An architecture for linking medical decision-support applications to clinical databases and its evaluation

  • Authors:

  • Efrat German;Akiva Leibowitz;Yuval Shahar

  • Affiliations:

  • Medical Informatics Research Center, Department of Information Systems Engineering, Ben-Gurion University, P.O. Box 653, 84105 Beer-Sheva, Israel;Medical Informatics Research Center, Department of Information Systems Engineering, Ben-Gurion University, P.O. Box 653, 84105 Beer-Sheva, Israel;Medical Informatics Research Center, Department of Information Systems Engineering, Ben-Gurion University, P.O. Box 653, 84105 Beer-Sheva, Israel

  • Venue:
  • Journal of Biomedical Informatics
  • Year:
  • 2009

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Abstract

We describe and evaluate a framework, the Medical Database Adaptor (MEIDA), for linking knowledge-based medical decision-support systems (MDSSs) to multiple clinical databases, using standard medical schemata and vocabularies. Our solution involves a set of tools for embedding standard terms and units within knowledge bases (KBs) of MDSSs; a set of methods and tools for mapping the local database (DB) schema and the terms and units relevant to the KB of the MDSS into standardized schema, terms and units, using three heuristics (choice of a vocabulary, choice of a key term, and choice of a measurement unit); and a set of tools which, at runtime, automatically map standard term queries originating from the KB, to queries formulated using the local DB's schema, terms and units. The methodology was successfully evaluated by mapping three KBs to three DBs. Using a unit-domain matching heuristic reduced the number of term-mapping candidates by a mean of 71% even after other heuristics were used. Runtime access of 10,000 records required one second. We conclude that mapping MDSSs to different local clinical DBs, using the three-phase methodology and several term-mapping heuristics, is both feasible and efficient.