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Related Experiment Videos

A chronic disease score from automated pharmacy data.

M Von Korff1, E H Wagner, K Saunders

  • 1Center for Health Studies, Group Health Cooperative of Puget Sound, Seattle, WA 98101.

Journal of Clinical Epidemiology
|February 1, 1992
PubMed
Summary

The Chronic Disease Score (CDS), derived from pharmacy data, offers a stable measure of chronic illness. It correlates with disease severity and predicts future hospitalizations and mortality, independent of healthcare use.

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Area of Science:

  • Health Services Research
  • Pharmacoepidemiology
  • Chronic Disease Management

Background:

  • Accurate assessment of chronic disease status is crucial for healthcare management and resource allocation.
  • Existing methods for measuring chronic disease burden can be resource-intensive or lack objective data.
  • Automated pharmacy data offers a potentially rich, underutilized source for health status assessment.

Purpose of the Study:

  • To develop and validate a Chronic Disease Score (CDS) using automated pharmacy data.
  • To assess the stability, reliability, and predictive validity of the CDS.
  • To evaluate the association of CDS with other health status measures and healthcare utilization.

Main Methods:

  • A consensus process identified prescription medication patterns indicative of chronic disease.

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  • The Chronic Disease Score (CDS) was constructed from these patterns in population-based pharmacy data.
  • CDS was evaluated for stability, correlation with physician ratings, and prediction of hospitalization/mortality in multiple patient cohorts.

    • Main Results:

    • CDS demonstrated good correlation with physician-rated disease severity (r=0.46-0.57) and high year-to-year stability (r=0.74).
    • CDS significantly predicted subsequent hospitalization and mortality, even after controlling for age, gender, and healthcare visits.
    • CDS showed moderate association with self-rated health and disability but was not linked to depression or anxiety.

    Conclusions:

    • Automated pharmacy data can generate a stable and valid Chronic Disease Score (CDS).
    • CDS serves as a valuable, objective measure of chronic disease burden, predicting adverse health outcomes.
    • Refinements in scoring algorithms, potentially including local prescribing practice adaptations and empirical weighting, may further enhance CDS utility.