Unambiguous data modeling to ensure higher accuracy term binding to clinical terminologies.
Work in the field of recording standard, coded data is important to reduce medical errors caused by misinterpretation and misrepresentation of data. The paper discusses the need to ensure that the source of the data i.e. the clinical data model is unambiguous to increase the quality and accuracy of the data mapping to terminology codes. The study chooses one especially ambiguous data model and remodels it to make clearer both the structure of the data, as well as its intended use and semantics. By ensuring an unambiguous model, results of the data mapping increased in accuracy from 64.7% to 80.55%. The clinical experts evaluating the models found it easier working with the revised model and agreed on the mappings 93.1% times as against 48.57% times previously. The aim of the study is to encourage good modeling practice to enable clinicians to record and code patient data unambiguously and accurately.
Qamar
Rahil
R
University of Manchester, Manchester, U.K.
Kola
Jay
J
Rector
Alan L
AL
D000043:Abstracting and Indexing; D005568:Forms and Records Control / Q000379:methods*; D006801:Humans; D016347:Medical Records Systems, Computerized / Q000458:organization & administration* / Q000592:standards; D009323:Natural Language Processing; D012660:Semantics; D039061:Systematized Nomenclature of Medicine; D009626:Terminology as Topic