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Related Experiment Videos

Improving drug prescribing in a primary care practice.

S H Gehlbach, W E Wilkinson, W E Hammond

    Medical Care
    |March 1, 1984
    PubMed
    Summary

    Computerized feedback significantly improved physician prescribing of generic drugs, increasing rates from 14% to 67%. This model shows promise for enhancing prescribing habits and reducing healthcare costs.

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    Area of Science:

    • Medical Informatics
    • Health Services Research
    • Pharmacoeconomics

    Background:

    • Physician prescribing habits significantly impact healthcare costs and patient outcomes.
    • Promoting the use of generic drugs is a key strategy for cost containment in healthcare.
    • Computerized decision support systems offer potential for influencing physician behavior.

    Purpose of the Study:

    • To evaluate the effectiveness of a computerized feedback model in improving generic drug prescribing rates among physicians.
    • To assess the impact of cost-saving feedback on physician prescribing behavior in a family medicine residency practice.

    Main Methods:

    • A randomized controlled trial was conducted with resident and faculty physicians.
    • The experimental group received monthly printouts detailing brand-name prescriptions and potential generic cost savings.

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  • The control group received no feedback; prescription monitoring continued for both groups post-intervention.

    • Main Results:

    • Median generic prescribing rates increased from 14% to 67% in the experimental group during the feedback period.
    • The experimental group's increase in generic prescribing was significantly greater than the control group (P = 0.01).
    • Generic prescribing rates in the experimental group remained elevated at 54% during the follow-up period.

    Conclusions:

    • Computerized feedback is an effective model for improving generic drug prescribing rates.
    • The study suggests this feedback model could be beneficial for broader applications in physician prescribing.
    • Further evaluation is recommended to explore the model's efficacy in other areas of medical prescribing.