In the health insurance marketplaces established by the Affordable Care Act (ACA), each state is divided into a set number of geographic “rating areas.” The ACA mandates that an insurer price its health insurance plan uniformly in all counties within the same rating area, conditional on insurees’ age and smoking status. However, the ACA does not require that an insurer sell its plan in all counties in a rating area. Using the federal marketplace data, we quantify the prevalence of a phenomenon, which we refer to as partial rating area offering, where insurers enter some but not all of the counties in a rating area. To understand why insurers selectively enter a subset of the counties in a rating area, we develop a simple model of insurer competition. The model implies that if common county characteristics, such as the county’s risk distribution, market size and provider availability, are the primary drivers for the partial rating area offering phenomenon, then there would be a positive correlation among insurers’ entry decisions. In contrast, if the partial rating area offering phenomenon is driven by market segmentation, then there would be a negative correlation. We develop a novel nonparametric correlation test and apply it to the federal marketplace data. We find strong evidence for a positive correlation of insurers’ entry decisions, suggesting that common cost factors are the main driver for the partial rating area offering phenomenon. To the extent that it is a concern that many counties now have few insurers, our result suggests that it is important to offer insurers subsidies that are tied to county characteristics.
Partial Rating Area Offering in the ACA Marketplaces: Facts, Theory and Evidence by Hanming Fang, Ami Ko :: SSRNOctober 19, 2018
Medicaid Expansion and Intensity of Treatment: Increased Cost in the Emergency Department by Shooshan Danagoulian, Allen C. Goodman, Alexander Janke, Phillip Levy :: SSRNOctober 18, 2018
We estimate the impact of the ACA Medicaid expansion on the intensity of treatment in the emergency department. We conduct a visit level analysis with a difference-in-differences specification for the number of procedures, number of diagnoses, and visit characterization according to the NYU Algorithm using the State Emergency Department Databases (SEDD) for six states in 2013-2014. Our results show that in expanding states the number of procedures increased by up to 0.27 per visits (3.9%), and the number of diagnoses declined by up to 0.10 diagnoses per visit. While we remain agnostic about the mechanism for the increase in procedures, we believe increasing reimbursements motivates providers to perform more procedures, or bill more carefully, or both. We also find evidence of changing composition of visit type, with an increase in non-preventable emergency visits and primary care treatable visits. This increase is particularly strong among patients who were uninsured in 2013. We estimate that the additional procedures cost $248 million, constituting at least 3.1% of the total medical expenditure associated with the expansion in the four expanding states in our study. We conclude that the provider side response in treatment presents a substantial additional cost to expanding insurance coverage with fee-for-service payment structure, and should be accordingly included in projected costs of future insurance expansions.
Enactment of the Patient Protection and Affordable Care Act (ACA) in 2010 marked the most important accomplishment in U.S. health care reform in decades. Not since Medicare and Medicaid were passed in 1965 have so many Americans been given access to insurance coverage for their health care. Though the goal of universal health care was not achieved, ACA brought coverage to millions of uninsured Americans and provided assurance to the already-insured that if they lost their insurance through job loss or job change, they could turn to an expanded Medicaid program or a government-subsidized insurance policy for affordable coverage.
But while ACA has had a major impact on the U.S. health care system, its promise has been limited by its design. Rather than replacing the U.S. system with a more effective, less costly, and politically sustainable model, lawmakers decided to build on top of an inefficient, expensive, and politically insecure, existing model. A health care system that rested on a shaky foundation now has to carry more weight and that makes for an unstable future. Indeed, we are already starting to see some unraveling of ACA. For ACA to achieve its goals in a durable fashion, it should be replaced by a health care program that provides the same kind of health care coverage for all Americans rather than relying on a system that mixes employer-based insurance with individually-purchased private insurance and government-provided coverage.
Has the Affordable Care Act Affected Health Care Efficiency? by Russell Kashian, Nicholas Lovett, Yuhan Xue :: SSRNSeptember 15, 2018
We utilize health care input and output data to evaluate how state-level efficiency in health care has changed in the wake of the Affordable Care Act (ACA). We use a Stochastic Frontier model to estimate annual measures of technical and cost efficiency before, and after, the implementation of the ACA. Results show that following the ACA, states’ technical efficiency improved and converged across states. However, cost efficiency declines suggest health outputs rose by a proportionally smaller margin than health care costs. Plausible explanations are a lack of substitutability between emergency care and preventive care, the presence of moral hazard in health care markets, and declining marginal returns to increased health care expenditures. The above pattern of results is repeated with greater magnitude for states that expanded Medicaid coverage. The results suggest the ACA represents a package of reforms that present a trade-off between technical and cost efficiency.
Prior to full implementation of the Affordable Care Act (ACA) in 2014, states had taken the leading role in regulating individual health insurance markets. The ACA’s regime of subsidies, penalties, and federal regulations made individual coverage more accessible to those with moderate incomes and those with preexisting medical conditions. Premiums for such coverage, however, doubled between 2013 and 2017, leading to turmoil in individual markets. Both Congress and the Centers for Medicare and Medicaid Services (CMS) sought to grant states more authority to stabilize their markets through a waiver process established by section 1332 of the ACA. These efforts fell short. Congress did not enact significant changes to the ACA, and few states obtained CMS approval for section 1332 waivers to stabilize their markets. This paper offers several recommendations for streamlining and improving that waiver process that would provide states with more tools to stabilize individual markets.
Expanding insurance coverage could, by insulating patients from having to pay full cost, encourage the utilization of arguably unnecessary medical services. It could also eliminate (or at least diminish) the need for emergency services through increasing access to preventive care. Using publicly available data from New York City for the period 2013-2016, we explore the effect of the Affordable Care Act (ACA) on the volume and composition of ambulance dispatches. Consistent with the argument that expanding insurance coverage encourages the utilization of unnecessary medical services, we find that, as compared to dispatches for more severe injuries, dispatches for minor injuries rose sharply after the implementation of the ACA. By contrast, dispatches for pre-labor pregnancy complications decreased as compared to dispatches for women in labor.
Resetting the Scoreboard: Why CBO Should Abandon Its Flawed Analysis of the Center for Medicare and Medicaid InnovationFebruary 15, 2018
Congress created the Center for Medicare and Medicaid Innovation (CMMI) in the Affordable Care Act and vested it with extraordinary powers. CMMI can conduct demonstration projects in the Medicare, Medicaid and Children’s Health Insurance Program and expand those projects nationwide without congressional approval.
The Congressional Budget Office (CBO) believes that CMMI will achieve substantial federal savings. It bases this conclusion not on analyses of projects that CMMI has undertaken, but on faith in the CMMI process. CBO assumes that process will produce money-saving ideas and that the center will scrap failed projects and expand
“The savings that CBO expects to result from the center’s activities,” a senior CBO official said in congressional testimony, “stem largely from the judgment that successful demonstrations will be expanded and achieve savings.”
The statement’s circularity – CBO “expects” CMMI to achieve savings because CMMI will “achieve savings” – is but one way which the agency’s analysis of CMMI departs from its long-established methods of preparing estimates. In addition to assuming that CMMI will sometime in the future conceive, launch and nationalize successful projects, CBO conjured a numerical factor to convert its assumptions into dollar estimates. It then embedded these numbers in its Medicare baseline, the yardstick against which it measures legislation.
CBO’s unique approach to CMMI thus colors its analysis of legislation designed to achieve Medicare savings. CBO believes that any bill that would overlap with any ongoing or possible future CMMI demonstration would increase Medicare spending above baseline levels. Even if Congress offers up a proposal that would reduce spending relative to the statute, CBO will score it as a spending hike if it believes that CMMI might someday test a similar policy.
CBO thus ascribes unobserved and unobservable savings to projects that CMMI has not yet undertaken (and may never undertake), quantifies these savings through the application of an arbitrary numerical factor, incorporates the savings into its Medicare baseline, and measures the budgetary effects of legislation against this revised baseline.
This paper traces the history of Medicare demonstration projects and shows how CMMI’s authorities differ from its predecessors. It then examines CBO’s assumptions about CMMI, carefully tracing the reasoning that has led to its conclusions. It then shows how recent events, including the Trump Administration’s cancellation of CMMI projects that CBO believed would save money, expose flaws in CBO’s assumptions and reasoning. It concludes with recommendations for CBO, Congress and the executive branch with respect to CMMI.