Knowledge Mapping Across Disparate Patient Care Datasets

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DESCRIPTION: (provided by applicant) Health informatics can yield computational insight in assimilating knowledge from large clinical datasets for both research and policy discussion. The adoption of computerized patient records (CPR) by healthcare organizations promises to expand the sources potential research data to include clinical patient data. Applications of health informatics can enhance health services and clinical research, as well as improve healthcare quality. A primary goal of this traineeship in health informatics is to gain expertise in the modeling of clinical knowledge and the mapping of this knowledge to alternative taxonomies and meta-languages. A computational approach to this knowledge modeling and mapping will enable the creation of methodologies for aggregating clinical data from disparate data storage systems for large analyses. The proposed research is a first step in creating a regional health data repository. Broadly, this research will explore how various health data systems created by the private sector to facilitate healthcare delivery will support the secondary analysis of healthcare information for both health services and clinical research. Specifically, this research will examine the attributes and knowledge representation of multiple patient care data sources, and map the knowledge relevant to vancomycin-resistant nosocomial infections indexed to a common Unified Medical Language System (UMLS) integrated knowledge base for combined outcomes analyses.