CN110109887B - Data retrieval method, electronic device, and computer storage medium - Google Patents
Data retrieval method, electronic device, and computer storage medium Download PDFInfo
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Abstract
The application provides a data retrieval method, an electronic device and a computer storage medium, wherein the method acquires a retrieval request; searching in the distributed document database according to the searching request to obtain a searching result; the distributed document database is constructed by elastic search and used for storing patient medical data; in the distributed document database, the patient identification is used as a main index, and medical data of each patient is stored in a classified mode by taking the medical event as a basis. According to the data retrieval method, the data in the distributed document database constructed by the ElasticSearch is retrieved, and the medical data of each patient are stored in a classified mode by taking the patient identification as the main index and taking the medical event as the basis in the distributed document database, so that the medical event of the patient can be quickly and accurately positioned when the distributed document database is retrieved, and the accuracy of data retrieval is improved.
Description
Technical Field
The present invention relates to the field of medical health technologies, and in particular, to a data retrieval method, an electronic device, and a computer storage medium.
Background
Three information points of new medical improvement in China are clearly proposed: "resident health information file, medical information sharing platform and regional medical system are to be established". Through construction and development of the medical industry for many years, at present, various large hospitals and medical units gradually form a comprehensive information system which is mainly applied.
With the increase of medical data scale in geometric progression, in order to effectively store and efficiently utilize related data and promote higher-level medical information sharing based on a regional medical system, especially clinical data in medical information, a multi-center, networked and large-sample sharing platform is urgently needed to be established for effective management so as to provide support for the retrieval of trans-institution and trans-center patient data for hospitals, and meanwhile, when the clinical data are specially researched, a large amount of historical medical record information needs to be collected, sorted and analyzed to obtain related information such as disease treatment and the like, so that the medical quality and the diagnosis and treatment level are improved.
Therefore, a data retrieval method for quickly and accurately locating the required health record information is needed.
Disclosure of Invention
In order to solve the above problem, embodiments of the present application provide a data retrieval method, an electronic device, and a computer storage medium.
In order to achieve the purpose, the invention adopts the main technical scheme that:
a method of data retrieval, the method comprising:
s101, acquiring a retrieval request;
s102, searching in a distributed document database according to the searching request to obtain a searching result;
the distributed document database is constructed by elastic search and used for storing patient medical data;
in the distributed document database, the patient identification is used as a main index, and medical data of each patient is stored in a classified mode by taking the medical event as a basis.
Optionally, the medical event comprises: electronic medical record events, referral recording events, outpatient events, hospitalization events, hand anesthesia events, gynecological events, patient basic information events, transfusion recording events, vital sign monitoring events, exam reporting events, medical record first page events, patient visit events, digital imaging and communications in DICOM events.
Optionally, the step of using the patient identifier as a main index and storing the medical data of each patient according to the medical event by classification includes:
for any patient, using the identity of said any patient as a primary index,
storing the clinical document record of any patient in a class corresponding to the electronic medical record event, wherein the clinical document record comprises clinical document segment data and clinical document data;
storing a referral or transfer record of any patient in a class corresponding to a referral record event, wherein the referral or transfer record comprises referral or transfer operation data and referral or transfer diagnosis data;
storing an outpatient clinic visit record and an outpatient prescription record of any patient in a class corresponding to an outpatient event, wherein the outpatient clinic visit record comprises outpatient clinic diagnosis data and skin test allergy data, and the outpatient prescription record comprises outpatient prescription detail data;
storing the hospitalization diagnosis data of any patient, the hospitalization registration record and the infant hospitalization registration record in a class corresponding to the hospitalization event, wherein the hospitalization registration record comprises the bed data and the hospitalization advice data;
storing operation risk evaluation data, operation records, operation anesthesia records and operation nursing records of any patient in a class corresponding to a hand anesthesia event, wherein the operation records comprise operation detail data, operation diagnosis data, operation drainage material data, operation blood transfusion data and operation medication data, the operation anesthesia records comprise anesthesia data and anesthesia sign data, and the operation nursing records comprise operation nursing operation detail data and operation nursing observation detail data;
storing the data to be delivered of any patient in a class corresponding to the gynecological event, guiding the childbirth data, the uterine dissection operation data and the nursing data;
storing a blood transfusion application form record, blood group monitoring data, blood bank bleeding data, blood bank transfusion adverse reaction data, mobile nursing blood transfusion inspection data and mobile nursing blood transfusion data of any patient in a class corresponding to a blood transfusion recording event, wherein the blood transfusion application form record comprises blood transfusion examination diagnosis data and blood transfusion item data;
storing a physical sign record, physical examination data and a critical value record of any patient in a class corresponding to the vital sign monitoring event, wherein the physical sign record comprises physical sign result data, and the critical value record comprises critical value detail data;
storing a test application form record, specimen signing data and a test report record of any patient in a class corresponding to a test report event, wherein the test application form record comprises test application form corresponding report relation data and test item data, and the test report record comprises test report detail data, test bacteria result data and test drug sensitivity result data;
storing examination appointment data, examination application form records and examination report records of any patient in a class corresponding to an examination report event, wherein the examination application form records comprise examination application but expansion data, examination diagnosis data, report relation data and examination item data corresponding to the examination application forms, and the examination report records comprise examination report expansion data, examination report detail data, data of an examination index database, examination and examination report attachment data and examination medicine data;
storing Image data, Series data, inspection studio data and Patient data of any Patient in a class corresponding to the DICOM event.
Optionally, the retrieval request includes a retrieval information; or, the retrieval request includes a plurality of retrieval information and combinational logic;
any retrieval information comprises a field identifier, a retrieval value and retrieval logic;
the S102 includes:
s102-1, determining a plurality of corresponding medical events according to the field identification;
s102-2, determining corresponding data items in each medical event according to the retrieval values and the retrieval logic;
s102-3, determining business logic according to the corresponding medical event;
s102-4, carrying out logic processing on the corresponding data item according to the service logic to obtain a retrieval result.
Optionally, the S102-1 specifically is: and determining the medical event corresponding to the field identification according to the corresponding relation between the stored data and the field in the preset medical event.
Optionally, the medical event has an attribute;
the attributes of the electronic medical record event, the referral recording event, the outpatient event, the hospitalization event, the medical record home page event and the patient basic information event are basic attributes;
the attributes of a hand anesthesia event, a gynecological event, a blood transfusion recording event, a vital sign monitoring event, a test report event, an examination report event, a patient diagnosis event and a DICOM event are business attributes;
the S102-3 comprises:
s102-3-1, determining attributes corresponding to the medical events;
s102-3-2, the business logic between the corresponding medical events with the same attribute is logical OR, and the business logic between the corresponding medical events with different attributes is logical AND.
Optionally, the S102-4 includes:
s102-4-1, determining the corresponding weight of the corresponding medical event;
s102-4-2, for the retrieval event with the weight larger than the preset threshold, if the business logic is logical AND, the business logic is changed into logical OR;
and S102-4-3, performing logic processing on the corresponding data item according to the changed service logic to obtain a retrieval result.
Optionally, for any medical event i, the S102-4-1 includes:
niNumber included for said any medical event iDepending on the total number of items it is possible to,
the number of data items stored with specific data m included for said any medical event iiThe specific total amount of data stored for said any medical event i,
the specific data amount stored for the data item corresponding to the any medical event i;
In order to achieve the above purpose, the main technical solution adopted by the present invention further comprises:
an electronic device comprising a memory, a processor, a bus and a computer program stored on the memory and executable on the processor, the processor implementing the steps of any of the above methods when executing the program.
In order to achieve the above purpose, the main technical solution adopted by the present invention further comprises:
a computer storage medium having stored thereon a computer program which, when executed by a processor, carries out the steps of any of the methods as described above.
The invention has the beneficial effects that: the data in the distributed document database constructed by the ElasticSearch is retrieved, and the medical data of each patient are classified and stored by taking the patient identification as the main index and the medical event as the basis in the distributed document database, so that the medical event of the patient can be quickly and accurately positioned when the distributed document database is retrieved, and the accuracy of data retrieval is improved.
Drawings
Specific embodiments of the present application will be described below with reference to the accompanying drawings, in which:
FIG. 1 is a schematic diagram illustrating an event model schema provided by an embodiment of the present application;
FIG. 2 is a flow chart of a data retrieval method according to an embodiment of the present application;
fig. 3 shows a schematic structural diagram of an electronic device according to an embodiment of the present application.
Detailed Description
With the increase of medical data scale in geometric progression, in order to effectively store and efficiently utilize related data and promote higher-level medical information sharing based on a regional medical system, especially clinical data in medical information, a multi-center, networked and large-sample sharing platform is urgently needed to be established for effective management so as to provide support for the retrieval of trans-institution and trans-center patient data for hospitals, and meanwhile, when the clinical data are specially researched, a large amount of historical medical record information needs to be collected, sorted and analyzed to obtain related information such as disease treatment and the like, so that the medical quality and the diagnosis and treatment level are improved. Therefore, a data retrieval method for quickly and accurately locating the required health record information is needed.
Based on this, the application provides a data retrieval method, which is used for retrieving data in a distributed document database constructed by elastic search, and since the patient identification is used as a main index in the distributed document database and medical data of each patient is stored in a classified manner by taking the medical event as a basis, the medical event of the patient can be quickly and accurately positioned when the distributed document database is retrieved, and the accuracy of data retrieval is improved.
The data set retrieval method provided by the application is applied to a new generation health archive big data platform, the new generation health archive big data platform breaks through an original 'archive management' mode, various health related data and records are collected in a full amount, and on the basis of providing a data search and analysis engine, a model algorithm and processing capacity of big data analysis are fully utilized, valuable information is automatically extracted from mass data, and correlation analysis and trend analysis prediction are provided for health comprehensive management business and health service industry application.
A distributed document database is adopted in a new generation health record big data platform to store patient medical data. The distributed document database is built by elastic search.
The ElasticSearch is a high-performance full-text search server based on Lucene, and data documents submit XML data format files to a search engine server through an Http request to generate indexes. And searching the request through an Http Get operation, and returning a result in an XML format. It provides an API interface similar to Web-service externally, and the main characteristics include: the method has the advantages of high-efficiency and flexible caching function, vertical searching function, highlighted search result, improved usability by index replication, and capability of providing a set of powerful Data Schema to define fields, types and set text analysis.
Each field of the distributed document database constructed by the Elasticsearch can be indexed, and the data of each field can be searched, and the Elasticsearch can be transversely expanded to hundreds of servers to store and process PB-level data. A large amount of data can be stored, searched, and analyzed in an extremely short time.
The distributed document database takes a patient as core unified data, an event model is taken as a design mode to construct various diagnosis and treatment related record data, a clinical patient view module is established based on a health big data center, all historical diagnosis and treatment data of the patient are displayed in series through a patient main index, a user is helped to grasp the disease development condition of the patient on the whole, and various treatment and nursing conditions, the specification of a diagnosis and treatment plan, the execution condition, the clinical effect and the like of the patient are visually checked under the condition that the disease condition changes continuously. The data-based scientific research analysis comprehensive application is based on a clinical data center, a series of scientific research applications are developed according to different requirements of a specialist, and diagnosis and treatment rules are discovered and revealed through analysis of a large amount of data, so that the clinical curative effect is evaluated, and the clinical practice is guided more effectively. The data integration application taking management as a core is centered on data application requirements of all management departments of a whole worker, and summary data centralized display, detailed data analysis display and effective display of real-time index early warning data are performed around clinical affair data, clinical process data, operation data, scientific research data and service data, and an event model summary architecture can be shown as 1.
The new generation of health record big data platform can quickly construct indexes through the distributed document database in the data retrieval method provided by the application, has high-efficiency storage capacity, and further solves the performance bottleneck of storing massive structured and semi-structured medical data in the regional medical data center. The distributed document database has automatic load balancing capability and high-speed index retrieval capability, solves the query pressure of high concurrent big data of a regional big data platform, improves the overall concurrent data reading and writing performance of a data platform server, and greatly improves the query performance.
Meanwhile, structural styles of health archive big data medical data documents stored in the distributed document database are diversified, and the document has recorded structured data (EHR/EMR), unstructured and semi-structured document data in a plain text or PDF format, influence data in a DICOM (Digital Imaging and Communications in Medicine) format, novel omics data and the like, and the event model free mode can flexibly respond to data demand changes of all service systems.
The data retrieval method provided by the application can obviously improve the data processing capacity and the stability and efficiency of retrieval service, and solves the problems of data processing delay, overlong query time, data loss and the like in the traditional system. Taking more than 2000 pieces of data recorded in a distributed document database as an example, all health archive medical data documents of a certain organization and a certain patient are respectively retrieved on a single machine, and the time consumed by query is about 0.03 second and about 0.015 second respectively, so that the speed is improved by dozens of times to dozens of times compared with the existing query performance, and the advantages of big data retrieval performance can be better embodied in a high-concurrency query scene.
The distributed document database in the present application is built by elastic search for storing patient medical data.
In the distributed document database, the patient identification is used as a main index, and medical data of each patient is stored in a classified mode by taking the medical event as a basis.
Wherein the medical events include: electronic medical record events, referral recording events, outpatient events, hospitalization events, hand anesthesia events, gynecological events, patient basic information events, transfusion recording events, vital sign monitoring events, examination reporting events, medical record first page events, patient attendance events, and DICOM events.
Storing clinical document records in the corresponding class of the electronic medical record events, wherein the clinical document records comprise clinical document segment data and clinical document data.
And storing a referral or transfer record in a class corresponding to the referral record event, wherein the referral or transfer record comprises referral or transfer operation data and referral or transfer diagnosis data.
Storing clinic treatment records and clinic prescription records in the classes corresponding to the clinic events, wherein the clinic treatment records comprise clinic diagnosis data and skin test allergy data, and the clinic prescription records comprise clinic prescription detailed data.
The method comprises the steps of storing hospitalization diagnosis data, hospitalization clinic registration records and infant hospitalization clinic registration data in a class corresponding to hospitalization events, wherein the hospitalization clinic registration records comprise bed data and hospitalization advice data.
The method comprises the steps of storing operation risk assessment data, operation records, operation anesthesia records and operation nursing records in classes corresponding to hand anesthesia events, wherein the operation records comprise operation detail data, operation diagnosis data, operation drainage material data, operation blood transfusion data and operation medication data, the operation anesthesia records comprise anesthesia data and anesthesia sign data, and the operation nursing records comprise operation nursing operation detail data and operation nursing observation detail data.
Storing the data to be delivered in the class corresponding to the gynecological events, guiding the delivery data, the data of the uterine dissection operation and the nursing data.
Storing blood transfusion application form records, blood group monitoring data of a blood bank, blood bank bleeding data, blood bank transfusion adverse reaction data, mobile nursing blood transfusion inspection data and mobile nursing blood transfusion data in classes corresponding to the blood transfusion recording events, wherein the blood transfusion application form records comprise blood transfusion inspection diagnosis data and blood transfusion item data.
And storing physical sign records, physical examination data and critical value records in the classes corresponding to the vital sign monitoring events, wherein the physical sign records comprise physical sign result data, and the critical value records comprise critical value detail data.
Storing an inspection application form record, specimen signing data and an inspection report record in the class corresponding to the inspection report event, wherein the inspection application form record comprises inspection application form corresponding report relation data and inspection project data, and the inspection report record comprises inspection report detail data, inspection bacteria result data and inspection drug sensitivity result data.
Storing examination appointment data, examination application form records and examination report records in classes corresponding to examination report events, wherein the examination application form records comprise examination application expansion data, examination diagnosis data, examination application form corresponding report relation data and examination item data, and the examination report records comprise examination report expansion data, examination report detail data, examination index database data, examination report accessory data and examination medicine data.
Image data, Series data, Study data, Patient data are stored in the class corresponding to the DICOM event.
For any patient j, for example, the identity of any patient j is used as the primary index,
and storing the clinical document record of any patient j in the class corresponding to the electronic medical record event, wherein the clinical document record comprises clinical document segment data and clinical document data.
And storing the referral or transfer record of any patient j in the class corresponding to the referral record event, wherein the referral or transfer record comprises referral or transfer operation data and referral or transfer diagnosis data.
Storing the clinic visit record and the clinic prescription record of any patient j in the class corresponding to the clinic event, wherein the clinic visit record comprises clinic diagnosis data and skin test allergy data, and the clinic prescription record comprises clinic prescription detail data.
The hospital diagnosis data of any patient j, the hospital treatment registration record and the infant hospital treatment registration record are stored in the class corresponding to the hospital event, and the hospital treatment registration record comprises the bed position data and the hospital advice data.
The method comprises the steps of storing operation risk assessment data, operation records, operation anesthesia records and operation nursing records of any patient j in a class corresponding to a hand anesthesia event, wherein the operation records comprise operation detail data, operation diagnosis data, operation drainage material data, operation blood transfusion data and operation medication data, the operation anesthesia records comprise anesthesia data and anesthesia sign data, and the operation nursing records comprise operation nursing operation detail data and operation nursing observation detail data.
Storing the data to be delivered of any patient j in the class corresponding to the gynecological event, guiding the childbirth data, the uterine dissection operation data and the nursing data.
And storing a blood transfusion application form record of any patient j, blood type monitoring data of a blood bank, blood bank bleeding data, blood bank blood transfusion adverse reaction data, mobile nursing blood transfusion inspection data and mobile nursing blood transfusion data in the class corresponding to the blood transfusion recording event, wherein the blood transfusion application form record comprises blood transfusion examination diagnosis data and blood transfusion item data.
And storing the physical sign record, physical examination data and critical value record of any patient j in the class corresponding to the vital sign monitoring event, wherein the physical sign record comprises physical sign result data, and the critical value record comprises critical value detail data.
And storing a test application form record, specimen signing data and a test report record of any patient j in the class corresponding to the test report event, wherein the test application form record comprises test application form corresponding report relation data and test item data, and the test report record comprises test report detail data, test bacteria result data and test drug sensitivity result data.
The method comprises the steps of storing examination appointment data, examination application form records and examination report records of any patient j in a class corresponding to an examination report event, wherein the examination application form records comprise examination application expansion data, examination diagnosis data, report relation data and examination item data corresponding to the examination application forms, and the examination report records comprise examination report expansion data, examination report detail data, data of an examination index database, examination and examination report attachment data and examination and medication data.
Image data, Series data, Study data and Patient data of any Patient j are stored in a class corresponding to the DICOM event.
In addition, medical events have attributes. The attributes of the electronic medical record event, the referral recording event, the outpatient event, the hospitalization event, the medical record home page event and the patient basic information event are basic attributes. The attributes of hand anesthesia events, gynecological events, transfusion recording events, vital sign monitoring events, examination report events, patient diagnosis events, and DICOM events are business attributes.
Based on the above distributed document database structure, referring to fig. 2, the data retrieval method provided by this embodiment is as follows:
s101, a retrieval request is obtained.
Wherein, the retrieval request comprises retrieval information. Alternatively, the search request includes a plurality of search information and combination logic.
Any retrieval information comprises field identification, retrieval value and retrieval logic.
For example, the retrieval request is: men and women are among those who have hypertensive diabetes over the age of 60.
The search information comprises 4 search information, the 1 st search information is over 60 years old, the field identification is age, the search value is 60, and the search logic is greater than. The 2 nd search information is of hypertension, wherein the field is identified as a disease, the search value is of hypertension, and the search logic is equal to. The 3 rd search information is for diabetes, where the field is identified as a condition, the search value is for diabetes, and the search logic is equal. The 4 th search information is male-female ratio, wherein the field identification is sex, the search value is male and female, and the search logic is grouping.
The combinational logic among the 1 st search information, the 2 nd search information and the 3 rd search information is a logical and, and the combinational logic among the 1 st search information, the 2 nd search information, the 3 rd search information and the 4 th search information is a group.
And S102, searching in the distributed document database according to the searching request to obtain a searching result.
Specifically, the implementation manner of S102 is:
and S102-1, determining a plurality of corresponding medical events according to the field identifications.
And if the retrieval information is multiple, respectively determining the medical events corresponding to the field identifications in each piece of retrieval information.
Taking the field identifier t in any retrieval information as an example, determining the medical event corresponding to the field identifier t according to the corresponding relation between the stored data and the field in the preset medical event.
For example, the field identification t is the age in the 1 st search information, and the medical event containing the age field is determined as the corresponding medical event. Such as electronic medical record, referral record, outpatient service, hospitalization, hand anesthesia, obstetrics, basic patient information, transfusion, vital sign, examination report, medical record, patient visit, DICOM and other related applications, documents and reports all contain patient age, therefore, electronic medical record event, referral record event, outpatient service event, hospitalization event, hand anesthesia event, obstetrics' events, basic patient information event, transfusion record event, vital sign monitoring event, examination report event, first page event of medical record, patient visit event, DICOM event all include age field. The medical events corresponding to the ages in the 1 st retrieval information are electronic medical record events, referral recording events, outpatient events, hospitalization events, hand anesthesia events, obstetric events, patient basic information events, transfusion recording events, vital sign monitoring events, inspection reporting events, examination reporting events, medical record first page events, patient diagnosis events and DICOM events.
In this step, all data corresponding to the search field can be found.
And S102-2, determining corresponding data items in each medical event according to the retrieval values and the retrieval logic.
And if the retrieval information is multiple, determining the data item corresponding to each piece of retrieval information in each medical event according to the retrieval value and the retrieval logic in each piece of retrieval information.
Still taking the 1 st retrieved information as an example, all data with age greater than 60 are determined in electronic medical record event, referral recording event, outpatient event, hospitalization event, hand anesthesia event, obstetrical event, patient basic information event, transfusion recording event, vital sign monitoring event, inspection reporting event, examination reporting event, medical record first page event, patient hospitalization event, DICOM event.
And S102-3, determining business logic according to the corresponding medical events.
And if the retrieval information is multiple, determining the business logic of each retrieval information according to the medical event corresponding to each retrieval information.
S102-3-1, determining the corresponding attribute of the corresponding medical event.
S102-3-2, the business logic between the corresponding medical events with the same attribute is logical OR, and the business logic between the corresponding medical events with different attributes is logical AND.
Still taking the 1 st retrieval information as an example, the attributes of the electronic medical record event, the referral recording event, the outpatient event, the hospitalization event, the medical record first page event and the patient basic information event are basic attributes. The attributes of hand anesthesia events, gynecological events, transfusion recording events, vital sign monitoring events, examination report events, patient diagnosis events, and DICOM events are business attributes. Therefore, the events of the electronic medical record, the referral recording events, the outpatient events, the hospitalization events, the first page events of the medical record, the basic information events of the patients are in a logical or relationship, the hand anesthesia events, the gynecological events, the transfusion recording events, the vital sign monitoring events, the inspection reporting events, the examination reporting events, the patient seeing events and the DICOM events are also in a logical or relationship, and the events of any basic attribute and the events of any service attribute are in a logical and relationship. Such as a logical and relationship between out-patient events and DICOM events.
And S102-4, performing logic processing according to the data items corresponding to the service logic to obtain a retrieval result.
The specific implementation manner of the step is as follows:
s102-4-1, determining the corresponding weight of the corresponding medical event.
If there are a plurality of pieces of search information, the weight of the medical event corresponding to each piece of search information is determined.
For example, for any medical event i, S102-4-1 includes:
niThe total number of data items included for any medical event i,
number of data items stored with specific data, m, included for any medical event iiThe specific amount of data stored for any medical event i,
the specific amount of data stored for the data item corresponding to any medical event i.
Still taking the electronic medical record event in the 1 st retrieval information as an example,
the event of the electronic medical record is taken as a basic attribute,
the electronic medical record event comprises a clinical document record, and the clinical document record comprises clinical document segment data andclinical document data, hence ni＝2。
If only the clinical document data is stored in the electronic medical record event and the clinical document segment data is not stored, the electronic medical record event is judged to be a clinical document segment event
If 3 pieces of data are stored in the electronic medical record event, m isiSince only clinical document data is stored, 3, therefore,
also 3.
Of events in electronic medical records
S102-4-2, for the retrieval event with the weight larger than the preset threshold, if the business logic is logical AND, the business logic is changed into logical OR.
After the weight of the medical event corresponding to each retrieved information is obtained, a correction is made to the business logic of each retrieved information.
If there are a plurality of search information, the step corrects the business logic of each search information according to the weight of the medical event corresponding to each search information.
Still taking the electronic medical record event in the 1 st retrieval information as an example, if the weight of the electronic medical record event is less than the threshold, all the logics and the logics corresponding to the electronic medical record event are changed into logic or.
The threshold is empirically set according to the event, and can describe the importance of the medical event.
In this step, the medical event with higher weight is considered as an important medical event, and therefore, the medical event is an event which must appear in the search result, and the logical and is changed into the logical or, so that the medical event is ensured to appear in the search result.
And S102-4-3, performing logic processing according to the data item corresponding to the changed business logic to obtain a retrieval result.
For example, the proportion of men and women among patients with hypertensive diabetes aged 60 or older is searched. The search information comprises 4 search information, the 1 st search information is over 60 years old, the field identification is age, the search value is 60, and the search logic is greater than. The 2 nd search information is of hypertension, wherein the field is identified as a disease, the search value is of hypertension, and the search logic is equal to. The 3 rd search information is for diabetes, where the field is identified as a condition, the search value is for diabetes, and the search logic is equal. The 4 th search information is male-female ratio, wherein the field identification is sex, the search value is male and female, and the search logic is grouping. The combinational logic among the 1 st search information, the 2 nd search information and the 3 rd search information is a logical and, and the combinational logic among the 1 st search information, the 2 nd search information, the 3 rd search information and the 4 th search information is a group.
Therefore, the first data item of age greater than 60 is retrieved first, the second data item of hypertension has the third data item of diabetes, and the fourth data item of gender is male and female. And operating the first data item, the second data item and the third data item to obtain a fifth data item. And grouping the fifth data item by the fourth data item disable value.
When the first data item is obtained, all data of the electronic medical record event, the referral recording event, the outpatient event, the hospitalization event, the hand anesthesia event, the gynecological event, the patient basic information event, the transfusion recording event, the vital sign monitoring event, the inspection reporting event, the medical record first page event, the patient hospitalization event and the DICOM event with the determined age being more than 60 are subjected to business logic processing after being changed.
Taking an electronic medical record event and a referral recording event as examples, if the service logic is logical and, performing and operation on the data with the age of more than 60 in the electronic medical record event and the data with the age of more than 60 in the referral recording event to obtain a result.
The data retrieval method provided by the embodiment is different from the existing retrieval scheme, considers the business relation among all events, and simultaneously adjusts the business relation according to the importance degree of the events to finally obtain the retrieval result, thereby ensuring the accurate positioning of the retrieval result and the medical treatment time and improving the accuracy of data retrieval.
According to the data retrieval method provided by the embodiment, the medical record retrieval requirements of doctors are known by means of rich experience accumulation of big data processing and analysis, the retrieval input model and rules are explained by combining with the NLP processing technology, natural language can be accurately converted into structural information expressed by frame semantics, automatic long-chain reasoning, intention identification and cause and effect analysis are realized, and meanwhile, the engine can understand the field more through learning. By inputting a question-lexical analysis-syntactic analysis-semantic expression sequence-conversion data query condition, a semantic understanding model taking a classification model and a sequence label as a core can accurately convert a natural language into structural information expressed by frame semantics, and queries on a database, so that automatic long-chain reasoning, intention identification and cause-effect analysis are realized, clue derivation is automatically completed, and the retrieval data of a user is quickly met.
The data retrieval method provided by the embodiment solves the automatic interpretation task of the text with the semantic meaning for a lightweight and effective knowledge base, and can clearly encode the complete semantic meaning of the complex query graph. The semantic representation of the question in the model is enriched by incorporating dependency grammar analysis information, and model analysis is performed to verify the validity thereof. And generating all candidate query graphs based on a staged mode so as to solve semantic structure representation and semantic matching calculation of the complex question sentence.
According to the method provided by the embodiment, the data in the distributed document database constructed by the elastic search is retrieved, and the patient identifier is used as the main index in the distributed document database, and the medical data of each patient is classified and stored according to the medical event, so that the medical event of the patient can be quickly and accurately positioned when the distributed document database is retrieved, and the accuracy of data retrieval is improved.
Referring to fig. 3, the present embodiment provides an electronic apparatus including: memory 301, processor 302, bus 303, and computer programs stored on memory 301 and executable on processor 302.
The processor 302, when executing the program, implements the following method:
s101, acquiring a retrieval request;
s102, searching in a distributed document database according to the searching request to obtain a searching result;
the distributed document database is constructed by elastic search and used for storing patient medical data;
in the distributed document database, the patient identification is used as a main index, and medical data of each patient is stored in a classified mode by taking the medical event as a basis.
Optionally, the medical event comprises: electronic medical record events, referral recording events, outpatient events, hospitalization events, hand anesthesia events, gynecological events, patient basic information events, transfusion recording events, vital sign monitoring events, exam reporting events, medical record first page events, patient visit events, digital imaging and communications in DICOM events.
Optionally, the step of using the patient identifier as a main index and storing the medical data of each patient according to the medical event by classification includes:
for any patient, the identity of any patient is used as the primary index,
storing a clinical document record of any patient in a class corresponding to the electronic medical record event, wherein the clinical document record comprises clinical document segment data and clinical document data;
storing the referral or transfer record of any patient in the corresponding class of the referral record event, wherein the referral or transfer record comprises referral or transfer operation data and referral or transfer diagnosis data;
storing an outpatient clinic record and an outpatient clinic prescription record of any patient in a class corresponding to the outpatient clinic event, wherein the outpatient clinic record comprises outpatient clinic diagnosis data and skin test allergy data, and the outpatient clinic prescription record comprises outpatient clinic prescription detail data;
storing the hospitalization diagnosis data of any patient in a class corresponding to the hospitalization event, wherein the hospitalization registration record comprises bed data and hospitalization advice data;
storing operation risk evaluation data, operation records, operation anesthesia records and operation nursing records of any patient in a class corresponding to a hand anesthesia event, wherein the operation records comprise operation detail data, operation diagnosis data, operation drainage material data, operation blood transfusion data and operation medication data, the operation anesthesia records comprise anesthesia data and anesthesia sign data, and the operation nursing records comprise operation nursing operation detail data and operation nursing observation detail data;
storing the data to be delivered of any patient in the class corresponding to the gynecological event, guiding the childbirth data, the uterine dissection operation data and the nursing data;
storing a blood transfusion application form record of any patient, blood type monitoring data of a blood bank, blood bank bleeding data, blood bank transfusion adverse reaction data, mobile nursing blood transfusion inspection data and mobile nursing blood transfusion data in a class corresponding to a blood transfusion recording event, wherein the blood transfusion application form record comprises blood transfusion examination diagnosis data and blood transfusion item data;
storing a physical sign record, physical examination data and a critical value record of any patient in a class corresponding to the vital sign monitoring event, wherein the physical sign record comprises physical sign result data, and the critical value record comprises critical value detail data;
storing a test application form record, specimen signing data and a test report record of any patient in a class corresponding to a test report event, wherein the test application form record comprises test application form corresponding report relation data and test item data, and the test report record comprises test report detail data, test bacteria result data and test drug sensitivity result data;
storing examination appointment data of any patient, examination application form records and examination report records in a class corresponding to an examination report event, wherein the examination application form records comprise examination application but expansion data, examination diagnosis data, report relation data and examination item data corresponding to the examination application forms, and the examination report records comprise examination report expansion data, examination report detail data, data of an examination index database, examination report attachment data and examination medicine data;
image data of any Patient, Series data, inspection studio data and Patient data are stored in a class corresponding to the DICOM event.
Optionally, the retrieval request includes a retrieval information; or the retrieval request comprises a plurality of retrieval information and combinational logic;
any retrieval information comprises a field identifier, a retrieval value and retrieval logic;
s102 includes:
s102-1, determining a plurality of corresponding medical events according to the field identification;
s102-2, determining corresponding data items in each medical event according to the retrieval values and the retrieval logic;
s102-3, determining business logic according to the corresponding medical event;
and S102-4, performing logic processing on the corresponding data item according to the service logic to obtain a retrieval result.
Optionally, S102-1 specifically is: and determining the medical event corresponding to the field identification according to the corresponding relation between the stored data and the field in the preset medical event.
Optionally, the medical event has an attribute;
the attributes of the electronic medical record event, the referral recording event, the outpatient event, the hospitalization event, the medical record home page event and the patient basic information event are basic attributes;
the attributes of a hand anesthesia event, a gynecological event, a blood transfusion recording event, a vital sign monitoring event, a test report event, an examination report event, a patient diagnosis event and a DICOM event are business attributes;
s102-3 includes:
s102-3-1, determining attributes corresponding to the medical events;
s102-3-2, the business logic between the corresponding medical events with the same attribute is logical OR, and the business logic between the corresponding medical events with different attributes is logical AND.
Optionally, S102-4 comprises:
s102-4-1, determining the corresponding weight of the corresponding medical event;
s102-4-2, for the retrieval event with the weight larger than the preset threshold, if the business logic is logical AND, the business logic is changed into logical OR;
and S102-4-3, performing logic processing on the corresponding data item according to the changed business logic to obtain a retrieval result.
Optionally, for any medical event i, S102-4-1 comprises:
niThe total number of data items included for any medical event i,
number of data items stored with specific data, m, included for any medical event iiThe specific amount of data stored for any medical event i,
the specific data amount stored for the data item corresponding to any medical event i;
The electronic device provided by the embodiment retrieves data in a distributed document database constructed by elastic search, and since the patient identifier is used as a main index in the distributed document database and medical data of each patient is stored in a classified manner according to the medical event, the medical event of the patient can be quickly and accurately positioned when the distributed document database is retrieved, and the accuracy of data retrieval is improved.
The present embodiments provide a computer storage medium that performs the following operations:
s101, acquiring a retrieval request;
s102, searching in a distributed document database according to the searching request to obtain a searching result;
the distributed document database is constructed by elastic search and used for storing patient medical data;
in the distributed document database, the patient identification is used as a main index, and medical data of each patient is stored in a classified mode by taking the medical event as a basis.
Optionally, the medical event comprises: electronic medical record events, referral recording events, outpatient events, hospitalization events, hand anesthesia events, gynecological events, patient basic information events, transfusion recording events, vital sign monitoring events, exam reporting events, medical record first page events, patient visit events, digital imaging and communications in DICOM events.
Optionally, the step of using the patient identifier as a main index and storing the medical data of each patient according to the medical event by classification includes:
for any patient, the identity of any patient is used as the primary index,
storing a clinical document record of any patient in a class corresponding to the electronic medical record event, wherein the clinical document record comprises clinical document segment data and clinical document data;
storing the referral or transfer record of any patient in the corresponding class of the referral record event, wherein the referral or transfer record comprises referral or transfer operation data and referral or transfer diagnosis data;
storing an outpatient clinic record and an outpatient clinic prescription record of any patient in a class corresponding to the outpatient clinic event, wherein the outpatient clinic record comprises outpatient clinic diagnosis data and skin test allergy data, and the outpatient clinic prescription record comprises outpatient clinic prescription detail data;
storing the hospitalization diagnosis data of any patient in a class corresponding to the hospitalization event, wherein the hospitalization registration record comprises bed data and hospitalization advice data;
storing operation risk evaluation data, operation records, operation anesthesia records and operation nursing records of any patient in a class corresponding to a hand anesthesia event, wherein the operation records comprise operation detail data, operation diagnosis data, operation drainage material data, operation blood transfusion data and operation medication data, the operation anesthesia records comprise anesthesia data and anesthesia sign data, and the operation nursing records comprise operation nursing operation detail data and operation nursing observation detail data;
storing the data to be delivered of any patient in the class corresponding to the gynecological event, guiding the childbirth data, the uterine dissection operation data and the nursing data;
storing a blood transfusion application form record of any patient, blood type monitoring data of a blood bank, blood bank bleeding data, blood bank transfusion adverse reaction data, mobile nursing blood transfusion inspection data and mobile nursing blood transfusion data in a class corresponding to a blood transfusion recording event, wherein the blood transfusion application form record comprises blood transfusion examination diagnosis data and blood transfusion item data;
storing a physical sign record, physical examination data and a critical value record of any patient in a class corresponding to the vital sign monitoring event, wherein the physical sign record comprises physical sign result data, and the critical value record comprises critical value detail data;
storing a test application form record, specimen signing data and a test report record of any patient in a class corresponding to a test report event, wherein the test application form record comprises test application form corresponding report relation data and test item data, and the test report record comprises test report detail data, test bacteria result data and test drug sensitivity result data;
storing examination appointment data of any patient, examination application form records and examination report records in a class corresponding to an examination report event, wherein the examination application form records comprise examination application but expansion data, examination diagnosis data, report relation data and examination item data corresponding to the examination application forms, and the examination report records comprise examination report expansion data, examination report detail data, data of an examination index database, examination report attachment data and examination medicine data;
image data of any Patient, Series data, inspection studio data and Patient data are stored in a class corresponding to the DICOM event.
Optionally, the retrieval request includes a retrieval information; or the retrieval request comprises a plurality of retrieval information and combinational logic;
any retrieval information comprises a field identifier, a retrieval value and retrieval logic;
s102 includes:
s102-1, determining a plurality of corresponding medical events according to the field identification;
s102-2, determining corresponding data items in each medical event according to the retrieval values and the retrieval logic;
s102-3, determining business logic according to the corresponding medical event;
and S102-4, performing logic processing on the corresponding data item according to the service logic to obtain a retrieval result.
Optionally, S102-1 specifically is: and determining the medical event corresponding to the field identification according to the corresponding relation between the stored data and the field in the preset medical event.
Optionally, the medical event has an attribute;
the attributes of the electronic medical record event, the referral recording event, the outpatient event, the hospitalization event, the medical record home page event and the patient basic information event are basic attributes;
the attributes of a hand anesthesia event, a gynecological event, a blood transfusion recording event, a vital sign monitoring event, a test report event, an examination report event, a patient diagnosis event and a DICOM event are business attributes;
s102-3 includes:
s102-3-1, determining attributes corresponding to the medical events;
s102-3-2, the business logic between the corresponding medical events with the same attribute is logical OR, and the business logic between the corresponding medical events with different attributes is logical AND.
Optionally, S102-4 comprises:
s102-4-1, determining the corresponding weight of the corresponding medical event;
s102-4-2, for the retrieval event with the weight larger than the preset threshold, if the business logic is logical AND, the business logic is changed into logical OR;
and S102-4-3, performing logic processing on the corresponding data item according to the changed business logic to obtain a retrieval result.
Optionally, for any medical event i, S102-4-1 comprises:
niThe total number of data items included for any medical event i,
number of data items stored with specific data, m, included for any medical event iiThe specific amount of data stored for any medical event i,
the specific data amount stored for the data item corresponding to any medical event i;
The computer storage medium provided by this embodiment retrieves data in a distributed document database constructed by elastic search, and since the patient identifier is used as a primary index in the distributed document database and medical data of each patient is stored in a classified manner based on the medical event, the medical event of the patient can be quickly and accurately located when the distributed document database is retrieved, and the accuracy of data retrieval is improved.
It is to be understood that the invention is not limited to the specific arrangements and instrumentality described above and shown in the drawings. A detailed description of known methods is omitted herein for the sake of brevity. In the above embodiments, several specific steps are described and shown as examples. However, the method processes of the present invention are not limited to the specific steps described and illustrated, and those skilled in the art can make various changes, modifications and additions or change the order between the steps after comprehending the spirit of the present invention.
It should also be noted that the exemplary embodiments mentioned in this patent describe some methods or systems based on a series of steps or devices. However, the present invention is not limited to the order of the above-described steps, that is, the steps may be performed in the order mentioned in the embodiments, may be performed in an order different from the order in the embodiments, or may be performed simultaneously.
Finally, it should be noted that: the above-mentioned embodiments are only used for illustrating the technical solution of the present invention, and not for limiting the same; although the present invention has been described in detail with reference to the foregoing embodiments, it will be understood by those of ordinary skill in the art that: the technical solutions described in the foregoing embodiments may still be modified, or some or all of the technical features may be equivalently replaced; and the modifications or the substitutions do not make the essence of the corresponding technical solutions depart from the scope of the technical solutions of the embodiments of the present invention.
Claims (6)
1. A method for data retrieval, the method comprising:
s101, acquiring a retrieval request;
s102, searching in a distributed document database according to the searching request to obtain a searching result;
the distributed document database is constructed by elastic search and used for storing patient medical data;
in the distributed document database, the patient identification is used as a main index, and medical data of each patient are stored in a classified manner by taking a medical event as a basis;
the medical events include: electronic medical record events, referral recording events, outpatient events, hospitalization events, hand anesthesia events, gynecological events, patient basic information events, transfusion recording events, vital sign monitoring events, examination reporting events, medical record first page events, patient attendance events, digital imaging and communications in medicine (DICOM) events;
the retrieval request comprises retrieval information; or, the retrieval request includes a plurality of retrieval information and combinational logic;
any retrieval information comprises a field identifier, a retrieval value and retrieval logic;
the S102 includes:
s102-1, determining a plurality of corresponding medical events according to the field identification;
s102-2, determining corresponding data items in each medical event according to the retrieval values and the retrieval logic;
s102-3, determining business logic according to the corresponding medical event;
s102-4, performing logic processing on the corresponding data item according to the service logic to obtain a retrieval result;
the medical event has an attribute;
the attributes of the electronic medical record event, the referral recording event, the outpatient event, the hospitalization event, the medical record home page event and the patient basic information event are basic attributes;
the attributes of a hand anesthesia event, a gynecological event, a blood transfusion recording event, a vital sign monitoring event, a test report event, an examination report event, a patient diagnosis event and a DICOM event are business attributes;
the S102-3 comprises:
s102-3-1, determining attributes corresponding to the medical events;
s102-3-2, the business logic between the corresponding medical events with the same attribute is logical OR, and the business logic between the corresponding medical events with different attributes is logical AND;
s102-4-1, determining the corresponding weight of the corresponding medical event;
s102-4-2, for the medical event with the weight larger than the preset threshold, if the business logic is logical AND, the business logic is changed into logical OR;
and S102-4-3, performing logic processing on the corresponding data item according to the changed service logic to obtain a retrieval result.
2. The method of claim 1, wherein the using the patient identification as a primary index and the categorizing the medical data for each patient based on the medical event comprises:
for any patient, using the identity of said any patient as a primary index,
storing the clinical document record of any patient in a class corresponding to the electronic medical record event, wherein the clinical document record comprises clinical document segment data and clinical document data;
storing a referral or transfer record of any patient in a class corresponding to a referral record event, wherein the referral or transfer record comprises referral or transfer operation data and referral or transfer diagnosis data;
storing an outpatient clinic visit record and an outpatient prescription record of any patient in a class corresponding to an outpatient event, wherein the outpatient clinic visit record comprises outpatient clinic diagnosis data and skin test allergy data, and the outpatient prescription record comprises outpatient prescription detail data;
storing the hospitalization diagnosis data of any patient, the hospitalization registration record and the infant hospitalization registration record in a class corresponding to the hospitalization event, wherein the hospitalization registration record comprises the bed data and the hospitalization advice data;
storing operation risk evaluation data, operation records, operation anesthesia records and operation nursing records of any patient in a class corresponding to a hand anesthesia event, wherein the operation records comprise operation detail data, operation diagnosis data, operation drainage material data, operation blood transfusion data and operation medication data, the operation anesthesia records comprise anesthesia data and anesthesia sign data, and the operation nursing records comprise operation nursing operation detail data and operation nursing observation detail data;
storing the data to be delivered of any patient in a class corresponding to the gynecological event, guiding the childbirth data, the uterine dissection operation data and the nursing data;
storing a blood transfusion application form record, blood group monitoring data, blood bank bleeding data, blood bank transfusion adverse reaction data, mobile nursing blood transfusion inspection data and mobile nursing blood transfusion data of any patient in a class corresponding to a blood transfusion recording event, wherein the blood transfusion application form record comprises blood transfusion examination diagnosis data and blood transfusion item data;
storing a physical sign record, physical examination data and a critical value record of any patient in a class corresponding to the vital sign monitoring event, wherein the physical sign record comprises physical sign result data, and the critical value record comprises critical value detail data;
storing a test application form record, specimen signing data and a test report record of any patient in a class corresponding to a test report event, wherein the test application form record comprises test application form corresponding report relation data and test item data, and the test report record comprises test report detail data, test bacteria result data and test drug sensitivity result data;
storing examination appointment data, examination application form records and examination report records of any patient in a class corresponding to an examination report event, wherein the examination application form records comprise examination application form expansion data, examination diagnosis data, examination application form corresponding report relation data and examination item data, and the examination report records comprise examination report expansion data, examination report detail data, examination index database data, examination report attachment data and examination medication data;
storing Image data, Series data, inspection studio data and Patient data of any Patient in a class corresponding to the DICOM event.
3. The method according to claim 1, wherein S102-1 is specifically: and determining the medical event corresponding to the field identification according to the corresponding relation between the stored data and the field in the preset medical event.
4. The method according to claim 1, wherein for any medical event i, the S102-4-1 comprises:
the above-mentioned
niThe total number of data items included for said any medical event i,
the number of data items stored with specific data m included for said any medical event iiThe specific total amount of data stored for said any medical event i,
the specific data amount stored for the data item corresponding to the any medical event i;
5. An electronic device comprising a memory, a processor, a bus and a computer program stored on the memory and executable on the processor, which when executed by the processor implements the method of any of claims 1-4.
6. A computer storage medium having a computer program stored thereon, characterized in that: the program when executed by a processor implementing the method of any one of claims 1 to 4.
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| CN110955711A (en) * | 2019-11-26 | 2020-04-03 | 南京甄视智能科技有限公司 | Search method and device capable of dynamic expansion |
| CN111161815A (en) * | 2019-12-27 | 2020-05-15 | 深圳中兴网信科技有限公司 | Medical data detection method, device, terminal and computer-readable storage medium |
| CN110931136B (en) * | 2020-01-21 | 2020-06-19 | 医渡云（北京）技术有限公司 | Event searching method and device, computer medium and electronic equipment |
| CN112635007A (en) * | 2020-12-21 | 2021-04-09 | 山东众阳健康科技集团有限公司 | Hospital integration method and system with patient as center |
| CN112669926B (en) * | 2020-12-30 | 2023-08-08 | 众阳健康科技集团有限公司 | Medical real-time data transmission method and system |
| TWI790576B (en) * | 2021-03-23 | 2023-01-21 | 中國信託商業銀行股份有限公司 | Doctor order information retrieval system |
| CN113314229A (en) * | 2021-05-26 | 2021-08-27 | 北京京东拓先科技有限公司 | Data processing method and device, electronic equipment and storage medium |
| CN113611383B (en) * | 2021-08-20 | 2024-02-02 | 深圳平安智慧医健科技有限公司 | Medical information acquisition method, device, electronic equipment and storage medium |
| CN115148322A (en) * | 2022-08-31 | 2022-10-04 | 神州医疗科技股份有限公司 | Clinical data storage method and system of clinical medical universal data structure model |
| CN115458103B (en) * | 2022-09-05 | 2024-03-22 | 北京百度网讯科技有限公司 | Medical data processing method, medical data processing device, electronic equipment and readable storage medium |
| CN116563039A (en) * | 2023-07-06 | 2023-08-08 | 山东贝森医院管理咨询有限公司 | Medical insurance management method and system based on DRG/DIP |
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