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Good and poor adherence: optimal cut-point for adherence measures using administrative claims data.

Sudeep Karve1, Mario A Cleves, Mark Helm

  • 1The Ohio State University, Columbus, OH, USA.

Current Medical Research and Opinion
|July 29, 2009
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Summary

A medication adherence threshold of 0.80 effectively distinguishes between good and poor compliers for chronic diseases like diabetes and hypertension. This adherence value helps predict hospitalizations in Medicaid patients.

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Area of Science:

  • Health Services Research
  • Pharmacoepidemiology
  • Chronic Disease Management

Background:

  • Patient adherence to medication is crucial for managing chronic conditions.
  • Administratively derived adherence measures like MPR and PDC are commonly used but require validated cut-off points.
  • Identifying optimal adherence thresholds can improve patient outcomes and healthcare resource utilization.

Purpose of the Study:

  • To determine the optimal adherence value cut-off for stratifying patients into good and poor compliers.
  • To evaluate the predictive value of medication possession ratio (MPR) and proportion of days covered (PDC) for hospitalization outcomes.
  • To assess these adherence measures across diverse chronic conditions including schizophrenia, diabetes, hypertension, CHF, and hyperlipidemia.

Main Methods:

  • Retrospective analysis of Arkansas Medicaid administrative claims data.
  • Inclusion of adult patients with specific chronic conditions and continuous eligibility.
  • Assessment of 1-year medication adherence using MPR and PDC, with hospitalization as the primary outcome.
  • Logistic regression and ROC curve analysis to identify optimal adherence cut-off values.

Main Results:

  • Optimal adherence cut-off values for predicting any-cause hospitalization ranged from 0.63 to 0.89.
  • Optimal cut-off values for disease-specific hospitalization ranged from 0.58 to 0.85 across the studied cohorts.
  • These findings indicate variability in optimal adherence thresholds depending on the outcome and disease.

Conclusions:

  • An adherence cut-off of 0.80 provides a reasonable basis for stratifying patients as adherent or non-adherent.
  • This threshold demonstrates validity in predicting subsequent hospitalizations across several prevalent chronic diseases.
  • Further research is recommended to explore other outcome metrics for adherence threshold identification.