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Cited by 620Medication Adherence and ComplianceHealthcare Policy and ManagementPharmaceutical Practices and Patient Outcomes

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

Karve, Sudeep, Cleves, Mario A., Helm, Mark, Hudson, Teresa J., West, Donna S., Martin, Bradley C.·2009·Current Medical Research and Opinion
DOI 10.1185/03007990903126833
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Abstract

OBJECTIVE: To identify the adherence value cut-off point that optimally stratifies good versus poor compliers using administratively derived adherence measures, the medication possession ratio (MPR) and the proportion of days covered (PDC) using hospitalization episode as the primary outcome among Medicaid eligible persons diagnosed with schizophrenia, diabetes, hypertension, congestive heart failure (CHF), or hyperlipidemia. RESEARCH DESIGN AND METHODS: This was a retrospective analysis of Arkansas Medicaid administrative claims data. Patients > or =18 years old had to have at least one ICD-9-CM code for the study diseases during the recruitment period July 2000 through April 2004 and be continuously eligible for 6 months prior and 24 months after their first prescription for the target condition. Adherence rates to disease-specific drug therapy were assessed during 1 year using MPR and PDC. MAIN OUTCOME MEASURE AND ANALYSIS SCHEME: The primary outcome measure was any-cause and disease-related hospitalization. Univariate logistic regression models were used to predict hospitalizations. The optimum adherence value was based on the adherence value that corresponded to the upper most left point of the ROC curve corresponding to the maximum specificity and sensitivity. RESULTS: The optimal cut-off adherence value for the MPR and PDC in predicting any-cause hospitalization varied between 0.63 and 0.89 across the five cohorts. In predicting disease-specific hospitalization across the five cohorts, the optimal cut-off adherence values ranged from 0.58 to 0.85. CONCLUSIONS: This study provided an initial empirical basis for selecting 0.80 as a reasonable cut-off point that stratifies adherent and non-adherent patients based on predicting subsequent hospitalization across several highly prevalent chronic diseases. This cut-off point has been widely used in previous research and our findings suggest that it may be valid in these conditions; it is based on a single outcome measure, and additional research using these methods to identify adherence thresholds using other outcome metrics such as laboratory or physiologic measures, which may be more strongly related to adherence, is warranted.

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  • A cut-off for optimal adherence of PDC equal to or higher than 80% is reasonable for predictable hospitalizations in chronic diseases.

    “Cut-off for optimal adherence was defined as PDC equal or higher than 80% as this has been found to be reasonable for predictable hospitalizations in chronic diseases”

    From Using Dispensing Data to Evaluate Adherence Implementation Rates in Community Pharmacy (2019) · cites this paper as Karve et al., 2009

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Authors
Karve, S., Cleves, M. A., Helm, M., Hudson, T. J., West, D. S., & Martin, B. C.
Affiliations
  • The Ohio State University (US)
  • University of Arkansas for Medical Sciences (US)
  • University of Mississippi (US)
Corresponding author
Karve, Sudeep
ORCID
Venue
Current Medical Research and Opinion
Publisher
Informa UK Limited
Published
2009-07-28
Volume
25
Issue
9
Pages
2303-2310
ISSN
  • 0300-7995 (ISSN-L)
  • 1473-4877
DOI
10.1185/03007990903126833
OpenAlex
W2102368961
Cited by
620
References
32
Citations by year
2026: 32 · 2025: 44 · 2024: 36 · 2023: 43 · 2022: 53 · 2021: 68 · 2020: 44 · 2019: 45 · 2018: 43 · 2017: 43 · 2016: 35 · 2015: 30 · 2014: 32 · 2013: 27 · 2012: 19
FWCI
10.78
Type
journal article
Language
en
Open access
closed
Locations
  • Current Medical Research and Opinion (publishedVersion)
  • PubMed (publishedVersion)
Topics
  • Health Sciences › Medicine › Family Practice › Medication Adherence and Compliance
  • Social Sciences › Economics, Econometrics and Finance › Economics and Econometrics › Healthcare Policy and Management
  • Health Sciences › Medicine › Geriatrics and Gerontology › Pharmaceutical Practices and Patient Outcomes
Keywords
medication adherence, medication possession ratio, proportion of days covered, hospitalization, Medicaid, schizophrenia, diabetes mellitus, hypertension, congestive heart failure, hyperlipidemia, chronic disease, administrative claims data, ROC curve
MeSH terms
Adolescent, Adult, Aged, Aged, 80 and over, Arkansas, Calibration, Forecasting, Hospitalization, Humans, Insurance Claim Review, Medicaid, Middle Aged, Patient Compliance, Reference Values, Retrospective Studies, United States, Drug Monitoring, Health Care Costs, International Classification of Diseases, Young Adult

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