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Related Experiment Videos

Assessing compliance to antihypertensive medications using computer-based pharmacy records

D B Christensen1, B Williams, H I Goldberg

  • 1Department of Pharmacy and Health Services, University of Washington, Seattle 98195-7630, USA.

Medical Care
|November 21, 1997
PubMed
Summary

Computer algorithms assessing prescription refill patterns can detect potential drug compliance issues in chronic disease management. However, these refill-based methods require cautious interpretation due to potential data discrepancies and do not confirm actual medication adherence.

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Area of Science:

  • Pharmacology
  • Health Informatics
  • Chronic Disease Management

Background:

  • Optimizing prescribed drug therapy in chronic disease management necessitates systematic approaches for compliance problem detection and intervention.
  • Computer algorithms analyzing prescription refill patterns offer an unobtrusive method for assessing medication adherence.

Purpose of the Study:

  • To evaluate the utility and limitations of computer-generated algorithms based on refill patterns for detecting drug-taking compliance problems.
  • To provide guidance for healthcare professionals, particularly pharmacists, in interpreting compliance data derived from refill patterns.

Main Methods:

  • Analysis of computer algorithms that assess patient compliance based on prescription refill data.
  • Examination of the advantages and disadvantages of refill-based compliance measures.

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  • Consideration of time periods for compliance assessment, with a recommendation for caution with intervals less than 60 days.

    • Main Results:

    • Refill pattern algorithms measure refill timeliness, not actual drug ingestion, presenting a potential limitation.
    • These algorithms can flag potential compliance issues but may also indicate discrepancies in medical charts, pharmacy records, or patient communication.
    • Calculating compliance rates across multiple refills and using longer time periods (e.g., >60 days) can decrease false positives but may reduce the number of assessable patients.

    Conclusions:

    • Healthcare professionals should exercise caution when using computer-generated compliance flags based on refill patterns.
    • Before initiating interventions for non-compliance, it is crucial to investigate potential discrepancies in drug records.
    • Refill pattern analysis is a useful tool but requires careful interpretation and validation with other data sources for accurate patient care.