BACKGROUND: Heart failure is a prevailing diagnosis of hospitalization and readmission within 6 months, and nearly a quarter of these patients die within a year. Guideline-directed medication therapies reduce risk of mortality by 73% over 2 years; however, the implementation of these therapies to their target dose in clinical practice continues to be challenging. In 2020, the Veterans Affairs (VA) Health Care System developed a HF dashboard to monitor and improve outpatient HF management. The DASH-HF (Dashboard Activated Services and Telehealth for Heart Failure) study is a randomized, pragmatic clinical trial to evaluate proactive dashboard-directed telehealth clinics to improve the use and dosing of guideline-directed medication therapy for patients with heart failure with reduced ejection fraction not on optimal guideline-directed medication therapy within the VA. METHODS: Three hundred veterans with heart failure with reduced ejection fraction met inclusion criteria with an optimization potential score (OPS) of 5 or less out of 10, representing nonoptimal guideline-directed medication therapy. The primary outcome was a composite score of guideline-directed medical therapy, the OPS, 6 months after the end of the intervention. Secondary outcomes included active prescriptions for each individual guideline-directed medical therapy class, HF-related hospitalizations, deaths, and clinician time per patient during the intervention clinics. RESULTS: There was no significant difference between the intervention arm and usual care group in the primary outcome (OPS, 2.9; SD=2.1 versus OPS, 2.6, SD=2.1); adjusted mean difference 0.3 (95% CI, −0.1 to 0.7) or in the prespecified secondary outcomes for hospitalization and all-cause mortality for the intervention of proactive dashboard-based clinics. CONCLUSIONS: A dashboard-based clinic intervention did not improve the OPS or secondary outcomes of hospitalization and all-cause mortality. There remains a larger opportunity to better target patients and provide more intensive follow-up to further evaluate the utility of proactive dashboard-based clinics for HF management and quality improvement. REGISTRATION: URL: https://www.clinicaltrials.gov ; Unique identifier: NCT05001165.
Due to the nature of health insurance in the United States, health care utilization is often tied to economic conditions, at both the individual and aggregate levels. This article examines how loss of employment may reduce medication adherence through the subsequent loss of insurance and income. At the individual level, the loss of employer-sponsored insurance is shown to be associated with lower prescription drug use and higher out-of-pocket expenditures. The rapid increase in unemployment during the COVID-19 pandemic provides a natural experiment to estimate the causal relationship between unemployment and prescription drug use at the aggregate level. In total, the growth in unemployment during the pandemic resulted in a 2.6% reduction in medication adherence and 57.5 million fewer prescriptions filled in 2020, with prescriptions declining for many chronic conditions. Unemployment-related reductions in prescription fills and medication adherence were highest in states without expanded Medicaid eligibility, further underscoring the importance of social safety nets such as Medicaid during times of economic hardship.
Objective To characterize price trends and variation for US generic and branded drugs at the retail level as they relate to pharmacy acquisition costs and local market factors. Data Sources Drug pricing data consisting of US pharmacy claims from 2014 to 2019 collected and licensed by GoodRx, an online tool for comparing drug prices. Study Design Time trends of median drug prices and coefficients of variation were measured for generic and branded drugs, including subgroups based on clinical condition (i.e., diabetes and cancer). Pharmacy competition was measured using the Herfindahl–Hirschman Index (HHI) at the zip‐code level. Multivariable linear regression analysis assessed the impact of local market‐level factors on drug prices and variation. Data Collection US drug pricing data consisting of claims filled through a mix of public and private insurance at 58,332 chain and independent pharmacies across 14,421 zip codes in all 50 states. Principal Findings From 2014 to 2019, pharmacy retail markets trended towards greater competition: average HHI by zip code decreased by 15.0% (p < 0.001). Median cash price increased significantly for both generic (6.58%, p < 0.001) and branded (84.10%, p < 0.001) drugs. When normalized to acquisition costs, cash prices for generic drugs rose 22.03% (p < 0.001) while those of branded drugs decreased by 2.31% (p < 0.001). Diabetes drugs showed higher baseline overall markup of cash prices relative to acquisition costs (10.54, Interquartile range (IQR) 3.28–18.43) than cancer drugs (1.88, IQR 1.36–3.08). Neither local pharmacy competition nor median income significantly predicted drug price or variation. Conclusion Measures of generic drug price and price variation are high despite decreased costs earlier in the pharmaceutical supply chain, defying expectations of what would happen in a competitive market. Efforts to bypass the pharmacy benefit model for generic drugs may offer consumers an opportunity for substantial savings.
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