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Estimating generic drug use with electronic health records data from a health care delivery system: implications for quality improvement and research.

Description

Nimbal V, Segal JB, Romanelli RJ., J Manag Care Spec Pharm. 22(10):1143-7. doi: 10.18553/jmcp.2016.22.10.1143., 2016 Oct 01

Abstract

BACKGROUND: Generic drug use in the outpatient setting is typically measured with adjudicated pharmacy claims; however, not all delivery systems have access to these data for their clinical populations.

OBJECTIVE: To develop an algorithm to estimate generic drug use in an outpatient setting using electronic health records (EHR) data.

METHODS: Twenty-five therapeutic classes were chosen with the potential for low generic use that were prescribed to managed care beneficiaries in a health care system in Northern California. An algorithm was developed to estimate generic drug use based on medication names and dispense-as-written requests from electronic prescriptions, as well as information on generic availability at the time the prescriptions were written. The algorithm was used to quantify a generic utilization rate (GUR) across therapeutic classes and was validated by comparing the estimated GUR to the true GUR, using pharmacy claims corresponding to prescriptions in the same patient cohort.

RESULTS: Among managed care beneficiaries, 104,859 prescriptions were identified for drugs in the therapeutic classes of interest with corresponding pharmacy claims. The algorithm estimated a GUR of 73.7% across 25 unique classes. The actual GUR based on pharmacy claims was 73.1%. Sensitivity (97%) and specificity (89%) of the algorithm were high, and total percentage of agreement was 95%.

CONCLUSIONS: An algorithm that estimates generic drug use performed well in a population of managed care beneficiaries. Health care delivery systems may apply methods described in this article to quantify generic drug use in their ambulatory populations for quality improvement and research initiatives, particularly when pharmacy claims are unavailable.

Pubmed Abstract

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Associated Topics

  • Medical Informatics
  • Pharmacoepidemiology

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