BioMed Research International · 2015 · 92 citations · 16 references
ComputingHealth InformaticsHealth SystemsClinical Decision SupportElectronic Health RecordsTranslational MedicineClinical Data StandardsElectronic Health Record Data StandardsHealth Informatics StandardsHealth Information ArchitectureHealthcare Data StandardsKnowledge TranslationDecision Support System ModelsElectronic Health Record DataHealth Data ModelsHealth Data Semantic InteroperabilityHealth Record InteroperabilityHealthcare Systems ImplementationTransformTranslation Of Diagnostic Information
UNLABELLED: The Learning Health System (LHS) describes linking routine healthcare systems directly with both research translation and knowledge translation as an extension of the evidence-based medicine paradigm, taking advantage of the ubiquitous use of electronic health record (EHR) systems. TRANSFoRm is an EU FP7 project that seeks to develop an infrastructure for the LHS in European primary care. METHODS: The project is based on three clinical use cases, a genotype-phenotype study in diabetes, a randomised controlled trial with gastroesophageal reflux disease, and a diagnostic decision support system for chest pain, abdominal pain, and shortness of breath. RESULTS: Four models were developed (clinical research, clinical data, provenance, and diagnosis) that form the basis of the projects approach to interoperability. These models are maintained as ontologies with binding of terms to define precise data elements. CDISC ODM and SDM standards are extended using an archetype approach to enable a two-level model of individual data elements, representing both research content and clinical content. Separate configurations of the TRANSFoRm tools serve each use case. CONCLUSIONS: The project has been successful in using ontologies and archetypes to develop a highly flexible solution to the problem of heterogeneity of data sources presented by the LHS.
16
Evidence based medicine: what it is and what it isn't
David L. Sackett, William Rosenberg, J. A. Muir Gray et al. · BMJ · 1996 · 15.7K citations · Full text
Charles P. Friedman, Joshua C. Rubin, Jeffrey S. Brown et al. · Journal of the American Medical Informatics Association · 2014 · 517 citations · Full text