How Terminology Mapping Drives Semantic Interoperability

The increasing use of electronic health records (EHRs) opens opportunities for data sharing and collaborative care that simply didn’t exist when patient information was confined to paper charts.

Emerging healthcare business models such as accountable care organizations (ACOs) and patient-centered medical homes (PCMHs) rely on the exchange of data among primary care physicians, specialists, hospitals and other providers. Health information exchanges (HIEs), whether localized or regional in scope, naturally depend on the ability to move clinical data among the participating parties. Population health management, a component of the nation’s healthcare reform initiative, calls for a robust data analysis infrastructure that can pull in anonymized patient data from myriad healthcare systems.

Ironically, the electronic systems that liberate data from paper records often end up restricting communications. Different healthcare providers tend to use different EHR systems, selecting from the dozens of products available in the market. Systems tend to represent data differently, which leads to interoperability issues. A recent report published in the Journal of the American Medical Informatics Association noted “615 observations of errors and data expression various” across the 21 EHR technologies examined.

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