The Research On Methed Of Patient Information Retrieval For Clinical Decision Support System

Numerous successes have been reported using clinical decision support system to improve the quality of patient care. Such usage of clinical decision support system requires the usage of patient data to generate contextually relevant recommendations. Traditional clinical decision support system requires that doctor entry patient data manually, seriously hinder the application of clinical decision support system at the point of care. So we carry out research on the method of heterogeneous data retrieval from local electronic health records to address the problem of patient data retrieval. Facing the reality of heterogeneity of local electronic health records, the diversity of CDSS, whose basic information requirements are common while detailed demands tend to be variable, requires many-to-many mappings between decision-support systems and electronic health records.To solve this problem, this paper proposes a basic information model that extracts information through defining general data types, data structures and classes needed by CDSS. The instantiation of basic information model, which is realized through binding and defining the restrictive relationships of data types and data structures according to semantic information, generates special information model for designated CDSS. The application of proposed method suits the patient information demands of dissimilar CDSS adaptively. This approach will allow for one-to-many mappings instead of the many-to-many mappings between decision-support systems and electronic health records.In order to overcome the difficulties brought about by the model heterogeneity, structure heterogeneity, semantic heterogeneity and data mismatching between EMR and patient information database, this paper proposed a modifiable method based on dual mode data transformation to transform heterogeneous data by building a set of medical logic operators and formally describing rules generated via combination of medical logic operators using EBNF, which avoids the shortcoming of traditional data transformation methods based on hard code. This paper design and develop a general information acquisition component pertaining to providing automatic patient information collection for CDSS based on the research of information model.This information acquisition component is constituted of a patient information database contains appropriate patient information demanded by CDSS, an interface to acquire general information and the key part, an adapter to transform data between EMR and patient information database. This paper testifies the proposed method by transforming information of 200 patients from heterogeneous EMR of two hospitals to Diabetes Mellitus (DM) and Hypertension diagnostic CDSS and the results prove it to be an effective method that fits for providing various CDSS with automatic patient information acquisition service.