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Pharmacoepidemiol Drug Saf. 2017 Aug;26(8):963-972. doi: 10.1002/pds.4234. Epub 2017 Jun 12.

Agreement and validity of electronic health record prescribing data relative to pharmacy claims data: A validation study from a US electronic health record database.

Author information

1
Collaborative Healthcare Research and Data Analytics (COHRDATA), Santa Monica, CA, USA.
2
Department of Health Policy and Research, Weill Cornell Medical College, New York, NY, USA.
3
Department of Pharmacy Practice and Administration, Ernest Mario School of Pharmacy, Rutgers University, Piscataway, NJ, USA.
4
AMGA, Alexandria, VA, USA.
5
Division of Gastroenterology, Center for Clinical Epidemiology and Biostatistics, University of Pennsylvania, Philadelphia, PA, USA.
6
Center for Clinical Epidemiology and Biostatistics, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA.

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.

KEYWORDS:

EHR prescribing records; medication possession ratio; positive predictive valuevalidity

PMID:
28608510
DOI:
10.1002/pds.4234
[Indexed for MEDLINE]

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