returning to the description of FIG. 1, the score storage unit 123 stores a score table for calculating a score for identifying a disease candidate. FIG. 6 is a diagram showing an example of a score storage unit. As shown in FIG. 6, the score storage unit 123 has a score table 123a corresponding to the symptom DB 121 and a score table 123b corresponding to the first medical examination result DB 122a. The score table 123a and the score table 123b have items such as "symptom matching number", "coefficient", "age", "gender", and "score".

The "symptom matching number" is information indicating the number of symptoms that match the complaint information. The "coefficient" is a coefficient for weighting the symptom DB 121 and the first medical examination result DB 122a. In the example of FIG. 6, the coefficient "1" is set in the score table 123a corresponding to the symptom DB 121, and the coefficient "3" is set in the score table 123b corresponding to the first examination result DB 122a, and the first examination result DB 122a is prioritized. Show that. "Age" is a score according to the patient's age. The "age" is, for example, "1.0" when the age of the patient matches the onset age of the symptom DB121 or the first medical examination record DB122a, and "0.1" when the age does not match. "Gender" is a score according to the patient's gender. The “gender” is, for example, “1” when the gender of the patient matches the gender of the symptom DB121 or the first medical examination record DB122a, and “0” when the gender does not match. The "score" is information indicating a score obtained by multiplying the numerical values of "symptom matching number", "coefficient", "age" and "gender".

Returning to the description of FIG. 1, the disease prediction table 124 stores the score of the disease candidate, the symptom of the disease candidate, and the symptom not in the symptom DB 121 but in the third medical examination result DB 122c in association with each other. FIG. 7 is a diagram showing an example of a disease prediction table. As shown in FIG. 7, the disease prediction table 124 has items such as "disease name", "score", "symptom", and "symptom in the third medical examination record DB". The disease prediction table 124 stores, for example, one record for each disease name.

The "disease name" is information indicating the name of the disease of the disease candidate. The "score" is information indicating the score of a disease candidate. The score of the disease candidate is the score obtained by adding the item "score" in the score table 123a and the score table 123b for each disease. "Symptom" is information indicating a symptom in a disease of a disease candidate. The "symptom" here corresponds to the "symptom" of the symptom DB 121. "Symptoms in the third medical examination record DB" is information indicating a symptom that is not in the "symptom" column of the symptom DB 121, but is in the "symptom" column of the third medical examination result DB 122c.

Returning to the description of FIG. 1, the questionnaire storage unit 125 stores the input contents of the patient's questionnaire. FIG. 8 is a diagram showing an example of a questionnaire storage unit. As shown in FIG. 8, the questionnaire storage unit 125 has items such as “patient ID (Identifier)”, “question input date”, “weight”, “age”, “gender”, and “patient complaint”. The questionnaire storage unit 125 stores, for example, one record for each visit of the patient. It should be noted that each item of the questionnaire storage unit 125 may be diverted from, for example, an electronic medical record or an item that can be diverted from past questionnaire input information. In addition, each item of the questionnaire storage unit 125 corresponds to the questionnaire information indicating the item of the questionnaire. As for the memory of the input contents of the questionnaire to the questionnaire storage unit 125, the information processing device 100 receives the input contents of the questionnaire from the mobile terminal 10 when the mobile terminal 10 detects the arrival at the hospital. It is done by remembering.

The "patient ID" is an identifier that identifies the patient. The "questionnaire input date" is information indicating the input date of the questionnaire this time. The "questionnaire input date" may include the time. "Weight" is information indicating the weight of a patient. "Age" is information indicating the age of a patient. "Gender" is information indicating the gender of a patient. The "patient complaint" is information indicating the symptoms and the like that the patient is complaining about at this visit.

Returning to the description of FIG. 1, in the control unit 130, for example, a program stored in an internal storage device is executed by a CPU (Central Processing Unit), an MPU (Micro Processing Unit), or the like using the RAM as a work area. It is realized by. Further, the control unit 130 may be realized by, for example, an integrated circuit such as an ASIC (Application Specific Integrated Circuit) or an FPGA (Field Programmable Gate Array). The control unit 130 includes a reception unit 131, a first specific unit 132, a second specific unit 133, and a generation unit 134, and realizes or executes the functions and operations of information processing described below. The internal configuration of the control unit 130 is not limited to the configuration shown in FIG. 1, and may be another configuration as long as it is a configuration for performing information processing described later.

The reception unit 131 receives the patient identification information and the clinical department information from the mobile terminal 10 via the network N and the communication unit 110. The reception unit 131 acquires the patient's electronic medical record information from the medical examination record DB 122 that stores the electronic medical record, based on the received patient identification information. The reception unit 131 transmits the electronic medical record information of the patient and the questionnaire information corresponding to the received clinical department information to the mobile terminal 10 via the communication unit 110 and the network N. The mobile terminal 10 may store data such as allergies, surgical history, drug history, and medical history in advance, and even if the patient fills out the questionnaire, these data are already input. good. Further, in the specific example of the following explanation, it is assumed that the consultation date is February 5, 2017, and a 25-year-old man is a patient.

The reception unit 131 receives the chief complaint information from the mobile terminal 10 via the network N and the communication unit 110. The reception unit 131 outputs the received chief complaint information and the patient's electronic medical record information to the first specific unit 132. That is, the reception unit 131 is an example of a reception unit that receives the chief complaint information which is the result of answering a predetermined inquiry from the mobile terminal 10 which is an information processing terminal. In addition, the reception unit 131 accepts input of chief complaint information which is information for identifying one or a plurality of symptoms.

When the chief complaint information and the electronic medical record information of the patient are input from the reception unit 131, the first specific unit 132 refers to the symptom DB 121 and calculates the score of the disease candidate based on the input chief complaint information. For example, when the chief complaint information is "headache" and "has a fever", the first specific unit 132 determines the number of the corresponding "headache" and "fever" that match the symptom in the symptom DB 121. Calculated for each disease name, that is, symptom candidate. In addition, the first specific unit 132 calculates the score corresponding to the age and gender of the patient based on the electronic medical record information of the patient. The first specific unit 132 calculates the score of the disease candidate by multiplying the score of each symptom match, the coefficient, the age, and the gender. The first specific unit 132 stores the calculated score of the disease candidate in the score table 123a of the score storage unit 123. When the score of the disease candidate is stored in the score table 123a, the first specific unit 132 outputs the chief complaint information and the electronic medical record information of the patient to the second specific unit 133.

For example, in the case of the disease name "chronic XX flame" in the first line of the symptom DB 121 shown in FIG. 2, the first specific part 132 has a coefficient of "1" and an onset age of "all ages" because it is the symptom DB 121. Therefore, the age score is calculated as "1.0", and the gender score is calculated as "1" because the gender is "male and female". Further, in the first specific unit 132, as shown by the shading in FIG. 2, since the symptom "fever" and "headache" match the "fever" and "headache" of the chief complaint information, the number of symptom matches is set to "2". Is calculated. The first specific unit 132 multiplies these scores and coefficients to calculate the score of the disease candidate “chronic XX flame” as “2.0”.

In other words, the first specific unit 132 identifies the disease candidate based on the complaint information which is the received response result. In addition, the first specific unit 132 identifies a disease candidate with reference to the symptom DB 121, which is a storage unit that associates the disease with the symptom group. In addition, the first specific unit 132 refers to the symptom DB 121, which is the first storage unit that stores the correspondence between the disease and the symptom group, and one or a plurality of symptoms specified by the input information (chief complaint information). Identify the disease associated with the most correlated symptom group.

When the chief complaint information and the electronic medical record information of the patient are input from the first specific unit 132, the second specific unit 133 refers to the first medical examination record DB 122a, and the number of patients is higher based on the input main complaint information. Calculate the score of the disease candidate. The second specific unit 133, for example, when the chief complaint information is "headache" and "has a fever", the number of symptoms matching "headache" and "fever" is determined by the disease of the first medical examination result DB122a. Calculate for each name, that is, for each symptom candidate. In addition, the second specific unit 133 calculates the score corresponding to the age and gender of the patient based on the electronic medical record information of the patient. The second specific unit 133 calculates the score of the disease candidate by multiplying each score of the symptom matching number, the coefficient, the age, and the gender. The second specific unit 133 stores the calculated score of the disease candidate in the score table 123b of the score storage unit 123.

When the score of the disease candidate is stored in the score table 123b, the second specific unit 133 refers to the score table 123a and the score table 123b, integrates the calculated disease candidate scores, and stores them in the disease prediction table 124. The second specific unit 133 sorts the disease prediction table 124 in descending order of points. In the example of FIG. 7, the scores are sorted from "viral ○○○" with 8 points to "chronic XX flame" (8 points) and "viral △△△" (0.6 points) in descending order. There is. If the scores are the same, the second specific unit 133 refers to, for example, the first medical examination record DB122a, and ranks the disease candidates with a large number of patients at the top. In addition, the second specific unit 133 extracts the symptom of each disease candidate from the symptom DB 121 and stores it in the disease prediction table 124.

When the disease prediction table 124 is sorted in descending order of points, the second specific unit 133 refers to the second medical examination result DB 122b and determines the epidemic of the disease. The second specific unit 133 determines that the disease is epidemic, for example, when the ratio in the latest month (-January) is a predetermined value, for example, 15% or more. In addition, the second specific unit 133 sets the patient data of the month after the month when the ratio is a predetermined value, for example, 10% or more as the patient data after the month when the epidemic of the disease starts, going back from the latest month. The second specific unit 133 extracts patient data after the month when the epidemic of the disease starts as the third medical examination record DB 122c based on the electronic medical record of the medical examination record DB 122.

The second specific unit 133 compares the symptom DB 121 with the third medical examination result DB 122c, and extracts a symptom not present in the symptom DB 121 from the third medical examination result DB 122c. In the examples of FIGS. 2 and 5, the symptom "swelling of the foot" shown by the symptom 20a and 20b of the disease name "viral XX" is not in the symptom DB 121. The second specific unit 133 stores the extracted symptom in the “symptom in the third medical examination result DB” column of the disease prediction table 124. That is, the symptom in the "symptom in the third medical examination result DB" column corresponds to the medical examination information to be additionally interviewed. When the extracted symptom is stored in the disease prediction table 124, the second specific unit 133 outputs a generation instruction to the generation unit 134.

In other words, when there are a plurality of identified disease candidates, the second specific unit 133 determines the range to be searched from the storage unit in which the medical examination results are recorded according to the degree of epidemic of the disease candidates. In addition, the second specific unit 133 searches the medical examination results within the determined range, and identifies additional medical examination information that can further narrow down the disease from the disease candidates. That is, the second specific unit 133 identifies the disease candidate based on the disease corresponding to the searched medical examination results, and refers to the storage unit that associates the disease with the symptom group based on the response result to identify the disease candidate. , Integrate disease candidates identified based on the disease corresponding to the searched medical examination results. The second specific unit 133 identifies additional interview information that can further narrow down the disease from the integrated disease candidates. That is, the second specific unit 133 associates with the specified disease stored in the first storage unit (symptom DB 121) based on the diagnostic data that stores the symptom registered for the specified disease at a time close to the input. Identify symptoms that are not included in the symptom group.

Here, the diseases corresponding to the medical examination results are the diseases included in a predetermined range from the top among the diseases arranged in descending order of the number of medical examination results. In addition, when each of the integrated disease candidates is a specific disease, the medical examination information is divided into the symptom group associated with the specific disease stored in the storage unit (symptom DB121) associated with the disease and the symptom group. This is interview information that asks whether or not there is a symptom included in the symptom group of the examination record of a specific disease stored in the storage unit (third examination result DB122c) that is not included and records the examination result.

When the generation instruction is input from the second specific unit 133, the generation unit 134 refers to the disease prediction table 124 and determines whether or not the number of disease candidates is a predetermined number or less. The predetermined number may be, for example, two, but is not limited to this, and may be any number such as one, three or more. When the generation unit 134 determines that the number of disease candidates is less than or equal to a predetermined number, the generation unit 134 transmits the input completion information to the mobile terminal 10 via the communication unit 110 and the network N.

On the other hand, when it is determined that the number of disease candidates is not less than or equal to a predetermined number, the generation unit 134 generates inquiry information of symptoms that are not included in the chief complaint information in order from the disease candidates at the top of the disease prediction table 124. In the example of FIG. 7, interview information regarding the viral XX symptoms "abdominal pain" and "swelling of the legs" is generated. In this case, the generation unit 134 generates interview information such as "Does your stomach hurt?" Or "Which part of your stomach does it hurt?" For the symptom "abdominal pain". In addition, the generation unit 134 generates interview information such as "Is there swelling of the legs?" For the symptom "swelling of the legs". The generation unit 134 transmits the generated inquiry information to the mobile terminal 10 via the communication unit 110 and the network N.

In other words, the generation unit 134 is an example of a transmission unit that transmits the specified additional inquiry information to the mobile terminal 10 which is an information processing terminal. That is, the generation unit 134 generates a question as to whether or not there is a specified symptom, and requests an answer to the question. That is, the generation unit 134 is an example of the generation unit and the request unit.

Here, the interview screen will be described with reference to FIGS. 9 to 11. FIG. 9 is a diagram showing an example of the interview screen. The inquiry screen shown in FIG. 9 is an example of an inquiry screen that accepts input of chief complaint information on the mobile terminal 10. The mobile terminal 10 prompts the patient to input the chief complaint as shown in the message 21. The patient, for example, operates the mobile terminal 10 to input the chief complaint as shown in the message 22. The message may be displayed and the input may be received by the display unit with a touch panel, or may be input / output by voice.

FIG. 10 is a diagram showing another example of the interview screen. The interview screen shown in FIG. 10 asks the question "Does your stomach hurt?" About the symptoms related to "abdominal pain" that were not included in the initial complaint information, and the interview after the patient inputs "pain". This is an example of the screen. The mobile terminal 10 displays the body 23 and the message 24 to the patient to prompt the patient to input the painful place. For example, the patient operates the mobile terminal 10 to input a painful place as shown in the place 25. In this case, the complaint information will include information such as "left lower abdominal pain".

FIG. 11 is a diagram showing another example of the interview screen. The interview screen shown in FIG. 11 is a symptom “swelling of the legs” which is a symptom that was not included in the second initial complaint information after the main complaint that “abdominal pain” was input in the interview screen shown in FIG. This is an example of an inquiry screen related to. The mobile terminal 10 displays a message 26 to the patient and prompts the patient to input whether or not the foot is swollen. The patient, for example, operates the mobile terminal 10 and inputs "yes". In this case, the complaint information will include information such as "swelling of the legs". When the patient inputs that the stomach does not hurt on the interview screen of FIG. 10, the generation unit 134 refers to, for example, the symptom column of "chronic XX inflammation" in the second row of the disease prediction table 124. , Send interview information asking questions about the presence or absence of "vomiting" not included in the initial complaint information. In this case, "viral ○○○" is excluded from the disease candidates. Alternatively, "viral XX" will move to the lower side of the disease prediction table 124.

Next, the operation of the information processing apparatus 100 of the embodiment will be described. FIG. 12 is a flowchart showing an example of the interview support process of the embodiment.

The reception unit 131 receives the patient identification information and the clinical department information from the mobile terminal 10 (step S1). The reception unit 131 acquires the patient's electronic medical record information from the medical examination record DB 122 that stores the electronic medical record, based on the received patient identification information. The reception unit 131 transmits the electronic medical record information of the patient and the questionnaire information corresponding to the received clinical department information to the mobile terminal 10 (step S2).

The reception unit 131 receives the chief complaint information from the mobile terminal 10 (step S3). The reception unit 131 outputs the received chief complaint information and the patient's electronic medical record information to the first specific unit 132.

When the chief complaint information and the electronic medical record information of the patient are input from the reception unit 131, the first specific unit 132 refers to the symptom DB 121 and calculates the score of the disease candidate based on the chief complaint information (step S4). That is, the first specific unit 132 calculates the score of the disease candidate by multiplying each score of the symptom matching number, the coefficient, the age, and the gender. The first specific unit 132 stores the calculated score of the disease candidate in the score table 123a of the score storage unit 123. When the score of the disease candidate is stored in the score table 123a, the first specific unit 132 outputs the chief complaint information and the electronic medical record information of the patient to the second specific unit 133.

When the main complaint information and the electronic chart information of the patient are input from the first specific unit 132, the second specific unit 133 refers to the first medical examination result DB 122a, and based on the main complaint information, the disease candidate having the highest number of patients The score is calculated (step S5). That is, the second specific unit 133 calculates the score of the disease candidate by multiplying each score of the symptom matching number, the coefficient, the age, and the gender. The second specific unit 133 stores the calculated score of the disease candidate in the score table 123b of the score storage unit 123.

The second specific unit 133 refers to the score table 123a and the score table 123b, integrates the calculated disease candidate scores, stores them in the disease prediction table 124, and sorts them in descending order of the scores (step S6).

When the disease prediction table 124 is sorted in descending order of points, the second specific unit 133 refers to the second medical examination result DB 122b and determines the epidemic of the disease (step S7). The second specific unit 133 extracts patient data after the month when the outbreak of the disease starts as the third medical examination record DB 122c based on the electronic medical record of the medical examination record DB 122 (step S8).

The second specific unit 133 compares the symptom DB 121 with the third medical examination result DB 122c, and extracts a symptom not present in the symptom DB 121 from the third medical examination result DB 122c. The second specific unit 133 stores the extracted symptom in the “symptom in the third medical examination result DB” column of the disease prediction table 124 (step S9). When the extracted symptom is stored in the disease prediction table 124, the second specific unit 133 outputs a generation instruction to the generation unit 134.

When the generation instruction is input from the second specific unit 133, the generation unit 134 refers to the disease prediction table 124 and determines whether or not the number of disease candidates is a predetermined number or less (step S10). When the generation unit 134 determines that the number of disease candidates is not less than a predetermined number (step S10: negative), the generation unit 134 generates inquiry information of symptoms not included in the chief complaint information in order from the top disease candidates in the disease prediction table 124 (step S11). .. The generation unit 134 transmits the generated interview information to the mobile terminal 10 (step S12), and returns to step S3.

When the generation unit 134 determines that the number of disease candidates is less than or equal to a predetermined number (step S10: affirmative), the generation unit 134 transmits the input completion information to the mobile terminal 10 (step S13), and ends the interview support process. Thereby, the information processing apparatus 100 can support the input of the symptom according to the epidemic of the disease. In addition, the information processing device 100 can suppress omission of entry in the questionnaire and contribute to highly accurate medical examination. In addition, since the information processing device 100 can confirm the presence or absence of symptoms that occur only in a specific area or season, it is possible to conduct a more accurate interview.

In this way, the information processing device 100 receives the answer result to the predetermined inquiry from the mobile terminal 10 which is the information processing terminal. In addition, the information processing device 100 identifies a disease candidate based on the received response result. Further, when there are a plurality of specified disease candidates, the information processing device 100 determines a range to be searched from the storage unit in which the medical examination results are recorded according to the degree of epidemic of the disease candidates. In addition, the information processing apparatus 100 searches the medical examination results within the determined range, and specifies additional medical examination information that can further narrow down the disease from the disease candidates. Further, the information processing device 100 transmits the specified additional inquiry information to the mobile terminal 10 which is an information processing terminal. As a result, the information processing apparatus 100 can support the input of symptoms according to the epidemic of the disease.

In addition, the information processing device 100 identifies a disease candidate by referring to a storage unit that associates the disease with the symptom group. In addition, the information processing apparatus 100 identifies disease candidates based on the diseases corresponding to the searched medical examination results. In addition, the information processing device 100 selects a disease candidate identified by referring to a storage unit that associates a disease and a symptom group based on the response result, and a disease candidate identified based on the disease corresponding to the searched medical examination results. Integrate. In addition, the information processing device 100 identifies additional interview information that can further narrow down the disease from the integrated disease candidates. As a result, the information processing apparatus 100 can support the input of symptoms by reflecting the medical examination results.

Further, in the information processing apparatus 100, the diseases corresponding to the medical examination results are diseases included in a predetermined range from the top among the diseases arranged in descending order of the number of medical examination results. As a result, the information processing apparatus 100 can support the input of symptoms by reflecting the medical examination results.

Further, in the information processing apparatus 100, when each of the integrated disease candidates is a specific disease, the medical examination information is the symptom associated with the specific disease stored in the storage unit in which the disease and the symptom group are associated. This is interview information that asks whether or not there is a symptom included in the symptom group of the diagnosis record of a specific disease stored in the memory unit that records the diagnosis result, which is not included in the group. As a result, the information processing apparatus 100 can confirm the presence or absence of symptoms that occur only in a specific area or season, so that it is possible to conduct a more accurate interview.

Further, the information processing device 100 accepts input of information for identifying one or a plurality of symptoms. Further, the information processing apparatus 100 refers to a first storage unit that stores the correspondence between the disease and the symptom group, and corresponds to the symptom group most correlated with one or a plurality of symptoms specified by the input information. Identify the attached disease. Further, the information processing apparatus 100 sets the symptom group associated with the specified disease stored in the first storage unit based on the diagnostic data for storing the symptom registered for the specified disease at a time close to the input. Identify symptoms that are not included. The information processing apparatus 100 also generates a question as to whether or not there is a specified symptom. Further, the information processing apparatus 100 requests an answer to the question. As a result, the information processing apparatus 100 can estimate the disease according to the epidemic of the disease.

In the above embodiment, the coefficient of the score storage unit 123 is the same in the score table 123a and the score table 123b, but the coefficient is not limited to this. For example, in the score table 123a and the score table 123b, different coefficients may be used for each disease. For example, when the disease "viral XX" is prevalent in a certain area, the coefficient of the disease "viral XX" may be larger than the coefficient of other diseases.

Further, each component of each of the illustrated parts does not necessarily have to be physically configured as shown in the figure. That is, the specific form of distribution / integration of each part is not limited to the one shown in the figure, and all or part of it is functionally or physically distributed / integrated in any unit according to various loads and usage conditions. Can be configured. For example, the second specific unit 133 and the generation unit 134 may be integrated. Further, the illustrated processes are not limited to the above order, and may be performed simultaneously or in a different order as long as the processing contents do not contradict each other.

Further, the various processing functions performed by each device may be executed in whole or in any part on the CPU (or a microcomputer such as an MPU or a MCU (Micro Controller Unit)). In addition, various processing functions may be executed in whole or in any part on a program analyzed and executed by a CPU (or a microcomputer such as an MPU or MCU) or on hardware by wired logic. Needless to say, it's good.

By the way, various processes described in each of the above embodiments can be realized by executing a program prepared in advance on a computer. Therefore, in the following, an example of a computer that executes a program having the same functions as those in each of the above embodiments will be described. FIG. 13 is a diagram showing an example of a computer that executes an interview support program or a disease estimation program.

As shown in FIG. 13, the computer 200 includes a CPU 201 that executes various arithmetic processes, an input device 202 that accepts data input, and a monitor 203. Further, the computer 200 includes a medium reading device 204 for reading a program or the like from a storage medium, an interface device 205 for connecting to various devices, and a communication device 206 for connecting to another information processing device or the like by wire or wirelessly. Has. Further, the computer 200 has a RAM 207 that temporarily stores various information and a hard disk device 208. Further, each of the devices 201 to 208 is connected to the bus 209.

The hard disk device 208 stores an interview support program or a disease estimation program having the same functions as the processing units of the reception unit 131, the first specific unit 132, the second specific unit 133, and the generation unit 134 shown in FIG. NS. Further, the hard disk device 208 stores a symptom DB 121, a medical examination record DB 122, a score storage unit 123, a disease prediction table 124, a questionnaire storage unit 125, and various data for realizing a medical examination support program or a disease estimation program. NS. The input device 202 receives input of various information such as operation information from the administrator of the computer 200, for example. The monitor 203 displays various screens such as an output screen to the administrator of the computer 200, for example. For example, a printing device or the like is connected to the interface device 205. For example, the communication device 206 has the same function as the communication unit 110 shown in FIG. 1 and is connected to the network N to exchange various information with the mobile terminal 10.

The CPU 201 performs various processes by reading out each program stored in the hard disk device 208, expanding the program in the RAM 207, and executing the program. Further, these programs can make the computer 200 function as the reception unit 131, the first specific unit 132, the second specific unit 133, and the generation unit 134 shown in FIG.

The above-mentioned interview support program or disease estimation program does not necessarily have to be stored in the hard disk device 208. For example, the computer 200 may read and execute a program stored in a storage medium that can be read by the computer 200. The storage medium that can be read by the computer 200 is, for example, a portable recording medium such as a CD-ROM, a DVD (Digital Versatile Disc), or a USB (Universal Serial Bus) memory, a semiconductor memory such as a flash memory, a hard disk drive, or the like. .. Further, even if the inquiry support program or the disease estimation program is stored in a device connected to a public line, the Internet, a LAN, etc., and the computer 200 reads the inquiry support program or the disease estimation program from these and executes the program. good.

1 Questionnaire support system 10 Mobile terminal 100 Information processing device 110 Communication unit 120 Storage unit 121 Symptom DB
122 Medical examination record DB
122a 1st medical examination record DB
122b Second medical examination record DB
122c 3rd medical examination record DB
123 Score storage unit 124 Disease prediction table 125 Questionnaire storage unit 130 Control unit 131 Reception unit 132 1st specific unit 133 2nd specific unit 134 Generation unit N network

Claims (9)

Receive the answer result to the predetermined interview from the information processing terminal,
Based on the received response results, identify disease candidates and
When there are a plurality of identified disease candidates, the range to be searched from the storage unit in which the medical examination results are recorded is determined according to the degree of epidemic of the disease candidates, and the medical examination results are searched within the determined range. , Identify additional interview information that can further narrow down the disease from the disease candidates,
The specified additional interview information is transmitted to the information processing terminal.
An interview support program characterized by having a computer execute processing. In the process of identifying the disease candidate, the disease candidate is specified by referring to the storage unit that associates the disease with the symptom group.
In the process of specifying the interview information, a disease candidate is specified based on the disease corresponding to the searched medical examination results, and the disease is specified by referring to the storage unit associated with the disease and the symptom group based on the answer result. The disease candidates and the disease candidates identified based on the diseases corresponding to the searched results of the medical examinations are integrated, and additional interview information that can further narrow down the diseases from the integrated disease candidates is provided. Identify,
The interview support program according to claim 1, wherein the interview support program is characterized in that. The diseases corresponding to the medical examination results are diseases included in a predetermined range from the top among the diseases arranged in descending order of the number of medical examination results.
The interview support program according to claim 2, characterized in that. When each of the integrated disease candidates is a specific disease, the medical examination information is not included in the symptom group associated with the specific disease stored in the storage unit associated with the disease and the symptom group. , Questionnaire information asking whether or not there is a symptom included in the symptom group of the medical examination record of the specific disease stored in the storage unit in which the medical examination result is recorded.
The interview support program according to claim 2 or 3, characterized in that. Accepts input of information that identifies one or more symptoms,
With reference to the first storage unit that stores the correspondence between the disease and the symptom group, the disease associated with the symptom group most correlated with the one or more symptoms specified by the input information is identified. death,
Symptoms that are not included in the symptom group associated with the specified disease stored in the first storage unit based on the diagnostic data that stores the symptoms registered for the disease identified at a time close to the input. Identify and
Generate a question about whether you have the identified symptoms and
Request an answer to the above question,
A disease estimation program characterized by having a computer perform processing. Receive the answer result to the predetermined interview from the information processing terminal,
Based on the received response results, identify disease candidates and
When there are a plurality of identified disease candidates, the range to be searched from the storage unit in which the medical examination results are recorded is determined according to the degree of epidemic of the disease candidates, and the medical examination results are searched within the determined range. , Identify additional interview information that can further narrow down the disease from the disease candidates,
The specified additional inquiry information is transmitted to the information processing terminal.
An interview support method characterized in that a computer executes processing. Accepts input of information that identifies one or more symptoms,
With reference to the first storage unit that stores the correspondence between the disease and the symptom group, the disease associated with the symptom group most correlated with the one or more symptoms specified by the input information is identified. death,
Symptoms that are not included in the symptom group associated with the specified disease stored in the first storage unit based on the diagnostic data that stores the symptoms registered for the disease identified at a time close to the input. Identify and
Generate a question about whether you have the identified symptoms and
Request an answer to the above question,
A disease estimation method characterized by a computer performing processing. A receiver that receives the answer results to a predetermined inquiry from the information processing terminal, and
Based on the received answer result, the first specific part that identifies the disease candidate and
When there are a plurality of identified disease candidates, the range to be searched from the storage unit in which the medical examination results are recorded is determined according to the degree of epidemic of the disease candidates, and the medical examination results are searched within the determined range. , The second specific part that identifies additional medical examination information that can further narrow down the disease from the disease candidates,
A transmitter that transmits the specified additional interview information to the information processing terminal, and
An information processing device characterized by having. A reception desk that accepts input of information that identifies one or more symptoms,
With reference to the first storage unit that stores the correspondence between the disease and the symptom group, the disease associated with the symptom group most correlated with the one or more symptoms specified by the input information is identified. The first specific part to do and
Based on the diagnostic data that stores the symptom registered for the disease identified at a time close to the input, it is included in the symptom group associated with the identified disease stored in the first storage unit. The second specific part that identifies no symptoms and
A generator that generates a question about whether or not there is the identified symptom,
The request section requesting an answer to the above question,
An information processing device characterized by having.

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