Geographic Variation in the Prevalence of High-Risk Medication Use Among Medicare Part D Beneficiaries by Hospital Referral Region

BACKGROUND: Understanding geographic patterns of high-risk medication (HRM) prescribed and dispensed among older adults may help the Centers for Medicare & Medicaid Services and their partners develop and tailor prevention strategies. OBJECTIVE: To compare the geographic variation in the prevalence of HRM use among Medicare Part D beneficiaries from 2011 to 2013, for Medicare Advantage Prescription Drug (MA-PD) plans and stand-alone Prescription Drug Plans (PDPs). METHODS: This retrospective study used the data of a 5% national Medicare sample (2011-2013). Beneficiaries were included in the study if they were aged ≥ 65 years, continuously enrolled in MA-PDs or PDPs (~1.3 million each year), and had ≥ 2 prescriptions for the same HRM (e.g., amitriptyline) prescribed and dispensed during the year based on the Pharmacy Quality Alliance’s (PQA) quality measures for HRM use. Multivariable logistic regression was used to estimate adjusted annual HRM use rates (i.e., adjusted predictions, average marginal predictions, or model-adjusted risk) across 306 Dartmouth Atlas of Health Care hospital referral regions (HRRs), controlling for sociodemographic, health-status, and access-to-care factors. RESULTS: Among eligible beneficiaries each year (1,161,076 in 2011, 1,237,653 in 2012, and 1,402,861 in 2013), nearly 40% were enrolled in MA-PD plans, whereas the remaining 60% were in PDP plans. The adjusted prevalence of HRM use significantly decreased among Medicare beneficiaries enrolled in MA-PD (13.1%-8.4%, P < 0.001) and PDP (16.2%-12.2%, P < 0.001) plans from 2011 to 2013. For MA-PD and PDP beneficiaries, HRM users were more likely to be (all P < 0.001) the following: female (MA-PD: 70.4% vs. 59.9%; PDP: 72.8% vs. 62.5%); White (MA-PD: 84.6% vs. 81.4%; PDP: 86.6% vs. 85.3%); with low-income subsidy or dual eligibility for Medicaid (MA-PD: 22.3% vs. 16.6%; PDP: 29.2% vs. 23.3%); and disabled (MA-PD: 15.6% vs. 8.7%; PDP: 15.4% vs. 8.5%) compared with non-HRM users in 2013. In 2013, significant geographic variation existed, with the ratios of 75th-25th percentiles of HRM use rates across HRRs as 1.42 for MA-PDs and 1.31 for PDPs. For MA-PDs, the top 5 HRRs with the highest HRM use rates in 2013 were Casper, WY (20.4%), Waco, TX (16.7%), Lubbock, TX (15.7%), Santa Barbara, CA (15.2%), and Temple, TX (15.1%); for PDPs, they were Lawton, OK (18.8%), Alexandria, LA (18.8%), Lake Charles, LA (18.6%), Oklahoma City, OK (18.0%), and Slidell, LA (18.0%). CONCLUSIONS: Substantial geographic variation exists in the prevalence of HRM use among older adults in Medicare, regardless of prescription drug plan. Areas with high prevalence of HRM use may benefit from targeted interventions (e.g., medication therapy management monitoring or alternative medication substitutions) to prevent potential adverse consequences.

[1]  Tero Alstola,et al.  Research Data , 2019, Judeans in Babylonia.

[2]  Ann M. Taylor,et al.  Initial assessment of an interprofessional team-delivered telehealth program for patients with epilepsy , 2019, Epilepsy Research.

[3]  T. Warholak,et al.  Integrating Innovative Telehealth Solutions into an Interprofessional Team-Delivered Chronic Care Management Pilot Program , 2018, Journal of managed care & specialty pharmacy.

[4]  M. Nahata,et al.  The Effect of Plan Type and Comprehensive Medication Reviews on High-Risk Medication Use , 2018, Journal of managed care & specialty pharmacy.

[5]  T. Warholak,et al.  Evaluation of an Academic-Community Partnership to Implement MTM Services in Rural Communities to Improve Pharmaceutical Care for Patients with Diabetes and/or Hypertension , 2018, Journal of managed care & specialty pharmacy.

[6]  H. Valtonen,et al.  A Systematic Review of the Impact of Potentially Inappropriate Medication on Health Care Utilization and Costs Among Older Adults , 2016, Medical care.

[7]  E. Perfetto,et al.  What Are the Incentives for Medicare Prescription Drug Plans to Consider Long-Term Outcomes and Cost? , 2016, Journal of managed care & specialty pharmacy.

[8]  A. Thiele,et al.  ANALYSIS OF MEDICARE PRESCRIPTION DRUG COVERAGE ENROLLMENT , 2016 .

[9]  Michael J Kallan,et al.  Do Hospital Service Areas and Hospital Referral Regions Define Discrete Health Care Populations? , 2015, Medical care.

[10]  Nicole Brandt,et al.  Prevalence of Potentially Inappropriate Medication Use in Older Adults Using the 2012 Beers Criteria , 2015, Journal of the American Geriatrics Society.

[11]  B. Patel,et al.  Is There an Association Between the High-Risk Medication Star Ratings and Member Experience CMS Star Ratings Measures? , 2014, Journal of managed care & specialty pharmacy.

[12]  James A Owen Medicare star ratings: Stakeholder proceedings on community pharmacy and managed care partnerships in quality: American Pharmacists Association and Academy of Managed Care Pharmacy , 2014 .

[13]  J. Newhouse,et al.  Geographic variation in Medicare services. , 2013, The New England journal of medicine.

[14]  P. Kaboli,et al.  Regional differences in prescribing quality among elder veterans and the impact of rural residence. , 2013, The Journal of rural health : official journal of the American Rural Health Association and the National Rural Health Care Association.

[15]  A. Abu-Hanna,et al.  Inappropriateness of Medication Prescriptions to Elderly Patients in the Primary Care Setting: A Systematic Review , 2012, PloS one.

[16]  S. Greenberg American Geriatrics Society Updated Beers Criteria for Potentially Inappropriate Medication Use in Older Adults , 2012, Journal of the American Geriatrics Society.

[17]  B. Schackman,et al.  Inappropriate Medication in a National Sample of US Elderly Patients Receiving Home Health Care , 2012, Journal of General Internal Medicine.

[18]  J. Hanlon,et al.  Sources of regional variation in Medicare Part D drug spending. , 2012, The New England journal of medicine.

[19]  E John Orav,et al.  Low-quality, high-cost hospitals, mainly in South, care for sharply higher shares of elderly black, Hispanic, and medicaid patients. , 2011, Health affairs.

[20]  Yuting Zhang,et al.  Geographic variation in the quality of prescribing. , 2010, The New England journal of medicine.

[21]  E. Roughead,et al.  Validity of medication‐based co‐morbidity indices in the Australian elderly population , 2009, Australian and New Zealand journal of public health.

[22]  P. Lindenauer,et al.  Potentially inappropriate medication use in hospitalized elders. , 2008, Journal of hospital medicine.

[23]  M. Beers,et al.  Health outcomes associated with potentially inappropriate medication use in older adults. , 2008, Research in nursing & health.

[24]  S. Pocock,et al.  The Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) statement: guidelines for reporting observational studies. , 2007, Preventive medicine.

[25]  Chuan-Fen Liu,et al.  Comparison of risk adjustment measures based on self-report, administrative data, and pharmacy records to predict clinical outcomes , 2006, Health Services and Outcomes Research Methodology.

[26]  Peter J. Richardson,et al.  Adapting the Rx-Risk-V for Mortality Prediction in Outpatient Populations , 2006, Medical care.

[27]  J. Farley,et al.  A comparison of comorbidity measurements to predict healthcare expenditures. , 2006, The American journal of managed care.

[28]  Linda Gavendo,et al.  The incidence of adverse drug events in two large academic long-term care facilities. , 2005, The American journal of medicine.

[29]  M. Beers,et al.  Updating the Beers criteria for potentially inappropriate medication use in older adults: results of a US consensus panel of experts. , 2003, Archives of internal medicine.

[30]  Stephen H. D. Jackson,et al.  Age-related changes in pharmacokinetics and pharmacodynamics: basic principles and practical applications. , 2003, British journal of clinical pharmacology.

[31]  Anne E Sales,et al.  Construction and Characteristics of the RxRisk-V: A VA-Adapted Pharmacy-Based Case-mix Instrument , 2003, Medical care.

[32]  Paul A. Fishman,et al.  Risk Adjustment Using Automated Ambulatory Pharmacy Data: The RxRisk Model , 2003, Medical care.

[33]  D B Reuben,et al.  Explicit criteria for determining inappropriate medication use in nursing home residents. UCLA Division of Geriatric Medicine. , 1991, Archives of internal medicine.

[34]  Academy of Managed Care Pharmacy,et al.  Medicare star ratings: stakeholder proceedings on community pharmacy and managed care partnerships in quality. , 2014, Journal of the American Pharmacists Association : JAPhA.

[35]  D. Touchette,et al.  Medication Therapy Management Services , 2012, Drugs.

[36]  John E. Wennberg,et al.  Tracking the Care of Patients with Severe Chronic Illness: The Dartmouth Atlas of Health Care 2008 , 2008 .

[37]  P. Barry,et al.  Inappropriate prescribing in an acutely ill population of elderly patients as determined by Beers' Criteria. , 2008, Age and ageing.

[38]  R. Schlienger,et al.  Prevalence of Potentially Inappropriate Medication Use in Elderly Patients , 2006, Drugs & aging.

[39]  B. McDowell,et al.  National Committee for Quality Assurance. , 2004, Social work.