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The Quality of Quality Measures: HEDIS® Quality Measures for Medication Management in the Elderly and Outcomes Associated with New Exposure

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Abstract

Background

Clinical validation studies of the Healthcare Effectiveness Data and Information Set (HEDIS®) measures of inappropriate prescribing in the elderly are limited.

Objectives

The 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.

Methods

A 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).

Results

Among 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).

Conclusions

Analyses 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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References

  1. Steinman MA, Hanlon JT. Managing medications in clinically complex elders: “There’s got to be a happy medium”. JAMA. 2010;304(14):1592–601.

    Article  PubMed  CAS  Google Scholar 

  2. Institute of Medicine. To err is human: building a safer health system. Washington, DC: National Academies Press; 1999.

    Google Scholar 

  3. Wenger NS, Young RT. Quality indicators for continuity and coordination of care in vulnerable elders. J Am Geriatr Soc. 2007;55(s2):S285–92.

    Google Scholar 

  4. Brook RH, McGlynn EA, Shekelle PG. Defining and measuring quality of care: a perspective from US researchers. Qual Assur Health Care. 2000;12(4):281–95.

    Article  CAS  Google Scholar 

  5. Beers MH, Ouslander JG, Rollingher I, et al. Explicit criteria for determining inappropriate medication use in nursing home residents. Arch Intern Med. 1991;151(9):1825–32.

    Article  PubMed  CAS  Google Scholar 

  6. Beers MH. Explicit criteria for determining potentially inappropriate medication use by the elderly. Arch Intern Med. 1997;157(14):1531–6.

    Article  PubMed  CAS  Google Scholar 

  7. Fick DM, Cooper JW, Wade WE, et al. Updating the Beers criteria for potentially inappropriate medication use in older adults: results of a US consensus panel of experts. Arch Intern Med. 2003;163(22):2716–24.

    Article  PubMed  Google Scholar 

  8. Pugh MJ, Hanlon JT, Zeber JE, et al. Assessing potentially inappropriate prescribing in the elderly Veterans Affairs population using the HEDIS® 2006 quality measure. J Manag Care Pharm. 2006;12(7):537–45.

    PubMed  Google Scholar 

  9. Albert SM, Colombi A, Hanlon J. Potentially inappropriate medications and risk of hospitalization in retirees: analysis of a US retiree health claims database. Drugs Aging. 2010;27(5):407–15.

    Article  PubMed  Google Scholar 

  10. Pugh MJ, Palmer RF, Parchman ML, Mortensen E, Markides K, Espino DV. Association of suboptimal prescribing and change in lower extremity physical function over time. Gerontology. 2007;53(6):445–53.

    Article  PubMed  Google Scholar 

  11. Fillenbaum GG, Hanlon JT, Landerman LR, Artz MB, O’Connor H, Dowd B, et al. Impact of inappropriate drug use on health services utilization among representative older community-dwelling residents. Am J Geriatr Pharmacother. 2004;2(2):92–101.

    Article  PubMed  Google Scholar 

  12. Hanlon JT, Artz MB, Pieper CF, Lindblad CI, Sloane RJ, Ruby CM, et al. Inappropriate medication use among frail elderly inpatients. Ann Pharmacother. 2004;38(1):9–14.

    Article  PubMed  Google Scholar 

  13. Fu AZ, Liu GG, Christensen DB. Inappropriate medication use and health outcomes in the elderly. J Am Geriatr Soc. 2004;52(11):1934–9.

    Article  PubMed  Google Scholar 

  14. Pugh MJ, Hanlon JT, Wang C-P, Semla T, Burk M, Amuan ME, et al. Trends in use of high-risk medications for older veterans: 2004 to 2006. J Am Geriatr Soc. 2011;59(10):1891–8.

    Article  PubMed  Google Scholar 

  15. Pugh MJ, Starner CI, Amuan ME, Berlowitz DR, Horton M, Marcum ZA, et al. Exposure to potentially harmful drug–disease interactions in older community-dwelling veterans based on the Healthcare Effectiveness Data and Information Set quality measure: who is at risk? J Am Geriatr Soc. 2011;59(9):1673–8.

    Article  PubMed  Google Scholar 

  16. Ray WA. Evaluating medication effects outside of clinical trials: new-user designs. Am J Epidemiol. 2003;158(9):915–20.

    Article  PubMed  Google Scholar 

  17. VA Information Resource Center. VIReC research user guide: VHA pharmacy prescription data. Washington, DC: VA Information Resource Center (VIReC); 2008 [online]. http://www.virec.research.va.gov/References/RUG/RUG.htm. Accessed Sept 2008.

  18. VA Information Resource Center. Medical SAS® inpatient dataset FY2009: VIReC research user guide. Hines (IL): VIReC; 2011 [online]. http://www.virec.research.va.gov/DataSourcesName/Medical-SAS-Datasets/MedSAS-Inpt-RUG/MedSAS-RUG-Inpt.htm. Accessed Feb 2011.

  19. VA Information Resource Center. VHA Medical SAS® outpatient datasets and inpatient encounters dataset FY2009: VIReC Research User Guide. Washington, DC: VA Information Resource Center; 2011 [online]. http://www.virec.research.va.gov/DataSourcesName/Medical-SAS-Datasets/MedSAS-Outpt-RUG/MedSAS-RUG-Outpt.htm. Accessed Apr 2011.

  20. Arnold N, Sohn MW, Maynard C, et al. VIReC Technical Report 2: VA-NDI mortality data merge project. Hines: VA Information Resource Center; 2006.

    Google Scholar 

  21. Sohn M, Arnold N, Maynard C, et al. Accuracy and completeness of mortality data in the Department of Veterans Affairs. Popul Health Metr. 2006;4:2.

    Article  PubMed  Google Scholar 

  22. National Committee on Quality Assurance. Proposed changes to existing measure for HEDIS® 2012: potentially harmful drug–disease interactions in the elderly. (DDE) Washington, DC: National Committee for Quality Assurance; 2011.

  23. National Committee on Quality Assurance. HEDIS® 2008 NDC Lists. Washington, DC; 2011 [online]. http://www.NCQA.org/tabid/598/Default.aspx. Accessed 4 Feb 2011.

  24. Fick DM, Mion LC, Beers MH, et al. Health outcomes associated with potentially inappropriate medication use in older adults. Res Nurs Health. 2008;31(1):42–51.

    Article  PubMed  Google Scholar 

  25. Hanlon JT, Fillenbaum GG, Kuchibhatla M, et al. Impact of inappropriate drug use on mortality and functional status in representative community dwelling elders. Med Care. 2002;40(2):166–76.

    Article  PubMed  Google Scholar 

  26. Spinewine A, Schmader KE, Barber N, et al. Appropriate prescribing in elderly people: how well can it be measured and optimised? Lancet. 2007;370(9582):173–84.

    Article  PubMed  Google Scholar 

  27. Budnitz DS, Lovegrove MC, Shehab N, et al. Emergency hospitalizations for adverse drug events in older Americans. N Engl J Med. 2011;365(21):2002–12.

    Article  PubMed  CAS  Google Scholar 

  28. Hellstrom LM, Bondesson A, Hoglund P, et al. Impact of the Lund Integrated Medicines Management (LIMM) model on medication appropriateness and drug-related hospital revisits. Eur J Clin Pharmacol. 2011;67(7):741–52.

    Article  PubMed  Google Scholar 

  29. Aspden P, Wolcott J, Bootman JL, Cronenwett LR, editors. Preventing medication errors: quality chasm series. Washington, DC: National Academies Press; 2007.

    Google Scholar 

  30. Selim AJ, Berlowitz DR, Ren XS, et al. The comorbidity index. In: Davies M, editor. Measuring and managing health care quality. New York: Aspen Publishers; 2002. p. 91–4.

    Google Scholar 

  31. Selim A, Fincke G, Ren X, et al. Comorbidity assessments based on patient report: results from the Veterans Health Study. J Ambul Care Manage. 2004;27(3):281–95.

    Article  PubMed  Google Scholar 

  32. Bindman AB, Grumbach K, Osmond D, et al. Preventable hospitalizations and access to health care. JAMA. 1995;274(4):305–11.

    Article  PubMed  CAS  Google Scholar 

  33. Zeger SL, Liang KY. Longitudinal data analysis for discrete and continuous outcomes. Biometrics. 1986;42(1):121–30.

    Article  PubMed  CAS  Google Scholar 

  34. Liang KY, Zeger SL. Longitudinal data-analysis using generalized linear-models. Biometrika. 1986;73(1):13–22.

    Article  Google Scholar 

  35. Austin PC. An introduction to propensity score methods for reducing the effects of confounding in observational studies. Multivariate Behav Res. 2011;46(3):399–424.

    Article  PubMed  Google Scholar 

  36. Budnitz DS, Shehab N, Kegler SR, et al. Medication use leading to emergency department visits for adverse drug events in older adults. Ann Intern Med. 2007;147(11):755–65.

    Article  PubMed  Google Scholar 

  37. Marcum ZA, Amuan ME, Hanlon JT, et al. Prevalence of unplanned hospitalizations caused by adverse drug reactions in older veterans. J Am Geriatr Soc. 2012;60(1):34–41.

    Article  PubMed  Google Scholar 

  38. Lund BC, Chrischilles EA, Kaboli PJ. Beers criteria as a proxy for inappropriate prescribing of other medications among older adults. Ann Pharmacother. 2011;45(11):1363–70.

    Google Scholar 

  39. Schmader KE, Hanlon JT, Landsman PB, et al. Inappropriate prescribing and health outcomes in elderly veteran outpatients. Ann Pharmacother. 1997;31(5):529–33.

    PubMed  CAS  Google Scholar 

  40. Olsson IN, Runnamo R, Engfeldt P. Medication quality and quality of life in the elderly, a cohort study. Health Qual Life Outcomes. 2011;9:95.

    Article  PubMed  Google Scholar 

  41. Lund BC, Carnahan RM, Egge JA, et al. Inappropriate prescribing predicts adverse drug events in older adults. Ann Pharmacother. 2010;44(6):957–63.

    Article  PubMed  Google Scholar 

  42. Hanlon JT, Wang X, Handler SM, et al. Potentially inappropriate prescribing of primarily renally cleared medications for older veterans affairs nursing home patients. J Am Med Dir Assoc. 2011;12(5):377–83.

    Article  PubMed  Google Scholar 

  43. Chirn-Bin C, Ding-Cheng C. Comparison of published explicit criteria for potentially inappropriate medications in older adults. Drugs Aging. 2010;27(12):947–57.

    Article  Google Scholar 

  44. Zekry D, Loures Valle BH, Graf C, et al. Prospective comparison of 6 comorbidity indices as predictors of 1-year post-hospital discharge institutionalization, readmission, and mortality in elderly individuals. J Am Med Dir Assoc. 2012;13(3):272–8.

    Google Scholar 

  45. Chrischilles EA, VanGilder R, Wright K, et al. Inappropriate medication use as a risk factor for self-reported adverse drug effects in older adults. J Am Geriatr Soc. 2009;57(6):1000–6.

    Article  PubMed  Google Scholar 

  46. Hanlon JT, Schmader KE. How important are drug–drug interactions to the health of older adults? Am J Geriatr Pharmacother. 2011;9(6):361–3.

    Article  PubMed  Google Scholar 

  47. The American Geriatrics Society Beers Criteria Update Expert Panel. American Geriatrics Society updated Beers criteria for potentially inappropriate medication use in older adults. J Am Geriatr Soc. 2012;60(4):616–31.

    Article  Google Scholar 

  48. Centers for Disease Control and Prevention (CDC). The state of aging and health in America 2007. Whitehouse Station: The Merck Company Foundation; 2007.

  49. Morgan R, Teal C, Reddy S, et al. Measurement in Veterans Affairs health services research: veterans as a special population. Health Serv Res. 2005;40(5 Pt 2):1573–83.

    Article  PubMed  Google Scholar 

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Acknowledgments

This study was funded by VA Health Services Research and Development Service, IIR 06-062 (Dr. Pugh PI). The funding agency had no role in data collection, analysis, or manuscript development. No conflict of interest is reported for any co-authors. We also acknowledge assistance with manuscript preparation by Jeffrey Tabares, Margaret Wells, and Kathleen Franklin. The views expressed in this article are those of the authors and do not necessarily represent the views of the Department of Veterans Affairs. The authors acknowledge and appreciate support from the South Texas Veterans Healthcare System/Audie L. Murphy Division and the VERDICT research program, and from the Central Texas Veterans Healthcare System, Center for Applied Health Research. Data from this paper was presented at the VA Health Services Research and Development Annual Research Meeting, National Harbor, MD, July 2012.

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Authors and Affiliations

  1. South Texas Veterans Health Care System, Audie L. Murphy Division, Veterans Evidence-based Research Dissemination Implementation CenTer (VERDICT 11C6), 7400 Merton Minter Boulevard, San Antonio, TX, 78229, USA

    Mary Jo V. Pugh, Polly H. Noël & John R. Downs

  2. University of Texas Health Science Center at San Antonio, San Antonio, TX, USA

    Mary Jo V. Pugh, Polly H. Noël & John R. Downs

  3. Division of Geriatric Medicine, Department of Medicine, School of Medicine, University of Pittsburgh, Pittsburgh, PA, USA

    Zachary A. Marcum & Joseph T. Hanlon

  4. Central Texas Veterans Healthcare System, Temple, TX, USA

    Laurel A. Copeland & John E. Zeber

  5. Center for Applied Health Research, Scott & White Healthcare jointly with Central Texas Veterans Health Care System, Temple, TX, USA

    Laurel A. Copeland & John E. Zeber

  6. VA North Texas Health Care System, Dallas, TX, USA

    Eric M. Mortensen

  7. University of Texas Southwestern Medical Center, Dallas, TX, USA

    Eric M. Mortensen & Carlos Alvarez

  8. Texas Tech University Health Sciences Center, Dallas, TX, USA

    Carlos Alvarez

  9. Center for Health Quality Outcomes and Economic Research (CHQOER), Edith Nourse Rogers Memorial Veterans Hospital, Bedford, MA, USA

    Dan R. Berlowitz & Megan E. Amuan

  10. Veterans Affairs Pittsburgh Healthcare System, Center for Health Equity Research and Promotion (CHERP), Pittsburgh, PA, USA

    Chester B. Good

  11. Division of General Medicine, University of Pittsburgh, Pittsburgh, PA, USA

    Chester B. Good

  12. Department of Veterans Affairs, Pharmacy Benefits Management Services, Hines, IL, USA

    Chester B. Good

Authors
  1. Mary Jo V. Pugh
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  2. Zachary A. Marcum
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  3. Laurel A. Copeland
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  4. Eric M. Mortensen
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  7. Dan R. Berlowitz
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  8. John R. Downs
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  9. Chester B. Good
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  10. Carlos Alvarez
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  11. Megan E. Amuan
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  12. Joseph T. Hanlon
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Correspondence to Mary Jo V. Pugh.

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Pugh, M.J.V., Marcum, Z.A., Copeland, L.A. et al. The Quality of Quality Measures: HEDIS® Quality Measures for Medication Management in the Elderly and Outcomes Associated with New Exposure. Drugs Aging 30, 645–654 (2013). https://doi.org/10.1007/s40266-013-0086-8

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  • DOI: https://doi.org/10.1007/s40266-013-0086-8

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