AMIA Annu Symp Proc - Validation and enhancement of a computable medication indication resource (MEDI) using a large practice-based dataset.

Tópicos

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Resumo

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.

Resumo Limpo

link medic indic import clinic care research recent develop freelyavail comput medicationind resourc call medi link rxnorm medic indic map icd code paper identifi medic diagnos million individu vanderbilt univers medic center evalu medic coverag medi calcul preval indic medic result demonstr medi cover medic record medic record high precis subset medi cover record medic signific prescript drug miss medi manual physician review random patient record four exampl medic found medi cover observ indic confirm estim preval medic use practic inform indic preval inform medic previous unavail public resourc may improv clinic usabl medi believ medi will use clinic informat aid recognit phenotyp electron medic recordbas research

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