Secondary Logo

Journal Logo

Institutional members access full text with Ovid®

A Refill Adherence Algorithm for Multiple Short Intervals to Estimate Refill Compliance (ReComp)

Bryson, Chris L. MD, MS*†; Au, David H. MD, MS*†; Young, Bessie MD, MS†‡; McDonell, Mary B. MS*; Fihn, Stephan D. MD, MPH*†

doi: 10.1097/MLR.0b013e3180329368
Original Article

Background: There are many measures of refill adherence available, but few have been designed or validated for use with repeated measures designs and short observation periods.

Objective: To design a refill-based adherence algorithm suitable for short observation periods, and compare it to 2 reference measures.

MethodsA single composite algorithm incorporating information on both medication gaps and oversupply was created. Electronic Veterans Affairs pharmacy data, clinical data, and laboratory data from routine clinical care were used to compare the new measure, ReComp, with standard reference measures of medication gaps (MEDOUT) and adherence or oversupply (MEDSUM) in 3 different repeated measures medication adherence-response analyses. These analyses examined the change in low density lipoprotein (LDL) with simvastatin use, blood pressure with antihypertensive use, and heart rate with β-blocker use for 30- and 90-day intervals. Measures were compared by regression based correlations (R2 values) and graphical comparisons of average medication adherence-response curves.

Results: In each analysis, ReComp yielded a significantly higher R2 value and more expected adherence-response curve regardless of the length of the observation interval. For the 30-day intervals, the highest correlations were observed in the LDL-simvastatin analysis (ReComp R2 = 0.231; [95% CI, 0.222–0.239]; MEDSUM R2 = 0.054; [95% CI, 0.049–0.059]; MEDOUT R2 = 0.053; [95% CI, 0.048–0.058]).

Conclusions: ReComp is better suited to shorter observation intervals with repeated measures than previously used measures.

From the *Health Services Research and Development Northwest Center of Excellence and the ‡Epidemiologic Research and Information Center, Veterans Affairs Puget Sound Health Care System, Seattle, Washington; and †Department of Medicine, University of Washington, Seattle.

Supported by a VA Career Development Award (RCD03-177 and RCD00-018). The Veterans Affairs (VA) Ambulatory Care Quality Improvement Project (ACQUIP) was funded by VA HSR&D Grants no. SDR96-002 and IIR99-376.

Views expressed in this article are those of the authors and do not necessarily represent the views of the Department of Veterans Affairs, or the University of Washington.

Reprints: Chris L. Bryson, MD, MS, Department of Veterans Affairs, Health Services Research and Development Northwest Center of Excellence, VA Puget Sound Health Care System, 1100 Olive Way, Suite 1400, Seattle, WA 98101. E-mail:

© 2007 Lippincott Williams & Wilkins, Inc.