• Drugs & aging · Aug 2013

    The quality of quality measures: HEDIS® quality measures for medication management in the elderly and outcomes associated with new exposure.

    • Mary Jo V Pugh, Zachary A Marcum, Laurel A Copeland, Eric M Mortensen, John E Zeber, Polly H Noël, Dan R Berlowitz, John R Downs, Chester B Good, Carlos Alvarez, Megan E Amuan, and Joseph T Hanlon.
    • South Texas Veterans Health Care System, Audie L. Murphy Division, Veterans Evidence-based Research Dissemination Implementation CenTer (VERDICT 11C6), San Antonio, TX 78229, USA. PughM@uthscsa.edu
    • Drugs Aging. 2013 Aug 1;30(8):645-54.

    BackgroundClinical validation studies of the Healthcare Effectiveness Data and Information Set (HEDIS®) measures of inappropriate prescribing in the elderly are limited.ObjectivesThe objective of this study was to examine associations of new exposure to high-risk medication in the elderly (HRME) and drug-disease interaction (Rx-DIS) with mortality, hospital admission, and emergency care.MethodsA retrospective database study was conducted examining new use of HRME and Rx-DIS in fiscal year 2006 (Oct 2005-Sep 2006; FY06), with index date being the date of first HRME/Rx-DIS exposure, or first day of FY07 if no HRME/Rx-DIS exposure. Outcomes were assessed 1 year after the index date. The participants were veterans who were ≥65 years old in FY06 and received Veterans Health Administration (VA) care in FY05-06. A history of falls/hip fracture, chronic renal failure, and/or dementia per diagnosis codes defined the Rx-DIS subsample. The variables included a number of new unique HRME drug exposures and new unique Rx-DIS drug exposure (0, 1, >1) in FY06, and outcomes (i.e., 1-year mortality, hospital admission, and emergency care) up to 1 year after exposure. Descriptive statistics summarized variables for the overall HRME cohort and the Rx-DIS subset. Multivariable statistical analyses using generalized estimating equations (GEE) models with a logit link accounted for nesting of patients within facilities. For these latter analyses, we controlled for demographic characteristics, chronic disease states, and indicators of disease burden the previous year (e.g., number of prescriptions, emergency/hospital care).ResultsAmong the 1,807,404 veterans who met inclusion criteria, 5.2 % had new HRME exposure. Of the 256,388 in the Rx-DIS cohort, 3.6 % had new Rx-DIS exposure. Multivariable analyses found that HRME was significantly associated with mortality [1: adjusted odds ratio (AOR) = 1.62, 95 % CI 1.56-1.68; >1: AOR = 1.80, 95 % CI 1.45-2.23], hospital admission (1: AOR = 2.31, 95 % CI 2.22-2.40; >1: AOR = 3.44, 95 % CI 3.06-3.87), and emergency care (1: AOR = 2.59, 95 % CI 2.49-2.70; >1: AOR = 4.18, 95 % CI 3.71-4.71). Rx-DIS exposure was significantly associated with mortality (1: AOR = 1.60, 95 % CI 1.51-1.71; >1: AOR = 2.00, 95 % CI 1.38-2.91), hospital admission for one exposure (1: AOR = 1.12, 95 % CI 1.03-1.27; >1: AOR = 1.18, 95 % CI 0.71-1.95), and emergency care for two or more exposures (1: AOR = 1.06, 95 % CI 0.97-1.15; >1: AOR = 2.0, 95 % CI 1.35-3.10).ConclusionsAnalyses support the link between HRME/Rx-DIS exposure and clinically significant outcomes in older veterans. Now is the time to begin incorporating input from both patients who receive these medications and providers who prescribe to develop approaches to reduce exposure to these agents.

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