Delivering Public Health Insurance Through Private Plan Choice in the United States

Heterogeneity within the Oregon Health Insurance Experiment: An application of causal forests

Existing evidence regarding the effects of Medicaid expansion, largely focused on aggregate effects, suggests health insurance impacts some health, healthcare utilization, and financial hardship outcomes. In this study we apply causal forest and instrumental forest methods to data from the Oregon Health Insurance Experiment (OHIE), to explore heterogeneity in the uptake of health insurance, and in the effects of (a) lottery selection and (b) health insurance on a range of health-related outcomes. The findings of this study suggest that the impact of winning the lottery on the health insurance uptake varies among different subgroups based on age and race. In addition, the results generally coincide with findings in the literature regarding the overall effects: lottery selection (and insurance) reduces out-of-pocket spending, increases physician visits and drug prescriptions, with little (short-term) impact on the number of emergency department visits and hospital admissions. Despite this, we detect quite weak evidence of heterogeneity in the effects of the lottery and of health insurance across the outcomes considered.

What Difference Does a Health Plan Make? Evidence from Random Plan Assignment in Medicaid

Exploiting the random assignment of Medicaid beneficiaries to managed care plans, we find substantial plan-specific spending effects despite plans having identical cost sharing. Enrollment in the lowest-spending plan reduces spending by at least 25%-primarily through quantity reductions-relative to enrollment in the highest-spending plan. Rather than reducing "wasteful" spending, lower-spending plans broadly reduce medical service provision-including the provision of low-cost, high-value care-and worsen beneficiary satisfaction and health. Consumer demand follows spending: a 10 percent increase in plan-specific spending is associated with a 40 percent increase in market share. These facts have implications for the government's contracting problem and program cost growth.

Financial transaction costs reduce benefit take-up evidence from zero-premium health insurance plans in Colorado

With the passage of the American Recovery Plan Act of 2021, roughly 12 million Americans are eligible to purchase zero-premium Health Insurance Marketplace plans. Millions more are eligible for generously subsidized health plans with small, positive premiums. What difference does a premium of zero make, relative to a slightly positive premium? Using a regression discontinuity design and administrative data from Colorado, we find that zero-premium plans increase coverage, primarily by helping low-income households begin coverage sooner. The main mechanism is eliminating the transaction costs of having to make on-time payments to begin coverage. Transaction costs may be a meaningful barrier to subsidized insurance coverage take-up, particularly for low-income families.

The Two-Margin Problem in Insurance Markets

Insurance markets often feature consumer sorting along both an extensive margin (whether to buy) and an intensive margin (which plan to buy). We present a new graphical theoretical framework that extends a workhorse model to incorporate both selection margins simultaneously. A key insight from our framework is that policies aimed at addressing one margin of selection often involve an economically meaningful trade-off on the other margin in terms of prices, enrollment, and welfare. Using data from Massachusetts, we illustrate these trade-offs in an empirical sufficient statistics approach that is tightly linked to the graphical framework we develop.

The pattern of health insurance economic resilience in the Covid 19 pandemic shock

Objective

Health insurance is based on people’s significant risks in receiving health services that they cannot afford alone. Since the outbreak of the corona epidemic, the health insurance system has suffered many economic problems. Designing a model of a health insurance system based on the requirements of a resilient economy can improve the functions of this system in the corona crisis.

Results

In this research 12, structural components were obtained in the form of 4 conceptual components. The 4 main conceptual components are Knowledge-based economy, Economic stability, Economic resilience, and justice. The knowledge-based economy is the basis for the formation of economic resilience in the health insurance systems. Health insurance systems will achieve two crucial intermediate results, namely economic resilience, and economic stability, by building the basic infrastructure of a knowledge-based economy. In the long run, maintaining such intermediate results is the foundation of justice in the health insurance system.

Supplementary Information

The online version contains supplementary material available at 10.1186/s13104-021-05779-2.

A supervised clustering MCMC methodology for large categorical feature spaces

There is a well-established tradition within the statistics literature that explores different techniques for reducing the dimensionality of large feature spaces. The problem is central to machine learning and it has been largely explored under the unsupervised learning paradigm. We introduce a supervised clustering methodology that capitalizes on a Metropolis Hastings algorithm to optimize the partition structure of a large categorical feature space tailored towards minimizing the test error of a learning algorithm. This is a general methodology that can be applied to any supervised learning problem with a large categorical feature space. We show the benefits of the algorithm by applying this methodology to the problem of risk adjustment in competitive health insurance markets. We use a large claims data set that records ICD-10 codes, a large categorical feature space. We aim at improving risk adjustment by clustering diagnostic codes into risk groups suitable for health expenditure prediction. We test the performance of our methodology against common alternatives using panel data from a representative sample of twenty three million citizens in Colombian Healthcare System. Our results outperform common alternatives and suggest that it has potential to improve risk adjustment.

Treatment flows after outsourcing public insurance provision: Evidence from Florida Medicaid

While politics can determine what public goods are available, elected officials must decide on the method of allocation. Commonly, governments provide public health insurance directly or pay private parties to administer it on their behalf. Such contracting can leverage private sector expertise but also raises agency concerns. In particular, little is known about how private provision of public health insurance impacts medical decision-making and treatment flows for low-income populations. An example comes from the Medicaid program, which has increasingly relied on outside insurers to deliver health services to enrollees. We exploit a large legislative intervention in Florida to show that Medicaid managed care (MMC) organizations generally do not skimp on short-run treatment delivery in the inpatient setting. In fact, patients with severe and chronic illnesses receive more inpatient services under these contracts, especially in relation to managing care transitions. We also document increased competition in the MMC market following the state's policy intervention.

How protected classes in Medicare Part D influence U.S. drug sales, utilization, and price

When the Medicare Part D prescription drug benefit was implemented in 2006, six drug classes were designated "protected classes." Because responsibility for obtaining favorable drug prices depends on private insurers' abilities to negotiate with pharmaceutical manufacturers using the threat of formulary exclusion, the protected class designation could undermine the insurers' ability to control spending and utilization of drugs in these six classes. I estimate the effect of the protected class policy on U.S. national drug sales, utilization, and price using 2001-2010 IMS Health National Sales Perspectives data and Verispan Vector One: National data and controlling for drug and year fixed effects. I find that protected status beginning in 2006 led to $112-121 million per drug per year higher U.S. sales for drugs in protected classes relative to unprotected drugs. Greater sales were driven by the antidepressant, antipsychotic, anticonvulsant, and antineoplastic classes. Subsequent analyses on a subset of drugs reveal that increases in both price and quantity are responsible for the growth of sales in protected class drugs. These results are important for informing the recent and ongoing deliberation by the Medicare program over whether to remove several classes from protection.

Subsidy Design in Privately Provided Social Insurance: Lessons from Medicare Part D

The efficiency of publicly-subsidized, privately-provisioned social insurance programs depends on the interaction between strategic insurers and the subsidy mechanism. We study this interaction in the context of Medicare's prescription drug coverage program. We find that the observed mechanism is successful in keeping "raise-the-subsidy" incentives relatively low, acts much like a flat voucher, and obtains a level of welfare close to the optimal voucher. Across a range of counterfactuals, we find that more efficient subsidy mechanisms share three features: they retain the marginal elasticity of demand, limit the exercise of market power, and preserve the link between prices and marginal costs.

Upcoding: Evidence from Medicare on Squishy Risk Adjustment

In most US health insurance markets, plans face strong incentives to "upcode" the patient diagnoses they report to the regulator, as these affect the risk-adjusted payments plans receive. We show that enrollees in private Medicare plans generate 6% to 16% higher diagnosis-based risk scores than they would under fee-for-service Medicare, where diagnoses do not affect most provider payments. Our estimates imply that upcoding generates billions in excess public spending and significant distortions to firm and consumer behavior. We show that coding intensity increases with vertical integration, suggesting a principal-agent problem faced by insurers, who desire more intense coding from the providers with whom they contract.

Marketplace Coverage and Limited Access to Care Among Employed Beneficiaries? Evidence From Ohio

This article examines the initial effect of Affordable Care Act (ACA) Health Insurance Marketplace (Exchange) insurance on access to care among employed beneficiaries in a highly populated US state. Does Exchange insurance lead to better/worse health care access for employed beneficiaries, compared with similar individuals covered through standard employer-sponsored insurance (ESI) coverage? This retrospective study uses data from the 2015 Ohio Medicaid Assessment Survey, a dual-frame and computer-assisted telephone survey administered by the Ohio Colleges of Medicine Graduate Resource Center, the Ohio Department of Medicaid, the Ohio Department of Health, and Ohio State University, in conjunction with RTI International. This study examines a sub-sample of employed adults (age 18-64) covered by either an Exchange plan or ESI, extracted from the full sample of n = 42 876. We use linear propensity score matching using Euclidean distance to balance treatment groups and logistic regression models to estimate the treatment effect of Exchange coverage on all outcome variables. McNemar tests, Rosenbaum sensitivity analysis, and Benjamini-Hochberg procedure adjustments are also conducted. Compared with ESI insurance, Exchange insurance has no significant effect on outcomes measuring either perceived access to care or, more specifically, perceived financial barriers to accessing care. Exchange plan viability remains a hot topic of debate across the United States, given the potential repeal of the individual mandate. We use risk-adjustment methods to demonstrate that Exchange plan beneficiaries do not experience worse access to care than ESI beneficiaries. That said, several key limitations are discussed.