What is the optimal subsidy for exercise? Informing health insurance companies\u27 fitness reimbursement programs

Health care costs account for 17% of US GDP and many programs and policies seek to reduce these costs. This paper focuses on exercise as preventive care due to its immense physiological benefits. I model the profit-maximizing choice of health insurance companies to subsidize exercise and the utility-maximizing choice of individuals to engage in exercise using a traditional principal-agent framework. I then use principles from behavioral economics and psychology to critique these models and provide further insight into understanding our underconsumption of such preventive services. I end with an evaluation of current programs and suggestions for improvement using empirical findings

Premium Subsidies, the Mandate, and Medicaid Expansion: Coverage Effects of the Affordable Care Act

Using premium subsidies for private coverage, an individual mandate, and Medicaid expansion, the Affordable Care Act (ACA) has increased insurance coverage. We provide the first comprehensive assessment of these provisions’ effects, using the 2012-2015 American Community Survey and a triple-difference estimation strategy that exploits variation by income, geography, and time. Overall, our model explains 60% of the coverage gains in 2014-2015. We find that coverage was moderately responsive to price subsidies, with larger gains in state-based insurance exchanges than the federal exchange. The individual mandate’s exemptions and penalties had little impact on coverage rates. The law increased Medicaid among individuals gaining eligibility under the ACA and among previously-eligible populations (“woodwork effect”) even in non-expansion states, with essentially no crowd-out of private insurance. Overall, exchange premium subsidies produced 40% of the coverage gains explained by our ACA policy measures, and Medicaid the other 60%, of which 1/2 occurred among previously-eligible individuals

Understanding Manufacturer-Sponsored Copay Assistance Programs For Pharmaceuticals

Manufacturer-sponsored copay assistance is an increasingly common and controversial practice in the US prescription drug industry. While manufacturers claim that their copay coupons help underinsured patients access valuable therapies, insurers are concerned that the discounts undermine cost-sharing as a means to address moral hazard and constrain prices. To date, research and policy on coupons have largely focused on coupons offered for branded drugs with generic equivalents. Much less is understood about coupons for branded drugs without generic equivalents, despite the fact that they comprise over half of all couponed drugs. In this paper, I develop an economic model of coupons and show that coupons may raise spending through both higher prices and higher quantities. Importantly, I also show that the effect of coupons on total welfare is ambiguous and depends in part on whether a generic equivalent is available. In a complementary empirical analysis, I combine a novel dataset of coupon offers with administrative claims data from a large national insurer to estimate the effects of coupon introductions between 2015 and 2018. I use difference-in-difference methods to address the potential endogeneity of coupon offers and introduce a measure of coupon exposure that exploits variation in cost-sharing across insurance plans. I find that for brands with a generic equivalent available, coupons increased prescription fills by 6%. However, coupons had limited, if any, impacts on utilization of brands that did not face generic competition. I also find evidence that coupons undermine the role of generic competition in constraining branded drug prices. Policy-makers should pursue restrictions on coupon use for branded drugs in the presence of generic equivalents and support further research on coupons in their absence

Premium subsidies, the mandate, and Medicaid expansion: Coverage effects of the Affordable Care Act

Using premium subsidies for private coverage, an individual mandate, and Medicaid expansion, the Affordable Care Act (ACA) has increased insurance coverage. We provide the first comprehensive assessment of these provisions’ effects, using the 2012–2015 American Community Survey and a triple-difference estimation strategy that exploits variation by income, geography, and time. Overall, our model explains 60% of the coverage gains in 2014–2015. We find that coverage was moderately responsive to price subsidies, with larger gains in state-based insurance exchanges than the federal exchange. The individual mandate's exemptions and penalties had little impact on coverage rates. The law increased Medicaid among individuals gaining eligibility under the ACA and among previously-eligible populations (“woodwork effect”) even in non-expansion states, with no resulting reductions in private insurance. Overall, exchange premium subsidies produced 40% of the coverage gains explained by our ACA policy measures, and Medicaid the other 60%, of which 1/2 occurred among previously-eligible individuals

Disentangling the ACA’s Coverage Effects — Lessons for Policymakers

Since the passage of the Affordable Care Act (ACA), an estimated 20 million Americans have gained health insurance, and the country’s uninsured rate has dropped from 16% to 9% since 2010.1 In the upcoming presidential election, the ACA’s future is again at stake. Understanding how the law has achieved these coverage changes is critical to evaluating its progress

El Diario de Pontevedra : periódico liberal: Ano XXIX Número 8565 - 1912 novembro 26

Abstract Background Administrative healthcare claims data provide a mechanism for assessing and monitoring multiple sclerosis (MS) disease status across large, clinically representative “real-world” populations. The estimation of MS disease status using administrative claims can be a challenge, however, due to a lack of detailed clinical information. Retrospective claims analyses in MS have traditionally used rates of MS relapses to approximate disease status. Healthcare costs may be alternate, broader claims-based indicators of disease activity because costs reflect multiple facets of care of patients with MS, and there is a strong correlation between quality of life of patients with MS and costs of the disease. This study developed, tested, and validated a healthcare cost-based measure to serve as an indicator of overall disease status in patients with MS treated with disease-modifying drugs (DMDs) utilizing administrative claims. Methods Using IMS Health Real World Data Adjudicated Claims – US data (January 2006–June 2013), a negative binomial regression predicted annual all-cause medical costs. Coefficients reaching statistical significance (p < 0.05) and increasing costs by ≥5% were selected for inclusion into an MS-specific severity score (scale of 0 to 100). Components of the score included rehabilitation services, altered mental state, pain, disability, stiffness, balance disorder, urinary incontinence, numbness, malaise/fatigue, and infections. Coefficient weights represented each predictor’s contribution. The predictive model was derived using 50% of a random sample and tested/validated using the remaining 50%. Results Average overall predicted annual total medical cost was $11,134 (development sample, n = 11,384, vs.$10,528 actual) and $11,303 (validation sample, n = 11,385, vs.$10,620 actual). The model had consistent bias (approximately +$600 or +6$5243 predicted vs. $5233 actual cost for lowest tertile). Conclusion The algorithm developed in this study provides an initial step to helping understand and potentially predict cost changes for a commercially insured MS population

Patient experiences of integrated care in medicare accountable care organizations and medicare advantage versus traditional fee-for-service

BACKGROUND: Health insurance design can influence the extent to which clinical care is well-coordinated. Through alternative payment models, Medicare Advantage (MA) and Accountable Care Organizations (ACOs) have the potential to improve integration relative to traditional fee-for-service (FFS) Medicare. OBJECTIVE: To characterize patient experiences of integrated care within Medicare and identify whether MA or ACO beneficiaries perceive greater integration than FFS beneficiaries. DESIGN: Retrospective cross-sectional analysis of the 2015 Medicare Current Beneficiary Survey. SUBJECTS: Nationally representative sample of 11,978 Medicare beneficiaries. MEASURES: Main outcomes included 8 previously derived domains of patient-perceived integrated care (PPIC), measured on a scale of 1-4. RESULTS: The final sample was 55% female with a mean (SD) age of 71.1 (11.3). In unadjusted analyses, we observed considerable variation across PPIC domains in the full sample, but little variation across subsamples defined by coverage type within a given PPIC domain. In linear models adjusting for a rich set of patient characteristics, we observe no significant benefits of ACOs nor MA relative to FFS, a finding which is robust to alternative specifications and adjustment for multiple comparisons. We similarly observed no benefits in subgroup analyses restricted to states with relatively high market penetration of ACOs or MA. CONCLUSIONS: Despite characteristics of ACOs and MA that theoretically promote integrated care, we find that PPIC is largely similar across coverage types in Medicare

Patients' Perceptions of Integrated Care Among Medicare Beneficiaries by Level of Need for Health Services

Requirements for integrating care across providers, settings, and over time increase with patients' needs. Health care providers' ability to offer care that patients experience as integrated may vary among patients with different levels of need. We explore the variation in patients' perceptions of integrated care among Medicare beneficiaries based on the beneficiary's level of need using ordinary least square regression for each of four high-need groups: beneficiaries (a) with complex chronic conditions, (b) with frailties, (c) below 65 with disability, and (d) with any (of the first three) high needs. We control for beneficiary demographics and other factors affecting integrated care, and we conduct sensitivity analyses controlling for multiple individual chronic conditions. We find significant positive associations with level of need for provider support for self-directed care and medication and home health management. Controlling for multiple individual chronic conditions reduces effect sizes and number of significant relationships