Evaluating Healthcare Quality Using Natural Language Processing

Abstract

Consistent monitoring for quality indicators as adverse events or missed screening opportunities remains a difficult proposition for most healthcare organizations. Much of the clinical data needed for quality reports is imbedded in narrative reports in the electronic health record. Narrative data most often require costly retrieval by manual data extraction. NUD*IST, a qualitative research computer program, was used as an automated natural Language processing tool to extract and code data for analysis of screening and treatment for breast cancer. The study method demonstrated acceptable Levels of precision and recall compared to large-scale natural Language processing programs.

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