CN109616168A - A kind of medical field Intelligent management model construction method based on electronic health record - Google Patents

A kind of medical field Intelligent management model construction method based on electronic health record Download PDF

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Publication number
CN109616168A
CN109616168A CN201811536456.4A CN201811536456A CN109616168A CN 109616168 A CN109616168 A CN 109616168A CN 201811536456 A CN201811536456 A CN 201811536456A CN 109616168 A CN109616168 A CN 109616168A
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data
intelligent management
management model
health record
electronic health
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闫健卓
杜小雪
谭绍峰
贺东东
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Beijing University of Technology
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Beijing University of Technology
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    • GPHYSICS
    • G16INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
    • G16HHEALTHCARE INFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR THE HANDLING OR PROCESSING OF MEDICAL OR HEALTHCARE DATA
    • G16H10/00ICT specially adapted for the handling or processing of patient-related medical or healthcare data
    • G16H10/60ICT specially adapted for the handling or processing of patient-related medical or healthcare data for patient-specific data, e.g. for electronic patient records
    • GPHYSICS
    • G16INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
    • G16HHEALTHCARE INFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR THE HANDLING OR PROCESSING OF MEDICAL OR HEALTHCARE DATA
    • G16H50/00ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics
    • G16H50/70ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for mining of medical data, e.g. analysing previous cases of other patients

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  • Engineering & Computer Science (AREA)
  • Health & Medical Sciences (AREA)
  • Medical Informatics (AREA)
  • Public Health (AREA)
  • Epidemiology (AREA)
  • General Health & Medical Sciences (AREA)
  • Primary Health Care (AREA)
  • Data Mining & Analysis (AREA)
  • Biomedical Technology (AREA)
  • Databases & Information Systems (AREA)
  • Pathology (AREA)
  • Information Retrieval, Db Structures And Fs Structures Therefor (AREA)

Abstract

The invention discloses a kind of medical field Intelligent management model construction method based on electronic health record, this method mainly include the following steps: to manage data needed for exporting in systems, derived data are stored in the form of Excel table.Derived data are subjected to data cleansing, data integration, data conversion, hough transformation, eventually form target data set result database.Optimal algorithm is chosen after carrying out data mining analysis comparison to result database using traditional data mining algorithm and is optimized, and is chosen most correlative factor using the algorithm chosen and is constructed Intelligent management model.The present invention faces a large amount of structurings and unstructured electronic health record information, summarizes the data cleansing process of complete set in data preprocessing phase, lays a solid foundation for the building of intelligent management model construction.

Description

A kind of medical field Intelligent management model construction method based on electronic health record
Technical field
The present invention relates to the buildings of medical field model method, are related to a kind of intelligence pipe of medical field based on electronic health record Manage model building method, the in particular to medical Intelligent management model structure of a kind of random forests algorithm indicator combination based on optimization Construction method.
Background technique
It is several for managing patient for medical field Intelligent management model construction method, commonly referred to as clinical pattern A possibility that various complication of Nian Houqi are fallen ill and order of occurrence etc..There is more grind in foreign countries for this class model at present Study carefully, and develop and form some assessment softwares, the more well-known perspective diabetes study diabetes for having UK Classic are pre- Model (UKPDS) model is surveyed, which is the prediction for the diagnosis and treatment of type II diabetes difference carried out in Britain in 1977 Property multicenter randomized control clinical trial group research, research object be related to 23 research points of Britain amount to 5120 diabetics, last 20 Year, until terminating for 1997.The model is common mainly for 7 kinds of the Major Clinical index (blood glucose, blood pressure, blood lipid etc.) of diabetes Complication (apoplexy, coronary heart disease, myocardial infarction, heart failure, diabetic foot, nephrosis and eye disease) and associated death event generation Probability and time of occurrence are simulated, so that can study strict glycemic control reduce the morbidity of type 2 diabetic patient's complication Risk has been widely used among the scientific research and management of diabetes.If the research in this direction of China is only indiscriminately imitated merely Foreign study model causes result of study to deviate due to the difference of crowd, therefore domestic research should be according to China National conditions are predicted for diabetic.Li Zhangping in 2009 et al. using prediction model Logistic regression model in three, Decision-tree model and neural network model, respectively to the hair of lesion around diabetes B nerve ending under conditions of small sample Raw probability predicted, be compared by the area under ROC curve obtain area it is maximum be neural network model, predict energy Power is best, is secondly Logistic regression model, group rear guard's decision-tree model;But it is back in the research using data set Care for Journal of Sex Research, sample content is less, and is related to that variable is more, therefore the accuracy of the model need further to test Card.
Summary of the invention
In view of above-mentioned existing deficiency, the purpose of the present invention is to provide a kind of, and the medical treatment based on electronic health record data is led Domain intelligent management construction method, it is intended to propose a kind of new methods of risk assessment.
The technical scheme adopted by the invention to solve the technical problem is that: a kind of new intelligence of the method based on electronic health record Change management construction method, this method mainly includes the following steps:
Step 1: managing data needed for export in systems, derived data are stored in the form of Excel table.
Step 2: derived data being subjected to data cleansing, data integration, data conversion, hough transformation, eventually form mesh Mark data set result database.
Step 3: being chosen most after carrying out data mining analysis comparison to result database using traditional data mining algorithm Excellent algorithm simultaneously optimizes, and chooses most correlative factor using the algorithm chosen and constructs Intelligent management model.
Further, the method that building obtains electronic health record data described in step 1 of the present invention, step specifically include:
Step 1-1: with authorized user identities login system database.
Step 1-2: electronic health record Basic Information Table is exported from system database using SQL statement, then from another Export, which is examined, in system number library checks data.
Step 1-3: by export data with the storage of Excel table.
Further, data preprocessing method described in step 2 of the present invention, step specifically include:
Step 2-1: by derived essential information and examine inspection data with unique No. id for external key using VBA language It matches Basic Information Table and examines and check tables of data.
Step 2-2: the dimension column for lacking mass data and the check item and information unrelated with objective result are deleted, is deleted Lack a large amount of data lines examined and check information.
Step 2-3: lacking a small amount of examine and check data, and all inspection numbers inspection inspection is found out in initial data from extracting Data are looked into, fill up data using averaging method.
Step 2-4: text data is become into numeric type data.Diabetes complicated retinopathy becomes label 1, and diabetes are not Suffer from retina and labels 0.
Further, the method for data digging method described in step 3 of the present invention, step specifically include:
Step 3-1: target data is assessed and is managed with Logistic, decision tree, KNN, Random Forest model respectively.
Step 3-2: most correlative factor, and benefit are found to every prominence score for examining Index for examination according to random forest With Logistic regression analysis other factors relevance score relevant to the factor.
Step 3-3: according to Index for examination and A/C relevance score is examined, it will be positively correlated index respectively and managed in conjunction with A/C Retinopathy eventually finds the highest indicator combination of accuracy rate.
Step 3-4: each forecast result of model is assessed.
Further step 3-4 comments index: assess respectively the prediction effects of various algorithms using precision ratio P, recall rate R with And the harmomic mean F of exact value and recall rate, with assessment algorithm, calculation formula difference is as follows:
Precision ratio:
Recall rate:
The harmomic mean of exact value and recall rate:
A kind of best algorithm prediction of assessment result is chosen, and utilizes random forest prominence score coherence check index Factor combination improves predictablity rate.
The present invention is a kind of new medical intelligent management construction method.
The utility model has the advantages that
1. the present invention faces a large amount of structurings and unstructured electronic health record information in data preprocessing phase, summarize The data cleansing process of complete set is laid a solid foundation for the building of intelligent management model construction.
2. the data analysis mining stage of the present invention constructs Intelligent management model using traditional data digging method, utilizes Grid optimization method optimizes best model-Random Forest model, and is found using the prominence score of random forests algorithm most related Factor is further found and the maximum inspection check item of correlative factor positive correlation coefficient using Logistic regression analysis.
3. the present invention constructs the stage in medical field Intelligent management model, using the random forests algorithm of optimization, utilize The correlative factor of Logistic regression analysis predicts objective result, to construct complete Intelligent management model.
Detailed description of the invention
Fig. 1 is a kind of flow chart of the medical field Intelligent management model construction method based on electronic health record of the present invention.
Fig. 2 is the specific flow chart of step 2.
Fig. 3 is the important scoring figure of random forest of step 3.
Fig. 4 is Random Forest model algorithm flow chart.
Fig. 5 is Logistic Regression Analysis Result figure.
Fig. 6 is algorithm comparing result table.
Fig. 7 is management result table of the influence factor combination to target data.
Specific embodiment
The present invention provides a kind of medical field disease forecasting construction method based on electronic health record, to make mesh of the invention , technical solution and effect it is clearer, clear, the present invention is described in more detail below.It should be appreciated that described herein Specific embodiment be only used to explain the present invention, be not intended to limit the present invention.
Please refer to Fig. 1.Fig. 1 be a kind of medical field Intelligent management model construction method based on electronic health record of the present invention compared with The flow chart of good embodiment, as shown, implementation step, includes the following:
Step 1: export relevant to target data essential information in system and examine inspection data, by derived data with The form of Excel table stores.
Step 2: derived data being subjected to data cleansing, data integration, data conversion, hough transformation, eventually form mesh Mark data result database.
Step 3: being chosen most after carrying out data mining analysis comparison to result database using traditional data mining algorithm Excellent algorithm simultaneously optimizes, and chooses and constructs risk Intelligent management model using the algorithm chosen with target data most correlative factor, finally Obtain medical field Intelligent management model mould construction method.
It as seen from Figure 3, is up to significantly Urine proteins creatinine ratio (A/C) with the scoring of target Correlative Influence Factors, by Fig. 5 As can be seen that sorting with glycoprotein urine creatinine than factor positive correlation factor, Fig. 7 can be seen that the management when index for selection combination Model has best effect.
It should be understood that the application of the present invention is not limited to the above for those of ordinary skills can With improvement or transformation based on the above description, all these modifications and variations all should belong to the guarantor of appended claims of the present invention Protect range.

Claims (4)

1. a kind of medical field Intelligent management model construction method based on electronic health record, it is characterised in that: this method is mainly wrapped Include following steps,
Step 1: managing data needed for export in systems, derived data are stored in the form of Excel table;
Step 2: derived data being subjected to data cleansing, data integration, data conversion, hough transformation, eventually form number of targets According to collection result database;
Step 3: choosing optimal calculation after carrying out data mining analysis comparison to result database using traditional data mining algorithm Method simultaneously optimizes, and chooses most correlative factor using the algorithm chosen and constructs Intelligent management model.
2. a kind of medical field Intelligent management model construction method based on electronic health record according to claim 1, special Sign is: the method that building obtains electronic health record data described in step 1, step specifically include:
Step 1-1: with authorized user identities login system database;
Step 1-2: electronic health record Basic Information Table is exported from system database using SQL statement, then from another system Export, which is examined, in number library checks data;
Step 1-3: by export data with the storage of Excel table.
3. a kind of medical field Intelligent management model construction method based on electronic health record according to claim 1, special Sign is: data preprocessing method described in step 2, step specifically include:
Step 2-1: by derived essential information and inspection data is examined to match with unique No. id for external key using VBA language Basic Information Table and inspection check tables of data;
Step 2-2: deleting the dimension column for lacking mass data and the check item and information unrelated with objective result, deletion lack It is a large amount of to examine the data line for checking information;
Step 2-3: lacking a small amount of examine and check data, and all inspection numbers inspection inspection number is found out in initial data from extracting According to filling up data using averaging method;
Step 2-4: text data is become into numeric type data;Diabetes complicated retinopathy becomes label 1, and diabetes are not suffering from view Nethike embrane labels 0.
4. a kind of medical field Intelligent management model construction method based on electronic health record according to claim 1, special Sign is: the method for data digging method described in step 3, step specifically include:
Step 3-1: target data is assessed and is managed with Logistic, decision tree, KNN, Random Forest model respectively;
Step 3-2: most correlative factor is found to every prominence score for examining Index for examination according to random forest, and is utilized Logistic regression analysis other factors relevance score relevant to the factor;
Step 3-3: according to Index for examination and A/C relevance score is examined, it will be positively correlated index respectively and manage view in conjunction with A/C Film lesion eventually finds the highest indicator combination of accuracy rate;
Step 3-4: each model intelligent management effect is assessed;
Further step 3-4 comments index: assessing looking into the intelligent management effect utilization of retinopathy for various algorithms respectively The harmomic mean F of quasi- rate P, recall rate R and exact value and recall rate, with assessment algorithm, calculation formula difference is as follows:
Precision ratio:
Recall rate:
The harmomic mean of exact value and recall rate:
It chooses a kind of best algorithm model of assessment result and constructs Intelligent management model, and utilize random forest prominence score The combination of coherence check index factor improves Intelligent management model and constructs a kind of new optimal Intelligent management model of effect.
CN201811536456.4A 2018-12-14 2018-12-14 A kind of medical field Intelligent management model construction method based on electronic health record Pending CN109616168A (en)

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CN110164524A (en) * 2019-04-29 2019-08-23 北京国润健康医学投资有限公司 A kind of hemiplegia patient training mission adaptive matching method and its system
CN110853764A (en) * 2019-11-28 2020-02-28 成都中医药大学 Diabetes syndrome prediction system
CN111554401A (en) * 2020-03-26 2020-08-18 肾泰网健康科技(南京)有限公司 Method for constructing AI (artificial intelligence) chronic kidney disease screening model, and chronic kidney disease screening method and system
CN111710420A (en) * 2020-05-15 2020-09-25 深圳先进技术研究院 Complication morbidity risk prediction method, system, terminal and storage medium based on electronic medical record big data
CN111986754A (en) * 2020-08-21 2020-11-24 南通大学 Electronic medical record management model construction method based on diabetes

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CN110164524A (en) * 2019-04-29 2019-08-23 北京国润健康医学投资有限公司 A kind of hemiplegia patient training mission adaptive matching method and its system
CN110853764A (en) * 2019-11-28 2020-02-28 成都中医药大学 Diabetes syndrome prediction system
CN110853764B (en) * 2019-11-28 2023-11-14 成都中医药大学 Diabetes syndrome prediction system
CN111554401A (en) * 2020-03-26 2020-08-18 肾泰网健康科技(南京)有限公司 Method for constructing AI (artificial intelligence) chronic kidney disease screening model, and chronic kidney disease screening method and system
CN111554401B (en) * 2020-03-26 2020-12-29 肾泰网健康科技(南京)有限公司 AI (AI) chronic kidney disease risk screening and modeling method, chronic kidney disease risk screening method and system
WO2021190300A1 (en) * 2020-03-26 2021-09-30 肾泰网健康科技(南京)有限公司 Method for constructing ai chronic kidney disease risk screening model, and chronic kidney disease risk screening method and system
CN111710420A (en) * 2020-05-15 2020-09-25 深圳先进技术研究院 Complication morbidity risk prediction method, system, terminal and storage medium based on electronic medical record big data
CN111710420B (en) * 2020-05-15 2024-03-19 深圳先进技术研究院 Complication onset risk prediction method, system, terminal and storage medium based on electronic medical record big data
CN111986754A (en) * 2020-08-21 2020-11-24 南通大学 Electronic medical record management model construction method based on diabetes

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