Abstract:
BACKGROUND:Granular clinical and laboratory data available in electronic health record (EHR) databases provide researchers the opportunity to conduct investigations that would not be possible in insurance claims databases; however, for pharmacoepidemiology studies, accurate classification of medication exposure is critical. OBJECTIVE:The aim of this study was to evaluate the validity of classifying medication exposure using EHR prescribing (EHR-Rx) data. METHODS:We conducted a retrospective cohort study among patients with linked claims and EHR data in OptumLabs™ Data Warehouse. The agreement between EHR-Rx data and pharmacy claims (PC-Rx) data (for 40 medications) was determined using the positive predictive value (PPV) and medication possession ratio (MPR)-calculated in 1- and 12-month medication exposure periods (MEPs). Secondary analyses were restricted to incident vs prevalent EHR-Rxs, age ≥65 vs <65, white vs black race, males vs females, and number of EHR-Rxs. RESULTS:The validity metrics varied substantially among the 40 medications assessed. Across all medications, the period PPV and MPR were 62% and 63% in the 1-month MEP. They were 78% and 43% in the 12-month MEP. Overall, PPV and MPR were higher for patients with a prevalent EHR-Rx and age <65. CONCLUSIONS:Despite substantial variability among different medications, there was very good agreement between EHR-Rx data and PC-Rx data. To maximize the validity of classifying medication exposure with EHR prescribing data, researchers may consider using longer MEPs (eg, 12 months) and potentially require multiple EHR-Rxs to classify baseline medication exposure.
journal_name
Pharmacoepidemiol Drug Safjournal_title
Pharmacoepidemiology and drug safetyauthors
Rowan CG,Flory J,Gerhard T,Cuddeback JK,Stempniewicz N,Lewis JD,Hennessy Sdoi
10.1002/pds.4234subject
Has Abstractpub_date
2017-08-01 00:00:00pages
963-972issue
8eissn
1053-8569issn
1099-1557journal_volume
26pub_type
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