Importance:Since 2013, 9 states have implemented health care spending growth benchmarks. States track performance against these benchmarks, and some states can penalize noncompliance. While subsequent growth has frequently exceeded the benchmark, the approach could slow growth relative to what would have happened without benchmark implementation. Objective:To assess the association between spending growth benchmarks and spending outcomes. Design, Setting, and Participants:This population-based case-control study used event study models that compare hospitals and counties in states with benchmarks with entropy-balanced comparators in nonimplementing states from January 1, 2015, to December 31, 2025. Exposures:Implementation of state spending growth benchmarks in Vermont (2018), Delaware (2019), Rhode Island (2019), Connecticut (2021), Oregon (2021), Washington (2022), New Jersey (2023), and California (2025). Massachusetts (2013) was excluded. Main Outcomes and Measures:Outcomes of interest included hospital inpatient net revenue per discharge and outpatient net revenue per discharge equivalent from the Centers for Medicare & Medicaid Services Health Care Cost Report Information System, mean county-level inpatient and outpatient standardized prices from the RAND Hospital Price Transparency data, and county-level individual and small group market single bronze premiums from the Center for Consumer Information and Insurance Oversight. Results:A total of 298 hospitals and 184 counties in 8 states that implemented benchmarks and 4515 hospitals and 2924 counties in nonimplementing states were included, yielding a final sample of 4813 hospitals and 3108 counties. On average, no statistically significant changes from preimplementation to postimplementation relative to comparators were found for hospital inpatient revenue (-$839 [95% CI, -$4276 to $1874]), hospital outpatient revenue ($439 [95% CI, -$1207 to $2126]), inpatient prices (-$3 [95% CI, -$2290 to $2417]), outpatient prices ($11 [95% CI, -$12 to $34]), individual market premiums ($8 [95% CI, -$8 to $26]), or small group premiums ($11 [95% CI, -$3 to $25]). State-specific findings were similar, except for Rhode Island, for which benchmarks were associated with a statistically significant $55 (95% CI, -$88 to -$20) reduction in outpatient prices. Conclusions and Relevance:In this case-control study of hospital revenue, hospital prices, and premiums, scant evidence suggested that spending growth benchmarks were associated with reductions in the outcomes of interest. States may need to pair benchmarks with more rigorous enforcement or additional policies to meaningfully influence health care spending.

ImportanceHouseholds have high burden of health care payments. Alternative financing approaches could reduce this burden for some households.ObjectiveTo estimate the distribution of household health care payments across income under health care reform policies.Design, Setting, and ParticipantsCross-sectional study with microsimulation used nationally representative data of the US population in 2030. Civilian, noninstitutionalized population from the 2022 Current Population Survey linked to expenditures from the 2018 and 2019 Medical Expenditure Panel Survey and 2022 National Health Expenditure Accounts were included.ExposureRate regulation of hospital, physician, and other health care professional payments equal to the all-payer mean in the status quo, spending growth target at 4% annual per capita growth, and single-payer health care financed through taxes.Main Outcomes and MeasuresHousehold health care payments (out-of-pocket expenses, premiums, and taxes) as a share of compensation.ResultsThe synthetic population contained 154 456 records representing 339.5 million individuals, with 51% female, 7% Asian, 14% Black, 18% Hispanic White, 56% non-Hispanic White, and 5% other races and ethnicities (American Indian or Alaskan Native only; Native Hawaiian or other Pacific Islander only; and 2 or more races). In the status quo, mean household health care payments as a share of compensation was 24% to 27% (standard error [SE], 0.2%-1.2%) across income groups (median [IQR] 22% [4%-52%] below 139% of the federal poverty level [FPL]; 21% [4%-34%] for households above 1000% FPL [11% of the population]). Under rate setting, mean (SE) payments by households above 1000% FPL increased to 29% (0.6%) (median [IQR], 22% [6%-35%]) and decreased to 23% to 25% for other income groups. Under the spending growth target, mean (SE) payments decreased from 23% to 26% (SE, 0.2%-1.2%) across income groups. Under the single-payer system, mean (SE) payments declined to 15% (0.7%) (median [IQR], 4% [0%-30%]) for those below 139% FPL and increased to 31% (0.6%) (median [IQR], 23% [3%-39%]) for those above 1000% FPL. Uninsurance fell from 9% to 6% under rate setting due to improved Medicaid access, and to zero under the single-payer system.Conclusions and RelevanceSingle-payer financing based on the current federal income tax schedule and a payroll tax could substantially increase progressivity of household payments by income. Rate setting led to slight increases in payments by higher-income households, who financed higher payment rates in Medicare and Medicaid. Spending growth targets reduced payments slightly for all households.

Starting in 2026, Minnesota could experience disruptions to its health insurance marketplace caused by the anticipated sunset of federal premium subsidy enhancements, made available through the Inflation Reduction Act of 2022, as well as the expiration of state funding for its reinsurance program. With reduced premium subsidies, fewer people might enroll in marketplace plans, which could lead to higher premiums and market instability. The expiration of reinsurance, which partially offsets insurers' claims costs for people with high expenditures, could exacerbate these issues. In this study, researchers estimate the effects of implementing state-funded subsidies to bolster Minnesota's marketplace given these anticipated changes. They also study the impact of replacing the state's Basic Health Program with a similarly structured marketplace plan. The policy reforms that researchers consider were developed by the Minnesota Council of Health Plans and share similar goals with legislation recently proposed by Minnesota policymakers, such as HF 96, a bill authorizing study of a public option that also proposed to temporarily enhance marketplace subsidies.

Policymakers in Connecticut are considering various options to increase the affordability of insurance in the state, such as expansions to premium and cost-sharing reduction subsidies on the state's health insurance marketplace, as well as expanded plan offerings, including extending eligibility for the state employee health plan (SEHP) to other groups and a publicly contracted, privately operated plan (the public option plan) offered to individuals on the marketplace. The authors used the RAND Corporation's COMPARE microsimulation model to estimate the impacts of such policy options. For each policy scenario, they calculated enrollment, premiums, consumer spending, and state spending and considered whether the results differed by race, ethnicity, or income group. The individual market reforms substantially increased affordability for people with incomes between 175 and 200 percent of the federal poverty level (FPL), reducing out-of-pocket spending as a share of income by 50 percent in some scenarios. Changes to affordability for higher-income groups were smaller, in part because the proposed policy changes for people with incomes between 200 and 400 percent of FPL were relatively modest and focused only on reducing cost-sharing (not premiums). New costs to the state for 2023 ranged from $19 million to $94 million, depending on the scenario. All four SEHP specifications led to the same bottom-line conclusion that offering a SEHP plan would improve insurance coverage and affordability for those eligible for the plan. Expanding eligibility for the SEHP holds promise for stabilizing or reducing consumer costs, improving plan generosity, and bringing more people into the market.

The state of Connecticut is considering a number of policy options to improve health insurance affordability, access, and equity. To create policies designed to increase insurance coverage and access to care in underserved communities and reduce racial and ethnic disparities, state policymakers need an accurate picture of the current distributions of insurance enrollment across these dimensions. The authors combine data from the American Community Survey Public Use Microdata Sample, which includes demographic characteristics, as well as insurance status, with various data sources from the state to provide a fuller picture of insurance enrollment among those under the age of 65 in Connecticut. They also use existing high-level estimates of 2020 insurance enrollment to provide estimates of how enrollment in the state was affected during the early months of the pandemic. The authors find that insurance enrollment in Connecticut in 2019 was generally high but that there were substantial differences in insurance coverage by race and ethnicity. Asian individuals had the highest rates of employer-sponsored insurance coverage, and Black individuals had the highest rates of Medicaid coverage. Hispanic individuals had a higher rate of Medicaid coverage than non-Hispanic individuals. High-level estimates of changes in insurance coverage during the early months of the COVID-19 pandemic suggest that uninsurance decreased slightly, Medicaid coverage increased, and private insurance coverage fell. This study provides the state of Connecticut with estimates of enrollment in detailed health insurance categories by age, gender, race, and ethnicity and highlights the need for better, more-detailed health insurance enrollment data.

Policymakers in Connecticut are considering various state-funded policy options to improve insurance coverage among undocumented and legally present recent immigrants in the state - almost 60 percent of whom lack health insurance. In particular, they are removing immigration status requirements from Medicaid eligibility. They are also considering whether to provide state-funded subsidies to undocumented immigrants enrolled in individual market plans. A key challenge for this analysis was determining what share of undocumented immigrants would be likely to take up insurance coverage if it were available to them. Because few states have expanded coverage to their undocumented populations and because the denominator is uncertain, estimates of take-up rates are highly uncertain. There is similar uncertainty in estimating how much health care undocumented populations will use once they become insured. To address these uncertainties, the authors conducted sensitivity analyses that varied both the take-up and utilization rates. Using the RAND Corporation's COMPARE microsimulation model, the authors estimate the impacts of each policy scenario on enrollment, premiums, state spending, and hospital spending on uncompensated care. Their analysis suggests that removing immigration status requirements for Medicaid and individual market subsidy eligibility would decrease uninsurance among the undocumented and legally present recent immigrant populations by 32 to 37 percent and could improve insurance coverage and affordability in Connecticut for these populations while not substantially impacting other Connecticut residents.

Objective: The objective of this study was to examine the price sensitivity for provider visits among Medicare Advantage beneficiaries. Data Sources: We used Medicare Advantage encounter data from 2014 to 2017 accessed as part of an evaluation for the Center for Medicare & Medicaid Innovation. Study Design: We analyzed the effect of cost-sharing on the utilization of 2 outcome categories: number of visits (specialist and primary care) and the probability of any visit (specialist and primary care). Our main independent variable was the size of the copayment for the visit, which we regressed on the outcomes with several beneficiary-level and plan-level control variables. Data Collection/Extraction Methods: We included beneficiaries with at least 1 of 4 specific chronic conditions and matched comparison beneficiaries. We did not require beneficiaries to be continuously enrolled from 2014 to 2017, but we required a full year of data for each year they were observed. This resulted in 371,140 beneficiary-year observations. Principal Findings: Copay reductions were associated with increases in utilization, although the changes were small, with elasticities <-0.2. We also found evidence of substitution effects between primary care provider (PCP) and specialist visits, particularly cardiology and endocrinology. When PCP copays declined, visits to these specialists also declined. Conclusions: We find that individuals with chronic conditions respond to changes in copays, although these responses are small. Reductions in PCP copays lead to reduced use of some specialists, suggesting that lowering PCP copays could be an effective way to reduce the use of specialist care, a desirable outcome if specialists are overused.

In 2015, the Centers for Medicare and Medicaid Services announced the Medicare Advantage (MA) Value-Based Insurance Design (VBID) model test, which allows MA insurers to use flexible benefit design strategies, such as reduced cost-sharing, to encourage beneficiaries with chronic disease to use high-value care. During the first year of implementation (2017), nine MA insurers offered VBID in 45 health plans to a total of 96 053 eligible beneficiaries. We used MA encounter data to estimate the impact of VBID on health services utilization in 2017 using a difference-in-differences research design. We found that VBID increased use of 10 out of 18 targeted services, and led to general increases in primary care visits, specialty care visits, and drug fills across eligible beneficiaries. The model was also associated with increases in ambulatory care sensitive inpatient and emergency department visits, an unanticipated effect that may be temporary. Overall, our findings suggest that VBID successfully increased the use of high-value services among eligible MA beneficiaries, an important first step along the pathway to better chronic disease management, lower spending, and improved beneficiary health.

Economic theory suggests that a binding minimum wage increase may reduce the generosity of employer-sponsored insurance (ESI) or other fringe benefits, yet previous empirical studies reach conflicting conclusions about the existence of a trade-off between minimum wages and ESI. We study whether recent state and federal minimum wage increases affect the level or the source of health insurance coverage for low-income families using the 2005–16 Current Population Survey. Our research design uses state and year fixed effects to isolate within-state minimum wage changes while controlling for Medicaid eligibility and other changes in health policy related to implementation of the Affordable Care Act. Because dependent coverage might also be affected by minimum wage hikes, we examine ESI coverage for both low-wage workers and their dependents. We find robust evidence that minimum wage increases lead to reductions in ESI coverage in families below 300 percent of the federal poverty level, with a nominal $1 increase in the minimum wage reducing the probability of ESI coverage by 0.99 percentage points. Reductions in coverage were observed both for workers and for their dependents.

The coronavirus disease 2019 pandemic–related recession and resulting job loss raised significant concerns that the U.S. uninsured population could increase, perhaps by millions. However, worrisome predictions about coverage loss have not materialized. RAND researchers (1) assess the importance of temporary provisions in stabilizing health insurance enrollment despite heavy job loss and (2) run simulations using New York state as a case study.

This report analyzes policy options that allow people to enroll in public health insurance plans.We consider public option scenarios with the public plan offered on or off the individual Health Insurance Marketplaces, varying provider payment rates, and the marginal effect of extending premium tax credits.For each scenario, we estimate enrollment, premiums, and federal subsidy spending.This research was

This brief describes how a public option for health care—that is, a government-sponsored health insurance plan with publicly determined provider payment rates—would affect insurance costs and coverage.

The following is a review of “Medical Costs of Keeping the US Economy Open During COVID-19”. The authors use an individual level synthetic social contact network based on publicly available data and national level epidemic simulations to estimate the medical costs of keeping the US economy open under COVID-19 pandemic. Amongst a range of findings, the simulations suggest that the US economy could be brought down by 5% if no mitigation strategies were taken.

This paper illustrates the use of entropy balancing in difference-in-differences analyses when pre-intervention outcome trends suggest a possible violation of the parallel trends assumption. We describe a set of assumptions under which weighting to balance intervention and comparison groups on pre-intervention outcome trends leads to consistent difference-in-differences estimates even when pre-intervention outcome trends are not parallel. Simulated results verify that entropy balancing of pre-intervention outcomes trends can remove bias when the parallel trends assumption is not directly satisfied, and thus may enable researchers to use difference-in-differences designs in a wider range of observational settings than previously acknowledged.

In this report, the authors analyze how allowing adults ages 50 and older to buy into the Medicare program could affect health insurance coverage, individual market premiums, and federal health care spending. Their findings suggest that a Medicare buy-in could offer significantly more-affordable coverage to older adults while potentially leading to higher premiums for the pool of people remaining on the individual market.

OBJECTIVES: Value-based insurance design (VBID) lowers cost sharing for high-value healthcare services that are clinically beneficial to patients with certain conditions. In 2017, the Center for Medicare and Medicaid Innovation began a voluntary VBID model test in Medicare Advantage (MA). This article describes insurers' perspectives on the MA VBID model, explores perceived barriers to joining this model, and describes ways to address participation barriers. STUDY DESIGN: A descriptive, qualitative study. METHODS: In spring/summer 2017, we conducted semistructured interviews with 24 representatives of 10 nonparticipating MA insurers to learn why they did n join the model test. We interviewed 73 representatives of 8 VBID-participating insurers about their participation decisions and implementation experiences. All interview data were analyzed thematically. RESULTS: Fewer than 30% of eligible insurers participated in the first 2 years of the model test. The main barriers to entry were a perceived lack of information on VBID in MA, an expectation of low return on investment, concerns over administrative and information technology (IT) hurdles, and model design parameters. Most VBID participants encountered administrative and IT hurdles but overcame them. CMS made changes to the model parameters to increase the uptake. CONCLUSIONS: The model uptake was low, and implementation challenges and concerns over VBID effectiveness in the Medicare population were important factors in participation decisions. To increase uptake, CMS could consider providing in-kind implementation assistance to model participants. Nonparticipants may want to incorporate lessons learned from current participants, and insurers should engage their IT departments/vendors early on.

OBJECTIVE:To estimate the effects of 2014 Medicaid expansions on inpatient outcomes.DATA SOURCES:Health Care Cost and Utilization Project State Inpatient Databases, 2011-2014; population and unemployment estimates.STUDY DESIGN:Retrospective study estimating effects of Medicaid expansions using difference-in-differences regression. Outcomes included total admissions, referral-sensitive surgical and preventable admissions, length of stay, cost, and patient illness severity.FINDINGS:In 2014 quarter four, compared with nonexpansion states, Medicaid admissions increased (28.5 percent, p = .006), and uninsured and private admissions decreased (-55.1 percent, p = .001, and -6.6 percent, p = .052), whereas all-payer admissions showed little change. Uninsured expansion effects were negative for preventable admissions (-24.4 percent, p = .068), length of stay (-9.3 percent, p = .039), total cost (-9.2 percent, p = .128), and illness severity (-4.5 percent, p = .397). Significant positive expansion effects were found for Medicaid referral-sensitive surgeries (11.8 percent, p = .021) and patient illness severity (2.3 percent, p = .015). Private and all-payer expansion effects for outcomes other than admission volume were small and mainly nonsignificant (p > .05).CONCLUSION:Medicaid expansions did not change all-payer admission volumes, but they were associated with increased Medicaid and decreased uninsured volumes. Results suggest those previously uninsured with greater needs for inpatient services were most likely to gain coverage. Compositional changes in uninsured and Medicaid admissions may be due to selection.

Issue:Recent changes to the Affordable Care Act, including elimination of the individual mandate penalty, the halting of federal payments for cost-sharing reductions, and expanded access to short-term plans, may reduce enrollment in the individual market.Goal:Analyze options to increase enrollment, accounting for recent policy changes.Methods:RAND’s COMPARE microsimulation model is used to analyze six policies that would expand access to tax credits, increase their generosity, and fund a reinsurance program.Key Findings and Conclusions:The options would increase individual market enrollment by 400,000 to 3.2 million in 2020. Net increases in total enrollment (300,000 to 2.4 million) are smaller because of offsetting decreases in employer-sponsored insurance. The largest gains are possible through two options: large-scale investment in reinsurance, and extension of tax credits to higher-income people combined with increases in the generosity of existing tax credits. If funded through a fee on health plans, reinsurance could be implemented without increasing the federal deficit. Additional taxpayer costs would increase by $1 billion to $23 billion, depending on the policy. While enhanced tax credits for young adults would lead to small coverage gains, they would entail the lowest costs to taxpayers among the six options.