Validation and enhancement of a computable medication indication resource (MEDI) using a large practice-based dataset

Abstract

Linking medications with their indications is important for clinical care and research. We have recently developed a freely-available, computable medication-indication resource, called MEDI, which links RxNorm medications to indications mapped to ICD9 codes. In this paper, we identified the medications and diagnoses for 1.3 million individuals at Vanderbilt University Medical Center to evaluate the medication coverage of MEDI and then to calculate the prevalence for each indication for each medication. Our results demonstrated MEDI covered 97.3% of medications recorded in medical records. The "high precision subset" of MEDI covered 93.8% of recorded medications. No significant prescription drugs were missed by MEDI. Manual physician review of random patient records for four example medications found that the MEDI covered the observed indications, and confirmed the estimated prevalence of these medications using practice information. Indication prevalence information for each medication, previously unavailable in other public resources, may improve the clinical usability of MEDI. We believe MEDI will be useful for both clinical informatics and to aid in recognition of phenotypes for electronic medical record-based research.