JP2006059149A - Disease name estimation apparatus and disease name estimation program - Google Patents

Abstract

<P>PROBLEM TO BE SOLVED: To provide a disease name estimation apparatus and a disease name estimation program capable of accurately estimating a disease name of an examined patient. <P>SOLUTION: This apparatus comprises a medical history master 161 storing information for medical histories of a plurality of patients; a first disease name estimation part 110 estimating a disease name of the examined patient based on chief complaint, symptom and specimen examination information of the examined patient; a first family disease name acquisition part 120 acquiring disease names of the family of the examined patient from the information stored in the medical history master 161; a second disease name estimation part 130 estimating a disease name of the examined patient based on the disease names acquired by the first acquisition part 120; and a disease name display part 150 displaying both the disease name estimated by the first estimation part 110 and the disease name estimated by the second estimation part 130. <P>COPYRIGHT: (C)2006,JPO&NCIPI

Description

  The present invention relates to a disease name estimation apparatus and a disease name estimation program for estimating a disease name of a patient to be used, which is used in an electronic medical record system in a hospital or the like.

  Electronic medical record systems using computers have become widely used in hospitals and clinics, and are contributing to the improvement of medical care. However, highly accurate disease name estimation technology that is the basis of this electronic medical record system has not yet been established, and in many cases, doctors estimate disease names based on information such as chief complaints / symptoms and sample test results.

A disease name estimation method applying a so-called knowledge base to this electronic medical record system has also been proposed.For example, the estimated disease name and necessary test items are registered based on the chief complaint / symptom, and the specimen test result based on the test order issued by the doctor A disease name estimation system is disclosed in which an estimated disease name is judged and registered based on the above, the estimated disease name from the chief complaint / symptom is matched with the estimated disease name from the specimen test result, and the matched disease name is displayed as the estimated disease name (for example, , See Patent Document 1).
JP-A-8-263568 (page 2-3, FIGS. 1 and 2)

  However, the above disease name estimation system estimates the disease name from the main complaint / symptoms and sample test results. Depending on the patient, the name of the disease cannot be accurately estimated from only the main complaint / symptoms and sample test results. There is.

  In view of the above circumstances, an object of the present invention is to provide a disease name estimation device and a disease name estimation program capable of accurately estimating the disease name of a patient to be examined.

The disease name estimation apparatus of the present invention that solves the above problems is as follows.
In the disease name estimation device that estimates the disease name of the patient being examined,
A medical history master that stores information about the medical history of multiple patients;
A first disease name estimation unit for estimating a disease name of the patient to be examined based on the main complaint / symptoms and sample examination information of the patient to be examined;
A first family disease name acquisition unit for acquiring a disease name of the family of the patient to be examined from the information stored in the medical history master;
A second disease name estimation unit that estimates the disease name of the patient to be examined based on the disease name acquired by the first family disease name acquisition unit;
And a disease name display unit for displaying the disease name estimated by the first disease name estimation unit and the disease name estimated by the second disease name estimation unit.

  According to the disease name estimation apparatus of the present invention, the disease name is estimated (first disease name estimation unit) based on the main complaint / symptoms and sample test information of the patient being examined, and the disease name of the family of the patient being examined is acquired (first family disease name) Acquisition unit), so as to estimate the disease name of the patient to be consulted based on the acquired disease name of the family (second disease name estimation unit), and to display the disease name estimated by these two disease name estimation units together to the doctor Therefore, the doctor can make a highly accurate diagnosis by taking into account not only the main complaint / symptoms and specimen test information of the patient being examined, but also the medical history of the family of the patient being examined.

  In addition, the “family of the patient” referred to in the present invention refers to a related family, and unrelated persons such as spouses and adopted children are not included in the “family”. The same applies to the following.

Here, a second family disease name acquisition unit for acquiring a disease name of the family of the patient to be examined based on the inquiry information obtained from the patient to be examined,
The second disease name estimation unit estimates the disease name of the patient to be examined based on the disease name acquired by the first family disease name acquisition unit and the disease name acquired by the second family disease name acquisition unit. May be.

  When the disease name estimation device of the present invention is configured as described above, it is possible to estimate the disease name more accurately because it is possible to obtain the disease name of the family based on the inquiry information obtained from the consulted patient and to take this information into account. can do.

The second disease name estimation unit
In response to the update of the information related to the medical history of the family of the medical patient in the medical history master, the disease name of the medical patient may be re-estimated based on the updated information.

  When the disease name estimation apparatus of the present invention is configured as described above, when the diagnosis of the patient being examined is confirmed and the medical history master is updated, the diagnosis information of the family of the patient being examined can be reviewed based on the updated information. Therefore, a more accurate disease name estimation apparatus can be obtained.

In addition, the disease name estimation program of the present invention that solves the above problems is
Computer
A first disease name estimating unit for estimating a name of a disease of the consulted patient based on the main complaint / symptoms and sample test information of the consulted patient;
A first family disease name acquisition unit for acquiring a disease name of the family of the patient to be examined from a history history master in which information on the history of a plurality of patients is stored;
A second disease name estimation unit that estimates the disease name of the patient to be examined based on the disease name acquired by the first family disease name acquisition unit;
The apparatus is operated as a disease name estimation apparatus including a disease name display unit that displays a disease name estimated by the first disease name estimation unit and a disease name estimated by the second disease name estimation unit.

  According to the disease name estimation program of the present invention, it is possible to make a highly accurate diagnosis by taking into account not only the main complaint / symptoms and sample examination information of the patient being examined, but also the medical history of the family of the patient being examined. It is possible to easily form a disease name estimation device capable of performing on a computer.

Here, a second family disease name acquisition unit for acquiring a disease name of the family of the patient to be examined based on the inquiry information obtained from the patient to be examined,
The second disease name estimation unit estimates the disease name of the patient to be examined based on the disease name acquired by the first family disease name acquisition unit and the disease name acquired by the second family disease name acquisition unit. May be.

  When the disease name estimation program of the present invention is configured as described above, since the disease name estimated by the above two disease name estimation units is displayed to the doctor together, the doctor can display the main complaint / symptoms and specimen of the patient being examined. It is possible to easily form on a computer a disease name estimation device capable of making a highly accurate diagnosis in consideration of not only the examination information but also the medical history of the family of the patient being examined.

  In addition, the second disease name estimation unit re-estimates the disease name of the examined patient based on the updated information in response to the update of the information related to the medical history of the family of the examined patient in the history history master. It may be what performs.

  When the disease name estimation program of the present invention is configured as described above, the diagnosis information of the family of the patient being examined can be reviewed based on the updated information when the diagnosis of the patient being examined is confirmed and the medical history master is updated. Therefore, a more accurate disease name estimation device can be easily formed on a computer.

  As described above, according to the disease name estimation device and the disease name estimation program of the present invention, since the disease name is estimated by taking into account information on the family medical history, the disease name that can accurately estimate the disease name of the patient being examined An estimation device and a disease name estimation program can be realized.

  Embodiments of the present invention will be described below with reference to the drawings.

  FIG. 1 is a schematic configuration diagram showing an embodiment of a disease name estimation apparatus and a disease name estimation program of the present invention.

  As shown in FIG. 1, the disease name estimation apparatus 100 of the present embodiment includes a first disease name estimation unit 110, a first family disease name acquisition unit 120, a second disease name estimation unit 130, and a second family disease name acquisition unit 140. A disease name display unit 150 and a database 160 including a medical history master 161.

  The first disease name estimation unit 110 estimates the disease name of the consulted patient based on the main complaint / symptom of the consulted patient and the sample test information.

  The first family disease name acquisition unit 120 acquires the disease name of the family of the patient being examined from the information stored in the medical history master 161.

  The second disease name estimation unit 130 estimates the disease name of the patient to be examined based on the disease name acquired by the first family disease name acquisition unit 120.

  The disease name display unit 150 displays the disease name estimated by the first disease name estimation unit 110 and the disease name estimated by the second disease name estimation unit 130 together.

  The second family disease name acquisition unit 140 acquires the disease name of the family of the patient being examined based on the inquiry information obtained from the patient being examined. When the second family disease name acquisition unit 140 is provided, The second disease name estimation unit 130 is configured to estimate the disease name of the patient to be examined based on the disease name acquired by the first family disease name acquisition unit 120 and the disease name acquired by the second family disease name acquisition unit 140. Yes.

  Further, in the present embodiment, the second disease name estimation unit 130 receives the updated information on the medical history of the family of the patient to be examined in the medical history master 161, and based on the updated information, It is configured to perform re-estimation.

  The database 160 includes a medical history master 161 that stores information related to the medical history of a plurality of patients, a patient master 162 that stores patient information such as patient ID, name, sex, date of birth, and address of the patient being consulted, It is composed of a family information master 163 that stores the relationship with the family and a family history master 164 that stores the medical history of the family of the patient being examined.

  Further, as shown in FIG. 1, the disease name estimation program 180 of the present embodiment includes a first disease name estimation unit 110, a first family disease name acquisition unit 120, a second disease name estimation unit 130, and a second family disease name acquisition. Unit 140 and disease name display unit 150.

  The disease name estimation program 180 is formed on a main storage device of a computer system described below, and is executed by the CPU.

  Next, the hardware of the disease name estimation apparatus of this embodiment will be described.

  FIG. 2 is a schematic diagram of a computer system in which a disease name estimation apparatus and a disease name estimation program according to this embodiment are formed.

  In FIG. 2, the disease name estimation apparatus 100 shown in FIG. 1, the server 80 on which the database 160 including the medical history master 161 is constructed, and a plurality of terminal devices 80_1, 80_2 connected to the server 80 via the network 86 are shown. 80_3 is exemplarily shown.

  As a computer system that constitutes the server 80 and the terminal devices 80_1, 80_2, and 80_3, a high-speed and large-capacity computer system generally called a workstation, a personal computer system, or the like is used.

  The server 80 and each of the terminal devices 80_1, 80_2, and 80_3 are connected to the main units 80a, 80b, 80c, and 80d, and the main units 80a, 80b, 80c, and 80d in which a CPU, a main storage device, a hard disk, a communication board, and the like are built. Keyboards 82a, 82b, 82c for inputting instructions from the operators to the display devices 81a, 81b, 81c, 81d, the server 80 and the terminal devices 80_1, 80_2, 80_3 that display images and character strings on the screen according to the instructions. The mouse 83a, 83b, 83c, and 83d is provided for inputting an instruction corresponding to the icon or the like displayed at the designated position by designating an arbitrary position on the display screen.

  The server 80, the terminal devices 80_1, 80_2, and 80_3, and the network 86 form the disease name estimation device 100 (see FIG. 1) of the present embodiment as a whole.

  The main body portions 80a, 80b, 80c, 80d are further provided with FD loading ports 84a, 84b, 84c, 84d, MO loading ports 85a, 85b, which are loaded with flexible disks (not shown) and MO (magneto-optical disks) 85, respectively. 85c and 85d, and a flexible disk drive unit and an MO drive unit for driving and accessing the flexible disk loaded from these loading ports and the MO are built in the inside.

  Next, the file structure of each master constituting the database 160 in the disease name estimation apparatus of this embodiment will be described.

  FIG. 3 is a diagram showing a file structure of the medical history master in the present embodiment.

  As shown in FIG. 3, the medical history master 161 includes a patient ID 161a, a data storage number 161b, a diagnosis date (1) 161c, a disease name CD (1) 161d, a diagnosis date (2) 161e, a disease name CD (2) 161f, Patients with diagnosis date (3) 161g, disease name CD (3) 161h, diagnosis date (4) 161i, disease name CD (4) 161j, etc. The medical history, that is, the date of diagnosis and the disease name CD (code) are stored for each patient ID. For example, in the first record 161_1, the medical history of the patient ID: “321879” (father of the patient to be examined), and in the second record 161_2, the medical history of the patient ID: “2588741” (mother of the patient to be examined), the third In the record 161_3, the medical history of the patient ID: “731586” (the mother father of the consulted patient) is stored.

  FIG. 4 is a diagram showing the file structure of the patient master in this embodiment.

  As shown in FIG. 4, the patient master 162 includes items such as a patient ID 162a, a Kana name 162b, a name 162c, a gender 162d, a date of birth 162e, an address 162f, an insurance information 162g,. Various types of information related to patients who have received medical care at a hospital are stored. For example, the patient ID of the patient to be examined: “123456”, the name of Kana: “Jiro Yamada”, the name: “Jiro Yamada”, etc. are stored.

  FIG. 5 is a diagram showing a file structure of the family information master in the present embodiment.

  As shown in FIG. 5, the family information master 163 includes a patient ID 163a, a data storage number 163b, a relationship CD (1) 163c, a patient ID (1) 163d, a relationship CD (2) 163e, and a patient ID (2) 163f. , Relationship CD (3) 163g, patient ID (3) 163h, relationship CD (4) 163i, patient ID (4) 163j,... Is remembered. The family information master 163 shown in FIG. 5 stores the family information of the four patients who have been examined (patient ID: “123456”).

  FIG. 6 is a diagram showing a file structure of the family history master in the present embodiment.

  As shown in FIG. 6, the family history master 164 includes a patient ID 164a, a related pattern CD (1) 164b, a disease name CD (1) 164c, a related pattern CD (2) 164d, a disease name CD (2) 164e, a related pattern CD (3 164 f, disease name CD (3) 164 g, etc., and the ID of the patient being examined: “123456” and the family's medical history such as father-stomach cancer, mother-diabetes, mother-gout, etc. are stored.

  In the present embodiment, the following auxiliary master is also used in addition to the above four basic masters.

  FIG. 7 is a diagram showing the file structure of the relationship master in this embodiment.

  As shown in FIG. 7, the relationship master 171 stores a relationship CD (code) 171 a, for example, “01” and its relationship name 171 b: “Father”.

  FIG. 8 is a diagram showing a file structure of a disease name master in the present embodiment.

  As shown in FIG. 8, the disease name master 172 stores a disease name CD (code) 172a, for example, “605003”, the disease name 172b :: “diabetes”, and a heritability flag 172c: “1”.

  Here, as the heritability flag 172c, “1” is stored when the disease name is heritable, and “0” is stored when the disease name is not heritable. . The function of the heritability flag 172c will be described later.

  FIG. 9 is a diagram showing a file structure of the inspection item master in the present embodiment.

  As shown in FIG. 9, the inspection item master 173 stores an inspection item CD (code) 173a, an inspection item name 173b, a normal value lower limit 173c, and a normal value upper limit 173d. For example, inspection item CD: “01001”, inspection item name: “GOT” normal value lower limit: “8” and normal value upper limit: “38” means that the inspection value of “GOT” is “8 or more, 38 or less” If it is within the range, it means that the “GOT” test value of this patient is normal.

  FIG. 10 is a diagram showing a file structure of the estimated disease name master in the present embodiment.

  As shown in FIG. 10, the estimated disease name master 174 is provided with items of a test item CD (code) 174a, a non-upper limit estimated disease name 174b, and a non-lower limit estimated disease name 174c. Below, disease name CD (1) 174b_1, disease name CD (2) 174b_2, disease name CD (3) 174b_3, disease name CD (4) 174b_4, disease name CD (5) 174b_5, ... Below, disease name CD (1) 174c_1, disease name CD (2) 174c_2, disease name CD (3) 174c_3, disease name CD (4) 174c_4, disease name CD (5) 174c_5, ... are provided.

  Here, in the first record 174_1, when the test value of the test item CD: “01001” is outside the upper limit of the normal value (see FIG. 9), the disease name CD is “145833”, “236714”, or “567376”. This means that there is a high possibility that either of them is high, and when the test value of the test item CD: “01001” deviates from the lower limit of the normal value, the disease name CD: “268902” is high.

  FIG. 11 is a diagram showing a file structure of the main complaint / symptom-specific estimated disease name master in the present embodiment.

  As shown in FIG. 11, the main complaint / symptom-specific estimated disease name master 175 includes key information 175a that is basic information on the patient's main complaint / symptom and an estimated disease name that indicates an estimated disease name code estimated from the key information. There are two items of 175b. Below the key information 175a, there are a part 175a_1, a place 175a_2, a 175a_3, a pain 175a_4, a nausea 175a_5, a fever 175a_6, seven items of jaundice 175a_7, and a presumed disease name 175b. , Disease name CD (1) 175b_1, disease name CD (2) 175b_2, disease name CD (3) 175b_3, disease name CD (4) 175b_4, disease name CD (5) 175b_5 are provided. The details of the chief / symptom-specific estimated disease name master 175 will be described later.

  Next, operations of the disease name estimation apparatus 100 and the disease name estimation program 180 of this embodiment will be described.

  FIG. 12 is a flowchart showing the operation of the disease name estimation apparatus and the disease name estimation program of this embodiment.

  As shown in FIG. 12, this disease name estimation apparatus and disease name estimation program includes a patient-specific main complaint / symptom input screen display and data input (S01), a patient-specific main complaint / symptom input data registration (S02), and a family information input screen. Display and data input (S03), specimen test result acquisition (S04), family history acquisition / editing (S05), disease name estimation / display processing (S06), doctor's diagnostic information input (S07), disease name diagnosis re- It consists of seven steps of calculation processing (S08). Among these, the first stage of disease name estimation unit 110 (see FIG. 1), the first stage of family disease name according to the present invention is a two-stage process of acquiring / editing family history (S05) and disease name estimation / display processing (S06). It corresponds to the acquisition unit 120, the second disease name estimation unit 130, the second family disease name acquisition unit 140, and the disease name display unit 150.

  As shown in FIG. 12, the main complaint / symptom input screen and data input are first performed by the user (step S01).

  FIG. 13 is a diagram showing a chief complaint / symptom input screen in the present embodiment.

  As shown in FIG. 13, the main complaint / symptom input screen 200 includes a patient ID input area 200a, a part input area 200b, a part input area 200c, an input area 200d, a pain input area 200e, a nausea input area 200f, fever An input area 200g, a jaundice input area 200h, a next button 200i, and a registration button 200j are provided.

  In general, in a relatively large hospital, when a patient is a first visit, a pre-examination is often performed prior to a doctor's examination. In such a case, the inquiry information is created by the patient to be filled in a predetermined questionnaire or the like by a nurse or the like.

  When the user inputs the patient ID of the patient to be examined such as “123456” in the patient ID input area 200a of the main complaint / symptom input screen 200 based on the inquiry information thus created, the patient master shown in FIG. 162, when there is a record whose patient ID is “123456” in the patient master 162, patient information is displayed in the patient ID input area 200a after “123456” as shown in the figure. If there is no record of the patient ID “123456” in the patient master 162, the patient information is input like “123456” followed by “Jiro Yamada 36 years old 1967/10/01 student”. The patient information is added to the patient master 162 as a new record.

  Next, “8” (belly) in the site input area 200b, “1” (center) in the site input area 200c, “4” (1 W before) in the input area 200d, and “1” (in the pain input area 200e) The chief complaint / symptom data is input as follows.

  When the registration button 200j is pressed after the user completes the input of the main complaint / symptom data, the main complaint / symptom data input so far is registered in the main complaint / symptom data file 210 shown in FIG. 14 (FIG. 12: Step S02).

  FIG. 14 is a diagram showing the structure of the main complaint / symptom data file in the present embodiment.

  As shown in FIG. 14, the main complaint / symptom data file 210 is provided with the following items: patient ID 210a, site 210b, site 210c, from 210d, pain 210e, nausea 210f, fever 210g, jaundice 210h, “123456”, “8”, “1”, “4”, “1”, “1”, “2”, “2” entered on the main complaint / symptom input screen 200 (see FIG. 13) are stored. Has been.

  When the next button 200i is pressed on the main complaint / symptom input screen 200 shown in FIG. 13, the family information input screen and data input shown in FIG. 15 are displayed (FIG. 12: step S03).

  FIG. 15 is a diagram showing a family information input screen in the present embodiment.

  As shown in FIG. 15, this family information input screen 220 is provided with a patient ID input area 220a, a family information input area 220b, and a registration button 220c.

  The family information input area 220b is provided with family relationship input areas 220b_1, 220b_3, 220b_5, 220b_7, 220b_9 of the patient being examined and patient ID input areas 220b_2, 220b_4, 220b_6, 220b_8, 220b_10 of the family of the patient being examined. .

  Based on the above-mentioned inquiry information, the user inputs the ID information of the patient to be examined into the patient ID input area 220a, and the family ID information of the patient to be examined is input into the family information input area 220b. Here, for example, when “01” is input to the relationship input area 220b_1, the relationship master 171 shown in FIG. 7 is referred to. As a result, the relationship “Father” with the patient to be examined is displayed on the right side of the relationship input area 220b_1. Is done. Further, when the patient ID “321879” of “Father” of the patient to be examined is entered in the patient ID input area 220b_2, the patient master 162 shown in FIG. 4 is referred to, and the record of “Father” of the patient to be examined is stored in the patient master 162. Is registered, the name “Ichiro Yamada” of “Father” is read from the patient master 162 and displayed on the right side of the patient ID input area 220b_2.

  Thus, when the registration patient 220 is pressed after the family information of the patient to be examined is input to each of the relationship input areas and the patient ID input area of the family information input screen 220, the family information of the patients that have been input so far is displayed. And registered in the family information master 163 (see FIG. 5).

  Next, the specimen test result of the patient being examined is acquired and stored in the specimen test result file (see FIG. 16) (FIG. 12: step S04).

  In the case of a large hospital, in order to improve the examination efficiency, the specimen examination is generally performed before the examination by the doctor. Therefore, in this embodiment, the specimen examination result is obtained at this timing. It is.

  FIG. 16 is a diagram showing a file structure of a specimen test result file in the present embodiment.

  As shown in FIG. 16, the specimen test result file 240 includes a patient ID 240a, a test date 240b, a test result number 240c, a test item CD (1) 240d, a test result (1) 240e, and a test item CD (2) 240f. , Inspection result (2) 240g, inspection item CD (3) 240h, inspection result (3) 240i, inspection item CD (4) 240j, inspection result (4) 240k, etc. are provided. In addition, the test data by each specimen test is, for example, as shown in the figure, “123456”, “2004/6/2”, “12”, “01001”, “21.5”, “01002”, “14.8”. "," 10501 "," 86 "," 21005 "," 7.0 ", and the like.

  Next, family history is acquired and edited (FIG. 12: step S05). This family history acquisition and editing is executed by the following family history acquisition / editing subroutine.

  FIG. 17 is a flowchart of a family history acquisition / editing subroutine in the present embodiment.

  As shown in the flowchart of FIG. 17, first, the data of the family history 1 table is acquired from the inquiry information of the patient being examined (step S051).

  Acquisition of the data of this family history 1 table is performed by the inquiry (family history 1) input screen shown in FIG.

  FIG. 18 is a diagram showing an inquiry (family history 1) input screen in the present embodiment.

  As shown in FIG. 18, this inquiry (family history 1) input screen 230 is provided with a patient ID input area 230a, a family history input area 230b, a return button 230c, and a registration button 230d.

  The patient ID input area 230a displays information such as the ID, name, gender, age, date of birth, etc. of the patient who has been entered on the family information input screen 220 (see FIG. 15).

  The family history input area 230b is provided with family relationship input areas 230b_1, 230b_3, 230b_5, 230b_7, 230b_9, and disease name input areas 230b_2, 230b_4, 230b_6, 230b_8, 230b_10 of the patient being examined.

  Based on the inquiry information acquired from the consultation patient described with reference to FIG. 15, the medical history of the consultation patient's family is input one by one in the relationship input area and the disease name input area.

  For example, “Father” or the like is displayed on the right side of the relationship input area 230b_1 as in the family information input screen 220 (see FIG. 15). Further, when “101001” is input to the disease name input area 230b_2, the disease name master 172 shown in FIG. 8 is referred to, and the disease name “stomach cancer” corresponding to “101001” is read out, and is displayed on the right side in the disease name input area 230b_2. “Stomach cancer” is displayed.

  When the registration button 230d is pressed after the medical history of the patient being examined is entered in each of the relationship input areas and the disease name input area in this way, the medical history of the family of the patient being examined so far is shown in the following family It is registered in the history 1 table (see FIG. 19). If the family information itself needs to be re-input while inputting the family medical history, the user returns to the family information input screen 220 (see FIG. 15) by pressing the return button 230c and re-edits the family information. Be able to.

  FIG. 19 is a diagram showing a family history 1 table in the present embodiment.

  As shown in FIG. 19, this family history 1 table 251 includes the number of data 251a: “3”, the relationship CD (1) 251b: “01” (father), the disease name CD (1) 251c: “101001” (stomach cancer ), Relationship CD (2) 251d: "02" (mother), disease name CD (2) 251e: "605003" (diabetes), relationship CD (3) 251f: "02" (mother), disease name CD (3) 252g : “785600” (gout) is stored.

  Next, the data of the family history 2 table is acquired from the family history master (FIG. 17: step S052).

  FIG. 20 is a flowchart showing a procedure for acquiring data of the family history 2 table in the present embodiment.

  This flowchart is in the form of a subroutine. Control is transferred from step S051 of the family history acquisition / editing subroutine shown in the figure, and after completion, the process returns to step S05.

  The variables used in this flowchart will be described.

  The variable I is a variable representing the number of family information of the patient being examined, the variable K is a variable representing the number of diagnosed disease names of the family, and the variables J and L are indices for work.

  As shown in FIG. 20, first, the patient record 163_1 is read from the family information master 163 (see FIG. 3) using the patient ID of the patient being examined as a key (step S052_1), and stored in the data storage number 163b of this record 163_1. The set value “4” is set in the variable I (step S052_2).

  Next, in step S052_3, it is determined whether or not the variable I is 0, that is, the number of stored data is “0” (step S052_3). If the variable I is not 0, the process proceeds to step S052_4, but the variable I is 0. If there is, the subroutine processing is terminated.

  In step S052_4, after setting variable J to 1, it is determined whether or not variable J exceeds variable I (step S052_4).

  As a result of the determination in step S052_4, if the variable J exceeds the variable I, the processing of this subroutine is terminated.

  As a result of the determination in step S052_4, if the variable J does not exceed the variable I, the process proceeds to step S052_6, and the medical history master 161 is used with the patient ID (J) of the patient record 163_1 of the family information master 163 (see FIG. 3) as a key. (See FIG. 3) is read, and then in step S052_7, it is determined whether or not there is a record corresponding to the medical history master 161.

  If the result of determination in step S052_7 is that there is no corresponding record, processing proceeds to step S052_8, variable J is incremented, and processing returns to step S052_5.

  If the result of determination in step S052_7 is that there is a corresponding record, processing proceeds to step S052_9. Here, since the variable J is initially set to 1, the record 161_1 of the medical history master 161 (see FIG. 3) is read with the patient ID (1): “321879” of the record 163_1 of the patient being consulted as a key, The medical history of the father of the patient being examined, that is, diagnosis date (1): “2001/5/19”, disease name CD (1): “101005” is acquired. The “101005” is “cardiac stomach cancer” as stored in the record 172-6 of the disease name master 172 (see FIG. 8). In this example, the determination result in step S052_7 corresponds to the case where there is a corresponding record, so the process proceeds to step S052_9.

  In step S052_9, the value “1” stored in the data storage number 161b of the record 161_1 of the medical history master 161 (see FIG. 3) is set in the variable K.

  Next, in step S052_10, after setting the variable L to 1, it is determined whether or not the variable L exceeds the variable K (step S052_11).

  As a result of the determination in step S052_11, when the variable L exceeds the variable K, the process proceeds to step S052_8, the variable J is counted up, and the process returns to step S052_5.

  As a result of the determination in step S052_11, if the variable L does not exceed the variable K, the process proceeds to step S052_12. The relationship (I) of the record 163_1 of the consulted patient (see FIG. 3) is stored in the family history 2 table.

  Next, in step S052_13, after the variable L is counted up, the process returns to step S052_11.

  When the above processing is completed, the data of the family history 2 table of the patient to be examined is formed and stored in the following family history 2 table.

  FIG. 21 is a diagram showing a family history 2 table in the present embodiment.

  As shown in FIG. 21, the family history 2 table 252 includes the number of data 252a, the relationship CD (1) 252b, the disease name CD (1) 252c, the relationship CD (2) 252d, the disease name CD (2) 252e, and the relationship CD. (3) 252f, disease name CD (3) 252g, relationship CD (4) 252h, disease name CD (4) 252i, etc. are provided, and the number of data of the family history 2 of the patient being examined is “2”, “ The father's disease name CD: “101005” (cardiac stomach cancer), the “mother” disease name CD: “605003” (diabetes type 1), and the “brother” disease name CD: “489600” (hypertension) are stored. .

  Next, family history summary data is created from the family history 1 table 251 and the family history 2 table 252 (FIG. 17: step S053).

  In the disease name estimation apparatus of this embodiment, when creating family history summary data, the data of the family history 2 table and the data of the family history 1 table are compared to create family history summary data to be used in the subsequent processing. However, when the same information exists, the family history summary data is created with priority given to the data of the family history 2 table based on the diagnosis of the doctor.

  FIG. 22 is a diagram showing a determination rule when creating family history summary data in the present embodiment.

  As shown in FIG. 22, the determination rule 260 determines whether the family history data to be adopted for the family history summary data is the data of the family history 2 table or the data of the family history 1 table according to the relationship and the disease name classification. ing.

  The disease name classification refers to the first three digits of the six-digit disease name CD in the disease name estimation apparatus of the present embodiment. For example, the disease name classification of the disease name CD: “101001” and the disease name CD: “101005” Both of the disease name classifications are “101”.

  As shown in FIG. 22, in the case 1 where the relationship is matched and the disease name classification is the same, it is determined that the data of the family history 2 table is adopted as the family history summary data. In case 2 where the family history does not match, both family history 1 table data and family history 2 table data are determined to be adopted as family history summary data. It is stipulated that both the data in one table and the data in the family history 2 table are adopted as family history summary data.

  Next, an example of creating family history summary data using the determination rule 260 and the family history 1 table 251 (see FIG. 19) and the family history 2 table 252 (see FIG. 21) is shown below.

  FIG. 23 is a diagram showing a family history summary data creation example (1) in the present embodiment.

  In this family history summary data creation example (1), of the data of the family history 2 table, the disease name classification of the relationship CD (1) 252b: “01” (father) disease name CD (1) 252c: “101005”: “ 101 ”is compared with the disease name CD (1) 164b:“ 101001 ”in the data of the family history 1 table:“ 101 ”, and the relationship CD and the disease name category are the same. It is determined as Case 1 of the determination rule 260, and the family CD (1) and disease name CD (1): “cardiac stomach cancer” in the family history 2 table data are output as family history summary data. At the same time as this data output, it is deleted from the family history 2 table. In addition, the data of the family history 1 table that is regarded as the same data is also deleted. The state of each table after deletion is as shown in the dashed line in FIG.

  FIG. 24 is a diagram showing a family history summary data creation example (2) in the present embodiment.

  In this family history summary data creation example (2), the disease history CD (2) 252e: “605005” in the data of the family history 2 table is also stored in the family history 1 table as in the creation example (1). Disease name CD (2) 164d: Disease name category of “605003”: “605” and Disease name CD (3) 164f: Disease name category of “785600”: “785” are compared, and the disease name of the data in the family history 1 table Since the relationship CD and the disease name classification are the same for CD (2), it is determined as Case 1 of the determination rule 260 shown in FIG. 22, and the (mother) relationship CD (2) and data of the family history 2 table Disease name CD (2): “Diabetes type 1” is output as family history summary data.

  Note that the disease name CD (3) in the data of the family history 1 table is determined to be the case 2 of the determination rule 260 shown in FIG. Two table data (mother) 's relationship (CD) (3) and disease name CD (3): “gout” is output as family history summary data.

  Similarly, the disease name CD (3) 252g: “489600” of the data of the family history 2 table is compared with each disease name CD of the data of the family history 1 table, and the relationship CD is the same. Therefore, it is determined as Case 3 of the determination rule 260 shown in FIG. 22, and the relationship CD (3) and disease name CD (3) of (elder brother) in the data of the family history 2 table are output as family history summary data. These data output as family history summary data are deleted from the family history 2 table and the family history 1 table simultaneously with the data output. The state of each table after deletion is as shown in the dashed line in FIG.

  FIG. 25 is a diagram showing family history summary data in the present embodiment.

  25, the family history summary data 270 according to the creation example described with reference to FIGS. 23 and 25, that is, “father” medical history data 270a, “mother” medical history data 270b, “brother” medical history data 270c, The medical history data 270d of “Mother” is shown. Since the first three data of these medical history data are information based on the diagnosis of the doctor, “1” is added as “information classification”, and since the last fourth data is information based on the inquiry, “information” “2” is added as “Division”.

  In the disease name estimation apparatus of the present embodiment, an example of creating family history summary data based on the data of the family history 1 table and the data of the family history 2 table has been shown. However, the disease name estimation apparatus of the present invention includes: It is not necessarily limited to the mode using both the data of the family history 1 table and the data of the family history 2 table, and summary data may be created using only the data of the family history 2 table.

  When the creation of the family history summary data (FIG. 17: step S053) is completed, the process returns to the main routine shown in FIG. 12, and the disease name estimation / display process (FIG. 12: step S06) is performed.

  In step S06 of the flowchart shown in FIG. 12, disease name estimation processing based on the sample test result and disease name estimation processing based on the main complaint / symptom are performed. Next, the disease name estimated from the sample test result and the disease name estimated from the main complaint / symptom are displayed. A matching process is performed.

  FIG. 26 is a flowchart of the disease name estimation process from the specimen test result.

  In this process, four specimen test result data stored in the specimen test result file 240 (see FIG. 16) are retrieved one by one, and the normal value lower limit 173c and the normal value upper limit 173d of the test item master 173 (see FIG. 9) are extracted. To determine whether the value is within the normal value range (steps S061 to S062).

  If the result of determination in step S062 is that the inspection result data is within the normal value range, there is no problem with the inspection item, so the process returns to step S061 to continue processing the next inspection result data.

  In the example shown in the specimen test result file 240 (see FIG. 16), the test results (1) to (3) are all higher than the normal value lower limit and the normal value upper limit shown in the test item master 173 (see FIG. 9). Since it is within the range of the normal value, the process returns from step S062 to step S061.

  If the result of determination in step S062 is that the inspection result data is outside the normal value range, the process proceeds to step S063, and whether the inspection result data exceeds the normal value upper limit 173d of the inspection item master 173 (see FIG. 9). A determination is made whether or not.

  As a result of the determination in step S063, when the test result data exceeds the normal value upper limit 173d of the test item master 173 (see FIG. 9), the process proceeds to step S065 and is outside the upper limit of the estimated disease name master 174 (see FIG. 10). After all the disease name codes of the estimated disease names are output to the patient-specific examination-specific estimated disease name file 281 (see FIG. 27), the process returns to step S061 to continue the processing of the next examination result data.

  In the example shown in the specimen test result file 240 (see FIG. 16), the test result (4) (test item CD (4) 240j: “21005”) indicates “7.0”, and the test item master 173 ( Since the normal value upper limit “5.6” of the examination item “21005” (HBA1c) shown in FIG. 9 is exceeded, in this case, the process proceeds to step S065 and is included in the estimated disease name master 174 (see FIG. 10). The disease name CD “605003” of the off-limit estimated disease name 174b of the examination item “21005” (HBA1c) is output to the patient-specific examination-specific estimated disease name file 281 (see FIG. 27).

  If the result of determination in step S063 is that the inspection result data does not exceed the normal value upper limit 173d of the inspection item master 173 (see FIG. 9), the inspection result data exceeds the normal value lower limit of the inspection item master. Therefore, after all the disease name codes of the estimated disease names outside the lower limit of the estimated disease name master 174 (see FIG. 10) are output to the estimated disease name file 281 for each patient-specific examination (step S064), the process returns to step S061 Continue processing the inspection result data.

  FIG. 27 is a diagram showing an estimated disease name file for each patient-specific examination in the present embodiment.

  As shown in FIG. 27, in the estimated disease name file 281 for each patient-specific examination, the patient ID 281a of the consultation patient: “123456” and the disease name CD (1) 281b: “605003” estimated from the specimen test result of the consultation patient. (Diabetes mellitus), disease name CD (2) 281c: “704360” (pancreatitis) is stored.

  This estimated disease name “605003” (diabetes mellitus) is, as described above, the test item “21005” (HBA1c) is “7.0” among the test results shown in the sample test result file 240 (see FIG. 16). The normal value upper limit “5.6” of the inspection item “21005” (HBA1c) shown in the item master 173 (see FIG. 9) is exceeded. Therefore, in this case, the process proceeds to step S065, where it is estimated that the disease name CD “605003” (diabetes) of the estimated disease name 174b outside the upper limit of the examination item “21005” in the estimated disease name master 174 (see FIG. 10).

  The estimated disease name “704360” (pancreatitis) is a disease name estimated from other test results not shown in the specimen test result file 240 (see FIG. 16).

  Next, the disease name estimation process from the chief complaint / symptom will be described.

  In this process, the main complaint / symptom data 210b to 210h of the main complaint / symptom data file 210 (see FIG. 14) registered on the main complaint / symptom input screen 200 (see FIG. 13) based on the doctor's examination result is used as a key. The estimated disease name master 175 classified by symptom (see FIG. 11) is searched, an estimated disease name matching the key is acquired, and it is output to the estimated disease name file classified by patient main complaint.

  FIG. 28 is a diagram showing the structure of an estimated disease name file classified by patient main complaint in the present embodiment.

  As shown in FIG. 28, in the estimated disease name file 282 for each main complaint by patient, the patient ID 282a: “123456” of the patient being examined and the disease name CD (1) 282b: “605003” estimated from the main complaint / symptom of the patient being examined. (Diabetes mellitus), disease name CD (2) 282c: “984650” (appendicitis) is stored.

  Next, the above-mentioned patient-specific examination-specific estimated disease name file 281 (see FIG. 27) and patient-specific main complaint-specific estimated disease name file 282 (see FIG. 28) are matched.

  In this matching process, when the disease name CDs of the estimated disease name file 281 classified by patient-specific examination and the estimated disease name file 282 classified by patient-specific main complaint match, the disease name CD is output to the estimated disease name file 283, and the estimated disease name file classified by patient-specific examination If the disease name CD present in 281 is not in the patient-specific main complaint-specific disease name file 282, the disease name CD in the patient-specific examination-specific estimated disease name file 281 is output to the patient-specific main disease-specific estimated disease name file 282. When there is no disease name CD to be estimated in the patient-specific examination-specific estimated disease name file 281, the disease name CD of the patient-specific main complaint-specific estimated disease name file 282 is output to the estimated disease name file 283.

  FIG. 29 is a diagram showing the structure of an estimated disease name file in the present embodiment.

  As shown in FIG. 29, in this estimated disease name file 283, the patient ID 283a: “123456” of the patient being examined, the disease names output from both the estimated disease name file 281 by patient-specific examination and the estimated disease name file 282 by patient-specific main complaint CD (1) 283b: "605003" (diabetes) and hereditary flag (1) 283c: "1" (corresponding), and disease name CD (2) 283d: "704360" output from the patient-specific examination-specific disease name file 281 "(Pancreatitis) and hereditary flag (2) 283e:" 0 "(not applicable), and disease name CD (3) 283f:" 984560 "(appendicitis) and inheritance output from the patient-specific main complaint-specific disease name file 282 Sex flag (3) 283g: “0” (not applicable) is stored.

  Next, a matching process between the estimated disease name file 283 (see FIG. 29) and the family history summary data stored in the family history summary data 270 (see FIG. 25) is performed. That is, for the three estimated disease names stored in the estimated disease name file 283, the estimated disease names whose heritability flags are “1” are checked.

  FIG. 30 is a flowchart of a matching process between an estimated disease name file and family history summary data.

  As shown in FIG. 30, first, the reading of the disease name CD from the estimated disease name file is started (step S071). At this time, the variable I is initialized to “1”.

  Next, it is determined whether or not the heritability flag (I) is “1” (step S072).

  If it is determined in step S072 that the heritability flag (I) is “1”, the process proceeds to step S073. If the heritability flag (I) is not “1”, the process proceeds to step S076.

  In step S073, family history summary data 270 is searched for the disease name CD (I) in the estimated disease name file 283, and in step S074, it is determined whether or not family history data of the same disease name category exists.

  As a result of the determination in step S074, if family history data of the same disease name category exists, the process proceeds to step S075. If family history data of the same disease name category does not exist, the process proceeds to step S076.

  In step S075, the estimated disease name screen (see FIG. 31), the estimated disease name of the disease name CD (I) in the estimated disease name file 283, the family history data of the same disease name category, age at the time of disease, and information category (doctor diagnosis) Edit information including, for example, whether or not an inquiry is made, and the process proceeds to step S077.

  In step S076, only the estimated disease name of the disease name CD (I) in the estimated disease name file 283 is output to the estimated disease name screen (see FIG. 31), and the process proceeds to step S077.

  In step S077, after incrementing variable I, the process proceeds to step S078 to determine whether or not there is data in disease name CD (I).

  If there is data in the disease name CD (I) as a result of the determination in step S077, the process returns to step S072 to continue processing the next data, but if there is no data in the disease name CD (I), this subroutine is terminated.

  In this example, since the hereditary flag (1) 283c of the disease name CD (1) 283b: “605003” in the estimated disease name file 283 (see FIG. 29) is “1”, the family of this patient “123456” Some people have a history of diabetes, a genetic disorder. Further, the relationship between the patient and the patient being examined is that the relationship is “mother” from the history data 270b whose disease name classification is “605” in the family history summary data 270 (see FIG. 25), and the status classification Shows that it is a “doctor's diagnosis”.

  FIG. 31 is a diagram showing a disease name estimation screen in the present embodiment.

  As shown in FIG. 31, this disease name estimation screen 290 includes a patient ID display area 290a, an estimated disease name display field 290b, an estimated disease name (considering family history) display field 290c, and a diagnosis input button 290d. In the disease name display column 290b, there are three disease names “diabetes”, “pancreatitis”, and “appendicitis”, and in the estimated disease name (considering family history) display column 290c, “diabetes / mother (at age 57)” diabetes. Three disease names are displayed: Type 1 / Doctor Diagnosis, Pancreatitis, and Appendicitis.

  In this disease name estimation screen 290, if there is a hereditary disease subject in the family of the patient being examined, the disease name is displayed with “★”.

  When the display of the estimated disease name on the disease name estimation screen 290 is completed, diagnosis information input by the doctor (FIG. 12: step S07) is then performed.

  After the doctor finishes viewing the disease name estimation screen 290 and presses the diagnosis input button 290d, the following diagnostic information input screen is displayed.

  FIG. 32 is a diagram showing a diagnostic information input screen in the present embodiment.

  As shown in FIG. 32, the diagnosis information input screen 291 includes a patient ID display area 291a, a current diagnosis date input area 291b, a current diagnosis disease name CD 291c, a past diagnosis record display area 291d, and a registration button 291e. It has been.

  The doctor makes a diagnosis by combining the information obtained so far, that is, the information on the estimated disease name displayed on the disease name estimation screen 290, and the diagnosis date: “2004/6/30” and the disease name CD: “605007”. (Diabetes type 1) is input to the diagnosis date input area 291b and the diagnosis disease name CD291c.

  When the registration button 291e is pressed after the input is completed, this diagnostic information is registered in the medical history master 161 (see FIG. 3).

  When registration of the diagnostic information by the doctor is completed, a disease name diagnosis recalculation process (FIG. 12: step S07) is performed.

  In the disease name estimation apparatus according to the present embodiment, the second disease name estimation unit 130 (see FIG. 1) receives the information about the medical history of the family of the patient being examined in the medical history master 161 (see FIG. 3) being updated. Based on the updated information, it is possible to re-estimate the disease names of patients who have been examined in the hospital in the past.

  That is, the disease name diagnosis recalculation process is performed in response to the diagnosis of the disease name “diabetes type 1” being made for the patient “Jiro Yamada” on the diagnosis information input screen 291 (see FIG. 32) as described above. Thus, the recalculation processing of the diagnosis of the disease name given to “2004/5/24” is enabled for “Taro Yamada”, the older brother of this patient.

  As an object of this disease name diagnosis recalculation process, for example, a patient whose diagnosis date in the medical history master 161 (see FIG. 3) is within three months from the diagnosis date of the patient is automatically extracted. It is good to make it.

  FIG. 33 is a diagram showing a disease name diagnosis recalculation processing screen in the present embodiment.

  As shown in FIG. 33, this disease name diagnosis recalculation processing screen 292 includes a patient ID display area 292a, a current diagnosis date input area 292b, a current diagnosis disease name CD 292c, a past diagnosis date display area 292d, and a past diagnosis disease name. A CD 292e and a registration button 292f are provided. In addition, a comment display area 293 is displayed at the bottom of the disease name diagnosis recalculation processing screen 292.

  FIG. 34 is a flowchart of disease name diagnosis recalculation processing in the present embodiment.

  As shown in FIG. 34, the medical history master 161 (see FIG. 3) is constantly monitored for update by the monitoring program (step S081), and when updated, the process proceeds to step S082, and the genetic flag of the updated disease name is set. A determination is made as to whether or not standing.

  If the result of determination in step S082 is that the inherited flag for the updated disease name is not raised, processing returns to step S081 and update monitoring is continued.

  As a result of the determination in step S082, if the hereditary flag of the updated disease name is set, the process proceeds to step S083, and the family information master 163 (FIG. 5) in which the patient ID of the updated medical history master is registered as family information. Search) is performed.

  As a result of the search, it is determined whether or not the corresponding record exists (step S084).

  If the result of determination in step S084 is that there is no corresponding record, processing returns to step S081 and update monitoring is continued.

  If the result of determination in step S084 is that there is a corresponding record, processing proceeds to step S085, and the patient ID 163a, which is the main key of the patient information master 163 (see FIG. 5), is stored in a predetermined table in the program. When there are a plurality of corresponding records, the processing is repeated a plurality of times. For example, when a patient to whom a disease name is added is a parent, records corresponding to the number of children who are children of the patient and who are suffering from the hospital should be applicable. In the case of grandparents, the corresponding number of people will increase further.

  Next, re-processing of the disease name diagnosis is performed for each acquired patient ID (step S086). In this disease name diagnosis reprocessing, steps S02 to S06 in the flowchart shown in FIG. 12 are executed.

  Next, the reprocessing result is notified (step S087).

  Next, it is determined whether or not the reprocessing for the acquired patient ID has been completed (step S088).

  If the result of determination in step S088 is that reprocessing has not been completed, processing returns to step S086 and reprocessing is repeated.

  If the result of determination in step S088 is that all reprocessing has been completed, this processing ends.

  In the example shown in FIG. 33, in response to the diagnosis result (see FIG. 32) of “2004/6/30” of the brother “Jiro Yamada” of this patient “Taro Yamada”, the diagnosis of the disease name of this patient “Taro Yamada” was re-established. As a result of the calculation processing, a comment display area 293 is displayed with a comment as shown in the figure.

  In addition, as a result of the disease name diagnosis recalculation process, if the same result as the previous process result is obtained, it is not always necessary to notify, but as reference information to the doctor, that is, warning information of the disease to be careful in the future Since it is often effective, it is preferable to notify.

  The following proposals can be considered for the notification timing and notification method in this case.

  The notification timing may be, for example, real time, that is, when a reprocessing result is obtained, or when an electronic medical record of a patient to be examined is opened.

  In addition, as a notification method, for example, an e-mail to a doctor in charge or display on an electronic medical record can be considered.

  As described above, by notifying the doctor of the result of the recalculation process of the disease name diagnosis, the doctor himself can verify the validity of the doctor's past diagnosis, and he / she is careful when performing future treatment. This makes it possible for doctors to accurately grasp information about diseases that must be attached.

  Various aspects of the present invention will be additionally described below.

(Appendix 1)
In the disease name estimation device that estimates the disease name of the patient being examined,
A medical history master that stores information about the medical history of multiple patients;
A first disease name estimator for estimating a name of a disease of the consulted patient based on the chief complaint / symptom and sample test information of the consulted patient;
A first family disease name acquisition unit for acquiring a disease name of the family of the patient to be examined from the information stored in the medical history master;
A second disease name estimation unit for estimating a disease name of the patient to be examined based on a disease name acquired by the first family disease name acquisition unit;
A disease name estimation apparatus comprising: a disease name display unit that displays a disease name estimated by the first disease name estimation unit and a disease name estimated by the second disease name estimation unit.

(Appendix 2)
A second family disease name acquisition unit for acquiring a family disease name of the patient based on the inquiry information obtained from the patient;
The second disease name estimation unit estimates the disease name of the patient to be examined based on the disease name acquired by the first family disease name acquisition unit and the disease name acquired by the second family disease name acquisition unit. The disease name estimation apparatus according to supplementary note 1, characterized by:

(Appendix 3)
The second disease name estimation unit re-estimates the disease name of the examined patient based on the updated information in response to the update of the information related to the family history of the examined patient in the history master. The disease name estimation apparatus according to supplementary note 1 or 2, wherein the disease name estimation apparatus is a device.

(Appendix 4)
Computer
A first disease name estimating unit for estimating a name of a disease of the consulted patient based on the main complaint / symptoms and sample test information of the consulted patient;
A first family disease name acquisition unit for acquiring a disease name of the family of the patient to be examined from a history history master in which information on the history of a plurality of patients is stored;
A second disease name estimation unit for estimating a disease name of the patient to be examined based on a disease name acquired by the first family disease name acquisition unit;
A disease name characterized by operating as a disease name estimation device including a disease name display unit that displays a disease name estimated by the first disease name estimation unit and a disease name estimated by the second disease name estimation unit. Estimation program.

It is a schematic block diagram which shows one Embodiment of the disease name estimation apparatus and disease name estimation program of this invention. It is a schematic diagram of the computer system in which the disease name estimation apparatus and disease name estimation program of this embodiment are formed. It is a figure which shows the file structure of the medical history master in this embodiment. It is a figure which shows the file structure of the patient master in this embodiment. It is a figure which shows the file structure of the family information master in this embodiment. It is a figure which shows the file structure of the family history master in this embodiment. It is a figure which shows the file structure of the connection pattern master in this embodiment. It is a figure which shows the file structure of the disease name master in this embodiment. It is a figure which shows the file structure of the inspection item master in this embodiment. It is a figure which shows the file structure of the estimated disease name master in this embodiment. It is a figure which shows the file structure of the presumed disease name master classified by main complaint and symptom in this embodiment. It is a flowchart which shows operation | movement of the disease name estimation apparatus and disease name estimation program of this embodiment. It is a figure which shows the main complaint and symptom input screen in this embodiment. It is a figure which shows the structure of the chief complaint and symptom data file in this embodiment. It is a figure which shows the family information input screen in this embodiment. It is a figure which shows the file structure of the sample test result file in this embodiment. It is a flowchart of the family history acquisition / edit subroutine in the present embodiment. It is a figure which shows the inquiry (family history 1) input screen in this embodiment. It is a figure which shows the family history 1 table in this embodiment. It is a flowchart which shows the procedure of the data acquisition of the family history 2 table in this embodiment. It is a figure which shows the family history 2 table in this embodiment. It is a figure which shows the determination rule in the case of preparation of the family history summary data in this embodiment. It is a figure which shows the family history summary data creation example (1) in this embodiment. It is a figure which shows the family history summary data creation example (2) in this embodiment. It is a figure which shows the family history summary data in this embodiment. It is a flowchart of the disease name estimation process from a test result. It is a figure which shows the estimated disease name file classified by examination according to patient in this embodiment. It is a figure which shows the structure of the estimated disease name file classified by patient main complaint in this embodiment. It is a figure which shows the structure of the presumed disease name file in this embodiment. It is a flowchart of the matching process of an estimated disease name file and family history summary data. It is a figure which shows the disease name estimation screen in this embodiment. It is a figure which shows the diagnostic information input screen in this embodiment. It is a figure which shows the disease name diagnosis recalculation process screen in this embodiment. It is a flowchart of the disease name diagnosis recalculation process in this embodiment.

Explanation of symbols

DESCRIPTION OF SYMBOLS 100 Disease name estimation apparatus 110 1st disease name estimation part 120 1st family disease name acquisition part 130 2nd disease name estimation part 140 2nd family disease name acquisition part 150 Disease name display part 160 Database 161 Disease history master 162 Patient master 163 Family information master 164 Family History Master

Claims (3)

In the disease name estimation device that estimates the disease name of the patient being examined,
A medical history master that stores information about the medical history of multiple patients;
A first disease name estimator for estimating a name of a disease of the consulted patient based on the chief complaint / symptom and sample test information of the consulted patient;
A first family disease name acquisition unit for acquiring a disease name of the family of the patient to be examined from the information stored in the medical history master;
A second disease name estimation unit for estimating a disease name of the patient to be examined based on a disease name acquired by the first family disease name acquisition unit;
A disease name estimation apparatus comprising: a disease name display unit that displays a disease name estimated by the first disease name estimation unit and a disease name estimated by the second disease name estimation unit. A second family disease name acquisition unit for acquiring a family disease name of the patient based on the inquiry information obtained from the patient;
The second disease name estimation unit estimates the disease name of the patient to be examined based on the disease name acquired by the first family disease name acquisition unit and the disease name acquired by the second family disease name acquisition unit. The disease name estimation apparatus according to claim 1. Computer
A first disease name estimating unit for estimating a name of a disease of the consulted patient based on the main complaint / symptoms and sample test information of the consulted patient;
A first family disease name acquisition unit for acquiring a disease name of the family of the patient to be examined from a history history master in which information on the history of a plurality of patients is stored;
A second disease name estimation unit for estimating a disease name of the patient to be examined based on a disease name acquired by the first family disease name acquisition unit;
A disease name characterized by operating as a disease name estimation device including a disease name display unit that displays a disease name estimated by the first disease name estimation unit and a disease name estimated by the second disease name estimation unit. Estimation program.

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