Design And Implementation Of Visualized An OpenEHR-Based Development Platform For Clinical Decision Support System

The clinical decision support system uses computerized medical knowledge,combined with the patient’s condition information,and uses the reasoning engine to make reasoning decisions,so as to help medical staff make correct decisions and improve medical level.However,due to the rapid update of medical knowledge,flexible and changeable clinical needs,and heterogeneous information systems among medical institutions,it is difficult for developers to quickly respond to the rapid update of medical knowledge and flexible and changeable demand changes,and it is also difficult for clinical decision support systems shared among different institutions.On the basis of building a standardized information model,using visual development technology to build a clinical decision support system through convenient graphical click,drag,connection,and configuration operations will help solve the difficulties in its development and sharing.In view of the above problems,this study,based on the analysis of the information modeling requirements of the clinical decision support system,constructed a unified information model for the clinical decision support system based on the open openEHR medical information model,which facilitates the rapid clinical application and sharing of the knowledge base;By analyzing the general functions and interaction requirements of the clinical decision support system,a visual editing tool for the human-computer interaction page was constructed,which improved the efficiency of the page construction;the visual development platform of the clinical decision support system was designed,developed and verified,and provided for the development of the system Supported by visualization tools for the whole process.The main research contents of this paper include:(1)Construct a unified information model for clinical decision support system.Analyze the data requirements of 5 domestic clinical decision support systems,combine the commonly used inspection and testing items in hospitals,summarize the information model standardization requirements,compare with the existing mainstream information models HL7 v MR and openEHR in the medical field,and sort out the clinical decision support system data for domestic hospitals A unified information model for sharing and knowledge expression needs,combined with the advantages of HL7 v MR and openEHR,constructs a unified information model for clinical decision support systems based on openEHR specifications,which includes 14 prototypes and 90 attributes.Finally,the etiological classification module of ischemic stroke in the "Chinese Cerebrovascular Clinical Management" guideline is selected.The guideline includes 10 clinical concepts and 36 data requirements.The practice results show that the diagnostic information and test result information prototype in the model can be completely integrated.The concepts and data requirements in the Express Guidelines validate the integrity of the Unified Information Model.(2)A human-computer interaction page visual editing tool for clinical decision support system was constructed.By analyzing the functions and human-computer interaction design of 5 typical domestic clinical decision support systems,the content that must be included in visual editing is determined,including 5 functional requirements and10 page requirements,and a dedicated clinical decision support system is designed and developed.It is a human-computer interactive page visual editing tool that can visually edit,manage and maintain pages.(3)Design and implement a visual development platform that can support the whole process of clinical decision support system construction.The development of a clinical decision support system using the elderly comorbid medication scenario and the etiological classification diagnosis scenario of ischemic stroke is used as a case verification.The verification results show that the construction of the elderly comorbidity drug system based on this platform reduces the development time from 72 hours to 18.5 hours,and the construction of the ischemic stroke etiology classification diagnosis system reduces the development time from 64 hours to 10.5 hours.