JP2009288880A - Health management support device and health examination system - Google Patents

Abstract

<P>PROBLEM TO BE SOLVED: To provide a health management support device and a health examination system for promoting understanding of the contents of an interview for a health examination result. <P>SOLUTION: An image storage section 14 stores data of an image displayed in an interview for a health examination result. A voice storage section 18 stores data of voice generated in the interview. A summary generation section 20 generates summary data of the interview by arranging images. The summary generation section 20 can also generate summary data, where the image and a button for reproducing voice are arranged according to time, based on the data of the image and voice. A summary output section 22 outputs the summary data generated. <P>COPYRIGHT: (C)2010,JPO&INPIT

Description

  The present invention relates to a health management support apparatus and a health examination system for supporting health management of a health examination subject.

  In the medical system reform that will start in the spring of 2008, insurers (all citizens between the ages of 40 and 74, who are subject to about 56 million people) are required to conduct medical examinations. Therefore, the need for interview support, such as providing easy-to-understand explanations of health checkup results, is increasing. Techniques related to interview support are described in, for example, Patent Document 1 and Patent Document 2.

However, in general, the examinee has little knowledge about medical care, so it cannot be judged whether or not the contents of the interview are based on fair judgment. In addition, if a lot of contents are explained in a short time or explained with technical terms at the time of the interview, the examinee cannot correctly understand the contents of the interview. In addition, after the interview, if the interview content is forgotten, the examinee cannot review the interview content.
JP 2004-265307 A JP 2006-268800 A

  An object of the present invention is to provide a health management support apparatus and a health examination system that facilitate understanding of the contents of an interview about a health examination result.

  The health management support apparatus according to claim 1, an image storage unit that stores image data displayed during an interview about a medical examination result, and a summary that generates the summary data of the interview based on the image data A generating unit; and an output unit that outputs the generated summary.

  The medical checkup system according to claim 9 is a medical checkup system comprising a server device that manages data of a medical checkup result related to a medical examinee, and an information terminal connected to the server device directly or via a network. The server device includes an image storage unit that stores image data displayed at the time of the interview, a summary generation unit that generates the summary data of the interview based on the image data, and the generated summary. Is output to the information terminal.

  According to the present invention, it is possible to promote understanding of the contents of an interview about a medical examination result.

(First embodiment)
Hereinafter, a health management support apparatus and a medical examination system according to a first embodiment of the present invention will be described with reference to the drawings. The health management support apparatus according to the first embodiment is typically installed in an interview room of a medical examination facility. In the interview room, the examinee who has completed each examination such as physical measurement, medical examination, and X-ray photography, interviews the interview doctor about the results of these examinations. At the time of the interview, the interview doctor explains the test result to the examinee or gives guidance on future health management while displaying the checkup result of the examinee on the display unit of the health management support apparatus. The health management support apparatus according to the first embodiment generates information (hereinafter referred to as a summary) in which information provided by an interview doctor is recorded together at the time of an interview. The summary is generated based on an image related to the contents of the medical examination displayed at the time of the interview, a conversation between the examinee and the interviewer, and the like. The examinee can look back on the contents of the interview by referring to the generated summary after the interview. You can also refer to the summary with your family and explain it to your family or seek advice. The summary can also be input information to the second opinion.

  FIG. 1 is a diagram illustrating a configuration of a health management support apparatus according to the first embodiment. As shown in FIG. 1, the health care support apparatus includes a medical examination information storage unit 10, a display unit 12, an image storage unit 14, a microphone (microphone) 16, a voice storage unit 18, a summary generation unit 20, and a summary output unit 22. Prepare. The health management support device is, for example, a personal computer including a CPU (Central Processing Unit), a RAM (Random Access Memory), a ROM (Read Only Memory), a hard disk device, a display, a mouse, a keyboard, and the like.

  The medical examination information storage unit 10 includes a database management system (DBMS: DataBase Management System), and manages data related to medical examination information of the examinee and the like by the DBMS. Specifically, the medical examination information storage unit 10 includes, for example, a group information table regarding information on a group (company, municipality, etc.) that applied for a medical checkup, a checker table related to information on a person who applied for a medical checkup, A reception information table regarding medical examination procedure information and medical examination result data are stored. This information is checked by manual input, reading from offline media such as FD (registered trademark) or MO, or from a shared directory, or receiving data from an inspection device (not shown) such as an X-ray diagnostic apparatus or automatic analyzer. It is stored in the information storage unit 10.

  FIG. 2 is a diagram illustrating a configuration example of a group information table stored in the medical examination information storage unit 10. As shown in FIG. 2, the group information table identifies the group number and group name (kanji, katakana, etc.), group address, phone number, zip code, and medical examination course provided to the group. Items such as a contract number, a FAX number, an e-mail address, and a representative name.

  FIG. 3 is a diagram illustrating a configuration example of the examinee information table stored in the medical examination information storage unit 10. As shown in FIG. 3, the examinee information table includes a personal number for identifying the examinee, name (kanji, katakana, etc.), gender, age, date of birth, address, postal code, telephone number, FAX number, It includes items such as an e-mail address, a group number to which the examinee belongs, and an employee number (employee code) for identifying the examinee in the group.

  FIG. 4 is a diagram illustrating a configuration example of a consultation information table stored in the medical examination information storage unit 10. As shown in FIG. 4, the consultation information table includes a consultation number for identifying the appointment or reception of the examinee, the name of the examinee (kanji, katakana, etc.), the individual number of the examinee, the scheduled checkup date, and the checkup Includes items such as scheduled time, medical examination course, inspector's name (kanji, katakana), group number, status, reception date / time, data update date / time, data updater, etc.

  FIG. 5 is a diagram illustrating a configuration example of a medical examination result table stored in the medical examination information storage unit 10. As shown in FIG. 5, the medical checkup result table includes items such as a medical checkup number, a name of the medical checkup (kanji, katakana, etc.), a checkup date, a checkup result, and a checkup location.

  The health check result includes at least one of an inquiry result, a test result for the test item, an abnormality determination result for each test item, and guidance information based on the abnormality determination result.

  The test results are roughly classified into, for example, measurement, X-ray / ultrasound / endoscopy, urine test, stool test, blood test, and other test items. Measurement items include items related to physical measurements such as height, weight, obesity, BMI, blood pressure measurement, electrocardiogram, heart rate, fundus examination, intraocular pressure examination, visual acuity examination, hearing examination, lung function examination, etc. Have. The X-ray / ultrasonic / endoscopic items include items such as chest X-ray, upper digestive tract X-ray, and abdominal ultrasound. The urinalysis items include items such as protein, urine sugar, sediment, occult blood, and specific gravity. The stool examination items include items relating to stool examinations such as occult blood. Blood test items are total protein, A / G, albumin, creatinine, uric acid, total cholesterol, HDL cholesterol, LDL cholesterol, neutral fat, total bilirubin, AST (GOT), ALT (GPT), γGTP, ALP, blood glucose ( Fasting), items related to biochemical tests such as HbA1c, items related to hematology tests such as red blood cells, white blood cells, hemoglobin, hematocrit, platelet count, MCV, MCH, MCHC, CRP, blood type (ABO), blood type (Rh) Including items related to serological tests such as glass plate method, agglutination method, and HBS antigen. Other items include items such as morbidity history.

  Interview results include information on current health conditions (such as the name of the disease and current medical condition), information on past diseases, genetic information (eg, “Father is hypertension”, “Mother is diabetes”, etc.), lifestyle related It has items such as information (habits such as eating, smoking, drinking, sleeping, exercising, working, and leisure).

  At the time of the interview, the display unit 12 receives the medical examination information of the medical examinee and information related to the medical examination information (the medical examination information of the medical examination information) based on an instruction via an input device (not shown) by the interviewing doctor or the medical examiner. Various information such as supplementary information, hospital maps and examination times are displayed on the screen.

  The image storage unit 14 stores various information such as medical examination information displayed on the screen and information related to the medical examination information as image data at a predetermined timing. Hereinafter, image data relating to information displayed on the screen is referred to as screen image data. The format of the image file at the time of storing may be a general one, for example, PDF (registered trademark) (Portable Document Format), PNG (Portable Network Graphics), BMP (BitMaP), or the like. The image storage unit 14 can similarly store the explanation information drawn on the screen by the interview doctor operating the input device (mouse, tablet, touch panel, etc.) as screen image data. Further, the image storage unit 14 can also store image data related to explanatory material written on a sheet by an interview doctor read by a camera or a scanner (not shown). Hereinafter, the image data related to the explanatory material will be referred to as material image data. Note that when the screen image data and the material image data are not distinguished, they are simply referred to as image data. The image storage unit 14 stores the image data in association with information specifying the order in which the image data is stored (hereinafter referred to as image series information).

  The microphone 16 receives a conversation between the interview doctor and the examinee at the time of the interview with a diaphragm provided in the microphone 16 and converts the vibration caused by the conversation into an analog electric signal.

  The voice storage unit 18 converts the analog electric signal converted by the microphone into a digital electric signal by a general method such as PCM (Pulse Code Module) or ADPCM (Adaptive differential Pulse Code Module) and stores the digital electric signal. The stored digital electrical signal is stored so as to be reproducible as a conversation between the interviewer and the examinee. Hereinafter, the stored digital electrical signal is referred to as audio data. The audio storage unit 18 may store the audio data by compressing the audio data using an MP3 (MPEG Audio Layer 3) method or the like. The voice storage unit 18 stores the voice data in association with information specifying the order in which the voice data is stored (hereinafter referred to as voice sequence information).

  The summary generation unit 20 generates summary data based on the image data. Specifically, the summary generation unit 20 generates summary data by arranging images according to image sequence information associated with each image. The summary generation unit 20 can also include audio data in the summary data. In this case, the summary generation unit 20 generates summary data by arranging GUI parts (for example, a reproduction button, an icon, etc.) for reproducing the sound according to the sound sequence information associated with the sound data. The summary output unit 20 also includes information on the examinee (for example, name, gender, date of birth, etc.), information on the medical institution (for example, group name, interview date, etc.), examination information (for example, medical checkup date, health checkup date, etc.). The medical examination information such as the name of the medical examination course may be included in the summary data. The summary data is generated in a general file format such as PDF (registered trademark), HTML (HyperText Markup Language), Word (registered trademark), or PowerPoint (registered trademark). The summary data may be generated in a dedicated file format by a dedicated program for generating and displaying the summary data.

  The summary output unit 22 outputs the generated summary data. As an output method, the summary may be printed on paper, may be output to an information terminal such as a personal computer, a PDA (Personal Digital Assistance), a mobile phone, or a portable such as a CD-R or a non-volatile memory. It may be output to a possible storage medium. When the summary data is generated in a dedicated file format, the information terminal reads and displays the summary data by a dedicated program. The summary output unit 22 may be in a form of accessing and displaying a Web browser in a form such as an ASP (Application Service Provider) service.

  Details of the summary generation process according to the first embodiment will be described below. At the time of the interview, the interview doctor, for example, provides guidance on health management to the examinee while displaying a window (display area that can be moved and expanded on the screen via the input device) indicating the result of the medical checkup on the screen of the display unit 12. To do. FIG. 6 is a diagram showing a window W1 showing a medical examination result. The health check result shown in FIG. 6 relates to the examinee “XX Jiro”. The pointer P on the window W1 moves with the movement of the mouse. In the upper part of the window, basic information such as interview date, consultation number, personal number, name, gender, age, affiliation, medical examination course, medical examination location, etc. are displayed. Below the middle part of the window, the values of the inspection items are listed. For example, FIG. 6 shows test items such as height, weight, standard weight, BMI index, systolic blood pressure, diastolic blood pressure, GOT, GPT, γGTP, ZTT, LDH, and ALP.

  As shown in FIG. 6, the inspection items indicating abnormal values are explicitly displayed. For example, as shown in FIG. 6, since the values of waist circumference, GOT, and GPT are not in the normal range, an “H” mark MH indicating an abnormal value is given to each. Whether it is an abnormal value is determined using a threshold value for determination. For example, if the GOT threshold is 40, it is determined that the GOT is 40 or more and abnormal, and if it is less than 40, the standard is determined. This abnormality determination process is a general technique, and it is assumed that the code indicating the abnormality determination result and the medical examination item are associated with the medical examination result table.

  Each item on the window W1 and the “H” mark MH can be selected. When an item or mark is selected via the input device, the display unit 12 reads a window showing detailed information on the selected item from the medical examination information storage unit 10 and displays it on the screen. For example, as shown in FIG. 6, when the blood test item “GOT” is selected on the window by the pointer P, the display unit 12 describes GOT and GPT as shown in FIG. Window W2 is displayed on the screen. Further, for example, when the numerical value (for example, 144) of the item “GOT” is selected on the image by the pointer P, the display unit 12 displays the normal range of GOT and GPT as shown in FIG. A window W3 with a description is displayed on the screen. Further, for example, when the “H” mark MH attached to the item “GOT” on the image is selected by the pointer P, the display unit 12 causes the onset risk of GOT and GPT as shown in FIG. A window W4 in which the explanation about is described is displayed on the screen. Further, these explanations may be displayed with a tooltip instead of a window. For example, the display unit 12 displays a detailed description with a tooltip when the mouse cursor is moved to a character string “GOT”.

  As shown in FIG. 6, the comprehensive determination result is displayed in the middle of the window W1. The comprehensive determination result is determined, for example, by applying the values of a plurality of inspection items listed to a decision tree for determining the comprehensive determination result. For example, in the case of FIG. 6, the comprehensive determination results are “liver dysfunction”, “necessary examination”, “metabolic syndrome”, and “necessary treatment”. This comprehensive determination process is a general technique, and it is assumed that the code indicating the comprehensive determination result and the examinee number are associated on the medical examination result table.

  The image storage unit 14 stores information displayed on the entire screen of the display unit 12 at a predetermined timing as screen image data using, for example, a print screen function. For example, a window displaying medical examination information is drawn on the stored screen image. The predetermined timing is, for example, when the window moves to the next page, when a new window is displayed on the screen, when a scroll bar on the window is moved, and another area in the window is displayed.

  The image data is stored in association with the image series information. The image series information is the time when the image data was stored, the elapsed time from the start of the interview when the image data was stored, identification information for uniquely identifying the image data, and the like. The identification information is, for example, a serial number. The serial number is a number that is incremented every time an image is displayed or every time an image is stored. The identification information may be a tag. The tag is a short character string (heading) for specifying (identifying) that an image has been displayed or that an image has been stored. The identification information may be a combination of a visitor ID, a visit number, and a serial number, or a combination of a visitor ID, a visit number, and a tag. Alternatively, a combination of the examinee ID, the consultation number, the serial number, and the tag may be used as the identification information. Hereinafter, in order to specifically describe the summary generation process, the image series information is the time when the image data is stored.

  The voice storage unit 18 stores the conversation between the interviewing doctor and the examinee during the interview as voice data. The voice storage unit 18 divides the voice data at a predetermined timing and stores the divided voice data in individual files. The timing of dividing the audio data is, for example, when the window moves to the next page, when a new window is displayed on the screen, or when silence and low volume continue for a certain period.

  The audio data is stored in association with the audio sequence information. The voice sequence information is the time when the voice data is stored, the elapsed time from the start of the interview when the voice data is stored, the identification information for uniquely identifying the voice data, and the like. Similar to the image series information, the identification information is composed of at least one information of a serial number of audio data and a tag of audio data. Hereinafter, in order to specifically describe the summary generation process, the audio sequence information is the time when the audio data is stored.

  The summary generation unit 20 generates the summary upon receiving a request for starting the summary generation processing from the examinee or interview doctor after the interview is completed, or automatically. In the summary generation process, the summary generation unit 20 associates the screen image and the document image stored in the image storage unit 18 and the audio data playback button stored in the audio storage unit 18 with each other. The summary data is generated by arranging according to the above. Image data is reduced or enlarged as necessary.

  FIG. 10 is a diagram illustrating an example of a generated summary. As shown in FIG. 10, on the summary D1, a first image I1, a second image I2, a first audio reproduction button S1, and a second audio reproduction button S2 are arranged according to time. The first image I1 is associated with an earlier time than the second image I2. Further, the first audio data corresponding to the first audio reproduction button S1 is associated with an earlier time than the second audio data corresponding to the second audio reproduction button S2. The time associated with the first image I1 and the time associated with the first audio data are approximate. Similarly, the time associated with the second image I1 is approximate to the time associated with the second audio data. The summary output unit 20 also includes information about the examinee (for example, name, gender, date of birth, etc.), information about the medical institution (for example, the name of the organization, the name of the doctor who conducted the interview, etc.), examination information (for example, the examination) Medical examination information Z such as date, medical examination course name, etc.) is arranged. When the summary data has a specification that does not use audio data, an image and medical examination information may be arranged in the summary.

  As described above, according to the first embodiment, the summary is generated based on the image actually viewed by the examinee during the interview. Therefore, when it becomes necessary to look back on the interview content after the interview, the examinee can easily and at any time look back on the interview content by referring to the generated summary. When the summary data includes voice data, the contents of the interview can be looked back more accurately by referring to the summary using an information terminal capable of reproducing the image data and the voice data. In addition, if the instruction contents cannot be followed during the interview, the examinee can grasp the instruction contents more accurately by repeatedly referring to the summary. Thus, it is possible to provide a health management support device and a health examination system that facilitate understanding of the contents of interviews about health examination results.

  In the above configuration, the medical examination information storage unit 10 and the constituent elements (display unit 12, image storage unit 14, microphone 16, voice storage unit 18, summary generation unit 20, and summary output unit 22) are one. Included in the device (health management support device). However, the first embodiment need not be limited to such a stand-alone format. For example, it may be a client / server type medical examination system as shown in the following modification.

(Modification)
FIG. 11 is a diagram illustrating a configuration of a medical examination system according to a modification of the first embodiment. The medical examination system includes a server device 40 and at least one client device 50 connected to each other via a network. The server device 40 includes a medical examination information storage unit 10. Each client device 50 includes a display unit 12, an image storage unit 14, a microphone 16, an audio storage unit 18, a summary generation unit 20, and a summary output unit 22. When displaying the medical examination information stored in the medical examination information storage unit 10 of the server apparatus 30 on the display unit 10 of each client apparatus 50, each client apparatus 50 accesses the server apparatus 40 via the network and is necessary. Information can be acquired.

(Second Embodiment)
FIG. 12 is a diagram illustrating a configuration of a health management support apparatus according to the second embodiment. In the following description, components having substantially the same functions as those in the first embodiment are denoted by the same reference numerals, and redundant description will be given only when necessary.

  As shown in FIG. 12, the health management support apparatus according to the second embodiment includes a medical examination information storage unit 10, a display unit 12, an image storage unit 14, a microphone (microphone) 16, a voice storage unit 18, and a summary generation unit 20. A summary output unit 22 and a storage request unit 24.

  The storage request unit 24 requests the image storage unit 14 to store screen image data and document image data. Further, the storage request unit 24 requests the voice storage unit 18 to store voice data. Specifically, the storage request unit 24 is realized by an input device such as a keyboard, a mouse, a switch, a touch panel, or a storage request button on the screen.

  The image storage unit 14 stores the screen image displayed on the display unit 10 at the time when the request is received and the data of the document image when the request from the storage request unit 24 is received. The image storage unit 14 stores the data of these images in association with the image series information. The serial number of the image series information is a number that increases each time a storage request is received.

  The voice storage unit 18 stores voice data for a predetermined period from the time when the request is received, when the request from the storage request unit 24 is received. The voice storage unit 18 stores the voice data separated by a predetermined period in an individual file. The predetermined period is, for example, a period from the time when the request is received to a certain time before, a period until the voice goes back to the silence level from the time when the request is received, a page is switched backward from the time when the request is received, This is the period until window display, storage request reception, etc. are performed. The audio data is stored in association with the audio sequence information. The serial number of the audio sequence information is a number that increases every time a request for storage is received.

  The summary generation unit 20 generates summary data by arranging storage-requested images and audio playback buttons according to the times associated with each. FIG. 13 is a diagram illustrating an example of the summary D2 according to the second embodiment. As shown in FIG. 13, when the examinee refers to the summary later, it corresponds to the time when the storage request is made on the play buttons S1 and S2 in order to easily remember the scene where the interview information is requested. Marks KM1 and KM2 may be attached to the positions. The marks KM1 and KM2 may be character data, illustrations, or a reduced version of the image stored in the image storage unit 14.

  As described above, according to the second embodiment, a summary is generated based on an image or sound requested to be stored, thereby generating a summary having only interview contents that the examinee wants to look back on later. It becomes possible. Thus, it is possible to provide a health management support device and a health examination system that facilitate understanding of the contents of interviews about health examination results.

  In the second embodiment, the image storage unit 14 stores only the image data requested to be stored, and the sound storage unit 18 stores only the sound data. However, the image storage unit 14 may store image data at a predetermined timing shown in the first embodiment regardless of whether there is a storage request. The voice storage unit 18 may store voice data at a predetermined timing shown in the first embodiment. In this case, the image storage unit 14 stores the time when the storage request is received from the storage request unit 24 in addition to the image data. The summary generation unit 20 reads the image data displayed at the storage requested time from the image storage unit 14 and uses it for generation of the summary. For example, it is assumed that data of a certain image (standard image) is stored at 10:00, and image (reference image) data displayed next is stored at 10:10. Then, it can be estimated that the reference image was displayed between 10:00 and 10:10. For example, when the time when the storage request is received is 10:05, the summary generation unit 20 determines that the image displayed at the time when the storage request is received is the reference image, and uses the reference image as a summary generation. Use. The summary generation unit 20 performs the same process as the image data on the audio data and uses it for the summary generation.

(Third embodiment)
FIG. 14 is a diagram illustrating a configuration of a health management support apparatus according to the third embodiment. In the following description, components having substantially the same functions as those in the first and second embodiments are denoted by the same reference numerals, and redundant description will be given only when necessary.

  As shown in FIG. 14, the health care support apparatus according to the third embodiment includes a medical examination information storage unit 10, a display unit 12, an image storage unit 14, a microphone 16, a voice storage unit 18, a summary generation unit 20, and a summary output. A unit 22 and a voice recognition unit 26 are provided.

  The voice recognition unit 26 recognizes voice data stored in the voice storage unit 18 and converts it into character string data. Generally speaking, speech recognition learns features of speech from learning data that records a large amount of utterances, and compares the input speech signal with those features and outputs the most likely language sequence as a recognition result. It is. Hereinafter, the character string data generated by the speech recognition is referred to as conversation sentence data.

  Although not shown in FIG. 15, in order to identify the conversation between the examiner and the interviewer, a microphone for the recipient and a microphone for the interviewer are provided. The voice data derived from the interview doctor's microphone may be recognized as the interview doctor's voice data.

  The summary generation unit 20 arranges the image stored in the image storage unit 14 and the conversation sentence generated by the voice recognition unit 26 according to time, and generates summary data. FIG. 15 is a diagram illustrating an example of a summary D3 including an image and a conversation sentence. As shown in FIG. 15, the images I1 and I2 are displayed in the left region LR of the summary D3, the first conversation sentence CM1 and the second conversation sentence CM2 of the interview doctor in the center area CR, and the examinee's first conversation sentence CM1 and second conversation sentence CM2. One conversation sentence CC1 and second conversation sentence CC2 are arranged. The conversation sentences are arranged in chronological order from the top. The conversation sentences CM1, CM2, CC1, and CC2 are character strings that represent conversations that were made when the images I1 and I2 were displayed on the display unit 12.

  As described above, according to the third embodiment, summary data is generated on the basis of an image and a conversation sentence that expresses a conversation between the interview doctor and the examinee in characters. Therefore, it is possible to look back on the conversation during the interview even when referring to the summary on a paper or an apparatus that cannot reproduce audio. Thus, it is possible to provide a health management support device and a health examination system that facilitate understanding of the contents of interviews about health examination results.

(Fourth embodiment)
FIG. 16 is a diagram illustrating a configuration of a health management support apparatus according to the fourth embodiment. In the following description, constituent elements having substantially the same functions as those in the first, second, and third embodiments are denoted by the same reference numerals, and redundant description is performed only when necessary.

  As shown in FIG. 16, the health care support apparatus according to the fourth embodiment includes a medical examination information storage unit 10, a display unit 12, an image storage unit 14, a microphone 16, a voice storage unit 18, a summary generation unit 20, and a summary output. Unit 22, storage request unit 24, voice recognition unit 26, related information storage unit 28, and related information extraction unit 30.

  The image storage unit 14 stores the character string displayed in the window and the data of the character string displayed in the title bar of the window when the storage request is received. The character strings displayed in the window are, for example, a character string “liver dysfunction”, a character string “GOT”, a character string “ZTT”, and the like as shown in FIG. The character string displayed in the title bar is, for example, the character string “Description of GOT and GPT” as shown in FIG. At the same time, the image storage unit 14 selects a selected position such as a mouse cursor position, a key input cursor position, or a focus position on the screen in order to estimate the contents of the interview explained by the interview doctor at the time when the storage request is received. The data is also stored. The image storage unit 14 stores the character string and the selected position in association with the stored time.

  The related information storage unit 28 stores data of information (hereinafter referred to as related information) related to medical information and the like explained during the interview. The related information is not information to be displayed on the display unit 10 during the interview, but information to be described in the summary. Specifically, the related information storage unit 28 stores a related information table in which related information is associated with a condition for describing the related information in the summary.

  The related information extraction unit 30 determines a condition for describing the related information in the summary based on the character string and the selected position stored in the image storage unit 14, and searches the related information table using the determined condition as a keyword. Thus, the related information data associated with the keyword on the related information table is extracted from the related information storage unit 28.

  The summary generation unit 20 arranges the extracted related information and images according to time and generates summary data. The related information is arranged as a character string in a predetermined area of the summary.

  Details of the summary generation process of the fourth embodiment will be described below. FIG. 17 is a diagram illustrating a configuration example of a related information table. As shown in FIG. 17, in the related information table, related information is associated with conditions for describing the related information in the summary. The conditions are, for example, “GOT explained”, “GOT is high”, and the like.

  The summary generation process will be described by taking the condition “GOT is high” as an example. For example, it is assumed that the character string “GOT” is stored in the image storage unit 14 and is associated with a code indicating that the medical examination item “GOT” is an abnormal value on the medical examination result table. The related information extraction unit 30 determines the condition “high GOT” from the combination of the character string “GOT” and the code indicating an abnormal value. Then, as illustrated in FIG. 17, the related information extraction unit 30 searches the related information table using the determined condition “GOT is high” as a keyword, and searches for related information “about heart and skeletal muscle disorders” as related information. Extracted from the storage unit 28. Then, the summary generation unit 20 arranges the extracted character string representing the related information “about heart and skeletal muscle disorder” in a predetermined region of the summary.

  Further, for example, when the mouse cursor selects or is in the vicinity of the medical examination item “GOT” at the time of receiving the storage request, it can be estimated that the interview doctor is explaining GOT. In this case, the related information extraction unit 30 determines “GOT explained” as a condition. Further, based on the character string “Description of GOT and GPT” simply described in the window title, the related information extraction unit 30 determines on the condition that “GOT and GPT explanation window is displayed”. Then, as shown in FIG. 17, the related information extraction unit 30 searches the related information table using the determined condition “GOT and GPT explanation window is displayed” as a keyword, and related information “about GOT and GPT”. Are extracted from the related information storage unit. Then, the summary generation unit 20 arranges the extracted character string representing the related information about “GOT and GPT” in a predetermined region of the summary.

  Further, as shown in FIG. 6, a character string “GOT”, a code indicating an abnormal value associated with the medical examination item “GOT” on the medical examination result table, a character string “GPT”, From the combination of the code indicating that the abnormal value is associated with the diagnosis item “GPT” on the medical examination result table and the code indicating the comprehensive determination result “necessary examination for liver dysfunction”, “GOT and GPT are standard It is also possible to determine on the condition that the value is higher than the value and a detailed examination of liver dysfunction is required. Then, as shown in FIG. 17, the related information extraction unit 30 searches the related information table using the determined condition “GOT and GPT are higher than the reference values and requires a detailed examination of liver dysfunction” as a keyword. The related information “What is a general work-up for a functional disorder” is extracted from the related information storage unit 28. Then, the summary generation unit 20 arranges the extracted character string representing the related information “what is a general close examination of liver dysfunction” in a predetermined region of the summary.

  Furthermore, the related information extraction unit 30 can also apply a character string related to the inquiry result to the related information table. FIG. 18 is a diagram showing a window W5 relating to information on the inquiry result. In the interview result shown in FIG. 18, the daily intake of beer is 5 large bottles. The number of large bins is larger than the reference value (for example, one). Therefore, the related information extraction unit 30 determines that “the amount of alcohol intake is large”. As a result, the related information extracting unit 30 combines “GOT”, a code indicating that “GOT” is an abnormal value associated with the medical examination result table, and the determination “high alcohol intake”. Thus, “GOT is higher than the reference value and alcohol intake is large” is determined as a condition. Then, as shown in FIG. 17, the related information extraction unit 30 searches the related information table using the determined condition “GOT is higher than the reference value and has a large amount of alcohol intake” as a keyword. The related information “about” is extracted from the related information storage unit 28. And the summary production | generation part 20 arrange | positions the extracted character string showing the relevant information about "about the eating habits which touch a liver" to the predetermined | prescribed area | region of a summary.

  In addition, the related information extraction process is not performed for all the character strings stored in the image storage unit 14, and the related information extraction process is performed only for the character strings related to the matter that the interview doctor is likely to explain. Also good. The related information extraction process in this case will be described below.

  The score indicating the degree of possibility of explanation is calculated based on, for example, the number of times a character string appears and an evaluation value determined by the positional relationship between the cursor and the character string on the image. FIG. 19 is a diagram illustrating a list of character strings, the number of appearances, evaluation values, and scores for each character string. The number of appearances of the character string is the number of times that the character string appears in the image stored in the image storage unit 14. For example, in the image including the window shown in FIG. 8, a high evaluation value (evaluation value “9” in FIG. 19 is set for the character string “GOT” existing at the cursor selected position. For “GPT” and “blood test”, the evaluation value is lower than “GOT” (evaluation value “3” in FIG. 19) because it is close to the cursor position but not selected. A lower evaluation value (evaluation value “1” in FIG. 19) is set for the character string “γGTP” located away from the cursor position, and the related information extraction unit 30 then sets the number of appearances and the selected position. The score is calculated from the weights (calculated from the respective products in FIG. 19), and the related information extraction unit 30 calculates the character string having a high score value (character string “GOT” in FIG. 19) Could explain Then, the related information extraction unit 30 extracts the related information corresponding to the character string “GOT” from the related information storage unit 28, and the summary generation unit 20 places the extracted related information in a predetermined area of the summary. .

  FIG. 20 is a diagram illustrating an example of the summary D4 in which related information is arranged. As shown in FIG. 20, an image I is arranged in the left region LR of the summary, a conversation sentence C is arranged in the central region CR, and a character string E representing related information is arranged in the right region RR. Note that related information can also be extracted from a conversation sentence generated by the speech recognition unit 26 in the same manner as a character string included in an image. For example, when a conversation as shown in FIG. 20 is performed, a character string “liver dysfunction” is identified from the conversation sentence, and “liver dysfunction is explained”, and “liver functions such as fatty liver and hepatitis” Relevant information about “failure” is extracted.

  As described above, according to the fourth embodiment, medical information is extracted from data of an image or a conversation sentence, and related information of the extracted medical information is arranged in the summary. The examinee can resolve the indigestion of the interview due to difficult medical terms and the forgetting of the explained contents by referring to the summary in which the related information is arranged. Also, by placing related information related to medical terms with high importance in the summary, it is possible to reduce the amount of summary data and the processing time for summary generation. Thus, it is possible to provide a health management support device and a health examination system that facilitate understanding of the contents of interviews about health examination results.

  Note that the present invention is not limited to the above-described embodiment as it is, and can be embodied by modifying the constituent elements without departing from the scope of the invention in the implementation stage. In addition, various inventions can be formed by appropriately combining a plurality of components disclosed in the embodiment. For example, some components may be deleted from all the components shown in the embodiment. Furthermore, constituent elements over different embodiments may be appropriately combined.

The figure which shows the structure of the health-care assistance apparatus which concerns on 1st Embodiment of this invention. The figure which shows the structural example of the group information table memorize | stored in the medical examination information storage part of FIG. The figure which shows the structural example of the examinee information table memorize | stored in the medical examination information storage part of FIG. The figure which shows the structural example of the consultation information table memorize | stored in the medical examination information storage part of FIG. The figure which shows the structural example of the medical examination result table memorize | stored in the medical examination information storage part of FIG. The figure which shows the window which shows the medical examination result displayed on the display part of FIG. The figure which shows the explanation window of GOT and GPT displayed on the display part of FIG. The figure which shows the normal range window of GOT and GPT displayed on the display part of FIG. The figure which shows the GOT and GPT onset risk window displayed on the display part of FIG. The figure which shows the summary produced | generated by the summary production | generation part of FIG. The figure which shows the structure of the medical examination system which concerns on the modification of 1st Embodiment. The figure which shows the structure of the health-care assistance apparatus which concerns on 2nd Embodiment of this invention. The figure which shows the summary produced | generated by the summary production | generation part of FIG. The figure which shows the structure of the health-care assistance apparatus which concerns on 3rd Embodiment of this invention. The figure which shows the summary produced | generated by the summary production | generation part of FIG. The figure which shows the structure of the health-care assistance apparatus which concerns on 4th Embodiment of this invention. The figure which shows the structural example of the related information table memorize | stored in the related information storage part of FIG. The figure which shows the inquiry result window displayed on the display part of FIG. The figure which shows the list of the character string which concerns on the application example of the related information extraction process by the related information extraction part of FIG. 16, the frequency | count of appearance about each character string, an evaluation value, and a score. The figure which shows the summary produced | generated by the summary production | generation part of FIG.

Explanation of symbols

  DESCRIPTION OF SYMBOLS 10 ... Medical examination information storage part, 12 ... Display part, 14 ... Image storage part, 16 ... Microphone (microphone), 18 ... Voice storage part, 20 ... Summary generation part, 22 ... Summary output part, 24 ... Storage request part, 26 ... voice recognition unit, 28 ... related information storage unit, 30 ... related information extraction unit, 40 ... server device, 50 ... client device

Claims (9)

An image storage unit for storing data of an image displayed at the time of an interview about a medical examination result;
A summary generation unit that generates summary data of the interview based on the image data;
An output unit for outputting the generated summary;
A health management support device comprising: The image storage unit stores the image data in association with first series information for specifying the stored order,
The summary generation unit generates the summary data by arranging the images according to the first series information.
The health management support apparatus according to claim 1. A display unit for displaying the image during the interview;
A storage requesting unit that requests the image storage unit to store the data of the displayed image;
The image storage unit stores the data of the image triggered by receiving the request;
The health management support apparatus according to claim 1. A voice storage unit for storing voice data generated during the interview;
The summary generation unit generates the summary data based on the image data and the audio data.
The health management support apparatus according to claim 1. The voice storage unit stores the voice data in association with second sequence information for specifying the stored order;
The summary generation unit generates the summary data by arranging the image according to the first sequence information and arranging components for reproducing the sound according to the second sequence information.
The health management support apparatus according to claim 4. A conversion unit for recognizing the voice data and converting the voice data into conversation text data;
The summary generation unit generates the summary data based on the image data and the conversation sentence data.
The health management support apparatus according to claim 3. A table storage unit for storing a table in which keywords and medical information related to the keywords are associated;
The summary generation unit is associated on the table with a condition determined based on at least one of a character string included in at least one of the image and the conversation sentence, and a cursor selection position included in the image. Medical information included in the summary,
The health management support apparatus according to claim 6.   The health management support apparatus according to claim 1, wherein the summary generation unit includes at least one of information on a medical examinee, information on a medical institution, and examination information in the summary data. In a medical examination system comprising a server device that manages data of medical examination results related to a medical examinee, and an information terminal connected to the server device directly or via a network,
The server device
An image storage unit for storing image data displayed during the interview;
A summary generation unit that generates summary data of the interview based on the image data;
An output unit for outputting the generated summary to the information terminal;
A medical examination system characterized by comprising:

Images