Computerized extraction of information on the quality of diabetes care from free text in electronic patient records of general practitioners.

Abstract

This study evaluated a computerized method for extracting numeric clinical measurements related to diabetes care from free text in electronic patient records (EPR) of general practitioners. Accuracy of this number-oriented approach was compared to manual chart abstraction. Audits measured performance in clinical practice for two commonly used electronic record systems. Numeric measurements embedded within free text of the EPRs constituted 80% of relevant measurements. For 11 of 13 clinical measurements, the study extraction method was 94%-100% sensitive with a positive predictive value (PPV) of 85%-100%. Post-processing increased sensitivity several points and improved PPV to 100%. Application in clinical practice involved processing times averaging 7.8 minutes per 100 patients to extract all relevant data. The study method converted numeric clinical information to structured data with high accuracy, and enabled research and quality of care assessments for practices lacking structured data entry.