Publications

OBJECTIVE: Older adults with diabetes and dementia are at increased risk for hypoglycemia and other adverse events associated with tight glycemic control and are unlikely to experience long-term benefits. We examined risk factors for tight glycemic control in this population and use of medications associated with a high risk of hypoglycemia in the subset with tight control.

RESEARCH DESIGN AND METHODS: This retrospective cohort study of national Veterans Affairs (VA) administrative/clinical data and Medicare claims for fiscal years (FYs) 2008-2009 included 15,880 veterans aged ≥ 65 years with type 2 diabetes and dementia and prescribed antidiabetic medication. Multivariable regression analyses were used to identify sociodemographic and clinical predictors of hemoglobin A1c (HbA1c) control (tight, moderate, poor, or not monitored) and, in patients with tight control, subsequent use of medication associated with a high risk of hypoglycemia (sulfonylureas, insulin).

RESULTS: Fifty-two percent of patients had tight glycemic control (HbA1c <7% [53 mmol/mol]). Specific comorbidities, older age, and recent weight loss were associated with greater odds of tight versus moderate control, whereas Hispanic ethnicity and obesity were associated with lower odds of tight control. Among tightly controlled patients, 75% used sulfonylureas and/or insulin, with higher odds in patients who were male, black, or aged ≥ 75 years; had a hospital or nursing home stay in FY2008; or had congestive heart failure, renal failure, or peripheral vascular disease.

CONCLUSIONS: Many older veterans with diabetes and dementia are at high risk for hypoglycemia associated with intense diabetes treatment and may be candidates for deintensification or alteration of diabetes medications.

OBJECTIVES: To describe variations in potentially inappropriate prescribing (PIP) and characterize the extent to which switching to an incidence-based indicator would affect health system quality rankings.

DESIGN: Observational study.

SETTING: Veterans Health Administration in 2011.

PARTICIPANTS: Older adults receiving outpatient primary care.

MEASUREMENTS: PIP was defined according to the National Committee for Quality Assurance High-Risk Medications in the Elderly list. Ranks were separately assigned for prevalent and incident PIP at the regional, network, and healthcare system levels.

RESULTS: National PIP prevalence was 12.3% (167,766/1,360,251), and incidence was 5.8% (78,604/1,360,251). PIP prevalence ranged from 3.5% to 33.1% across healthcare systems (interquartile range (IQR) = 9.2-15.5%). PIP incidence ranged from 1.2% to 14.9% (IQR = 4.1-7.2%). Rank order in PIP prevalence and incidence was correlated (Spearman correlation; ρ = 0.934, P < .001), although substantial changes in ranks were seen for some healthcare systems, with seven of 139 (5.0%) systems shifting more than 30 rank positions and 21 (15.1%) systems shifting 16 to 30 positions.

CONCLUSION: Prevalence- and incidence-based indicators of prescribing quality were strongly correlated. Transitioning to incidence-based indicators would not produce an initial disruption in quality rankings for most healthcare systems and might yield more-salient measures for tracking healthcare quality.

Effective medications are a cornerstone of prevention and disease treatment, yet only about half of patients take their medications as prescribed, resulting in a common and costly public health challenge for the US health care system. Since poor medication adherence is a complex problem with many contributing causes, there is no one universal solution. This paper describes interventions that were not only effective in improving medication adherence among patients with diabetes, but were also potentially scalable (ie, easy to implement to a large population). We identify key characteristics that make these interventions effective and scalable. This information is intended to inform health care systems seeking proven, low resource, cost-effective solutions to improve medication adherence.

Decisions to control pharmaceutical costs can cause conflicts as to what medications are covered. Such conflicts have ethical implications, however implicit, and given this fact, an ethical framework can help address them. In the following commentary, we discuss the more traditional, individual-level ethical considerations likely familiar to most clinicians. We, then, discuss population-level ethical constructs that clinicians may not as readily embrace. We also present a hypothetical cancer-care case to illustrate how imbalances in ethical foci between individual- and population-level constructs may lead to conflicts among health care actors and promote shifts in pharmaceutical decision making away from providers and toward payers, paradoxically reducing provider autonomy and hence patient autonomy. Finally, we propose a more comprehensive ethical framework to help converge individual, payer, and societal interests when making pharmaceutical use decisions. Pharmacists play a crucial role as pharmacy benefits managers and should be familiar with individual- and population-based ethical constructs.