The proposal also establishes a global health budget, moves away from fee-for-service and toward lump-sum payments for many providers, includes a number of measures to hold down drug prices, and makes a variety of other changes to the health care system.
The proposal is broadly similar to Senator Sanders's proposed single-payer plan introduced during the Presidential campaign. All other estimates come to similar conclusions. Importantly, these totals represent the increased cost to the federal government , not the change of total national health expenditures. National health expenditures would likely change by no more than a few trillion dollars over the decade.
Biden argued that the plan was fiscally irresponsible and would require raising middle-class taxes. But we had never heard this figure before. It caught our attention, so we decided to dig in. The math, they said, shows Medicare for All would cost more than the national budget.
Research by the nonpartisan Urban Institute, a Washington, D. The campaign suggested that if you take 10 times the current federal budget, you get a figure smaller than the estimated cost of Medicare for All over that year window.
That raises one point on which Biden may have some ground. Goldwein argued that you would indeed need significant tax increases to finance the Sanders proposal. This relies on faulty math. Single-payer often referred to as Medicare for All , a proposed policy solution since , is receiving renewed press attention and popular support.
Our review seeks to assess the projected cost impact of a single-payer approach. We conducted our literature search between June 1 and December 31, , without start date restriction for included studies. We surveyed an expert panel and searched PubMed, Google, Google Scholar, and preexisting lists for formal economic studies of the projected costs of single-payer plans for the US or for individual states.
Reviewer pairs extracted data on methods and findings using a template. We quantified changes in total costs standardized to percentage of contemporaneous healthcare spending.
Additionally, we quantified cost changes by subtype, such as costs due to increased healthcare utilization and savings due to simplified payment administration, lower drug costs, and other factors. We further examined how modeling assumptions affected results. Our search yielded economic analyses of the cost of 22 single-payer plans over the past 30 years. Exclusions were due to inadequate technical data or assuming a substantial ongoing role for private insurers.
The largest source of savings was simplified payment administration median 8. Only drug cost savings remained significant in multivariate analysis. Included studies were heterogeneous in methods, which precluded us from conducting a formal meta-analysis.
In this systematic review, we found a high degree of analytic consensus for the fiscal feasibility of a single-payer approach in the US. Actual costs will depend on plan features and implementation. Future research should refine estimates of the effects of coverage expansion on utilization, evaluate provider administrative costs in varied existing single-payer systems, analyze implementation options, and evaluate US-based single-payer programs, as available.
Economic models help assess the financial viability of single-payer. Yet, models vary widely in their assumptions and methods, and can be hard to compare. We found and compared cost analyses of 22 single-payer plans for the US or individual states. The largest savings were predicted to come from simplified billing and lower drug costs. Studies funded by organizations across the political spectrum estimated savings for single-payer.
There is near-consensus in these analyses that single-payer would reduce health expenditures while providing high-quality insurance to all US residents.
To achieve net savings, single-payer plans rely on simplified billing and negotiated drug price reductions, as well as global budgets to control spending growth over time. Replacing private insurers with a public system is expected to achieve lower net healthcare costs. Nine years after passage of the Affordable Care Act, Lack of insurance is associated with worse health outcomes, including death [ 2 ], due to decreased access to healthcare and preventive services [ 3 — 5 ].
Low-income adults with public insurance have improved access and quality of care compared to uninsured adults [ 8 ]. Meanwhile, healthcare costs continue to rise, approaching one-fifth of the economy.
Higher costs in the US are due primarily to higher prices and administrative inefficiency, not higher utilization [ 11 — 13 ]. An oft-proposed alternative to the contemporary multi-payer system is single-payer, also referred to as Medicare for All. Key elements of single-payer include unified government or quasi-government financing, universal coverage with a single comprehensive benefit package, elimination of private insurers, and universal negotiation of provider reimbursement and drug prices.
Single-payer as it has been proposed in the US has no or minimal cost sharing. Two-thirds of Americans support providing universal health coverage through a national plan like Medicare for All as an extremely high priority for the incoming Congress [ 16 ]. However, support varies substantially according to how single-payer is described [ 17 ].
Economic analyses are crucial for formally estimating the net cost of single-payer proposals. These models estimate how potential added costs of single-payer, due to increased utilization of services, compare with the savings induced by simplified payment administration, lower drug prices, and other factors.
Such economic projections can shape plan design, contribute to policy discourse, and affect the viability of legislation. As single-payer proposals gain legislative traction, the importance of economic models rises. However, these analyses are complex and heterogeneous, making generalizations difficult. The diversity of findings contributes to political spin and fuels popular uncertainty over the anticipated costs of a single-payer healthcare system. For example, a study by Pollin et al.
Urban Institute suggested that a modified form of this proposal, e. Variation in single-payer proposals and analytic approaches likely explains many of the differences in outcomes across studies, but no comparative review has been undertaken, to our knowledge. The goal of this study is to systematically review economic analyses of the cost of single-payer proposals in the US both national and state level , summarize results in a logical but accessible manner, examine the association of findings with plan features and with analytic methods, and, finally, examine the empirical evidence regarding key study assumptions.
We specified in advance that we would extract and quantitatively compare increased costs due to utilization rises and savings due to administrative simplification, drug savings, and other factors.
We searched for studies by examining existing lists, querying experts, and searching online. Ethics approval was not deemed to be necessary since all data were publicly available. All data are available in the original studies, which are listed in S1 Appendix. We included studies that examined insurance plans with essential single-payer features and that provided adequate technical detail on inputs and results. For these studies, we extracted information about plan features, analytic assumptions, and findings costs due to higher utilization, savings of all types, and net costs; see Table A in S1 Appendix for definitions of terms.
We expressed all estimates as a percentage of contemporaneous healthcare spending, to facilitate comparison across settings and time periods. We summarized study methods and findings graphically and analyzed associations between studies and spending estimates.
We adopted a broad search strategy, reflecting our initial assessment subsequently confirmed that economic models of the cost of single-payer plans are not published in academic journals.
We conducted all components of our search from June 1 to December 31 of We limited our Google search to 10 pages of results. We asked a convenience sample of 10 single-payer experts. Additional search details are provided in Table B in S1 Appendix.
We chose inclusion and exclusion criteria that were most consistent with single-payer plans that have been proposed in the US. For example, while some single-payer plans internationally have included private intermediaries within a unified payment system, US proposals have omitted a role for private insurers. Thus, we use private intermediaries as an exclusion criterion. Study inclusion required appropriateness of both the plan and the analysis. Specific inclusion criteria for the plan were that 1 all legal residents are permanently covered for a standard comprehensive set of medically appropriate outpatient and inpatient medical services under one payer and 2 the payer is a not-for-profit government or quasi-government agency.
Other central single-payer features, such as providers being entirely in or out, uniform payments with no balance billing, and use of a drug formulary, are often unspecified and thus were assumed present and thus not a basis for exclusion unless explicitly omitted. Some plans include undocumented immigrants, and some exclude them. Exclusion criteria were 1 use of large cost-sharing measures such as deductibles some US single-payer plans include small copays, e.
Importantly, we applied these criteria to the modeled plan, so models incorporating any of these features when analyzing an otherwise qualifying single-payer plan would be excluded.
These excluded studies are listed in Table C in S1 Appendix. Finally, we excluded 12 plans from 11 studies that met inclusion criteria but were redundant to newer studies of similar single-payer plans by the same analysis teams already included Table D in S1 Appendix. Net savings from these excluded studies were similar to those from the included studies Table E in S1 Appendix. For this report, we did not require or consider financing revenue plans, which turn on an entirely different set of technical issues.
We also did not seek analyses of broader economic effects, such as de-investing in the private insurance market or facilitation of labor mobility and start-ups through delinking of insurance and employment.
Our analysis also omits long-term effects on medical innovation. Studies were reviewed by at least 2 team members before finalizing inclusion or exclusion. Uncertain decisions e. We extracted the following information from each study: annual healthcare costs without single-payer specified for the year and setting, at the national or state level , initial-year annual cost under single-payer, cost increase due to utilization growth, and savings from all sources and 4 specific categories: simplified payment administration, lowered costs for medications [and for durable medical equipment, if bundled together], reduced clinical inefficiency [i.
We did not report transition costs such as purchases of for-profit businesses and training which were, in any case, rarely assessed , and no study quantified the costs of potential first-year implementation challenges.
If available, we extracted longer term costs and savings, defined as costs or savings accumulated subsequent to the first year of implementation. We also extracted or calculated the utilization increase assumed for newly insured individuals.
Each study was reviewed by 2 team members, and all study extractions were reviewed by the senior investigator JGK , who requested refinements and further documentation for unclear or unexpected values. When we had questions due to omissions or ambiguity in the report, we attempted to contact study authors. We also sent them, when successfully located, a report draft for review. We standardized all cost numbers to percentage of contemporaneous total health system costs, to allow for direct comparison across times and locations.
This approach obviated the need for inflation adjustments. We standardized costs due to increased utilization as the increase in annual cost for the newly insured divided by the mean cost for the already insured.
We examined results visually, ordered by year and by net cost highest net cost to highest net savings. To assess the association of net cost with plan and analysis features e. We also conducted univariate and multivariate linear regressions with net savings or cost as the outcome and with the following predictors: utilization increase, specific savings categories, type of funder organization, and type of analyst organization.
In the multivariate analysis, we assigned dummy variables for missingness of the utilization predictor. We reviewed 90 studies and included primary analyses of 22 single-payer plans from 18 studies, published between and , including 8 national and 14 state-level plans Massachusetts, California, Maryland, Vermont, Minnesota, Pennsylvania, New York, and Oregon.
Included studies are listed in Table F in S1 Appendix. Analysis teams included US government agencies, business consultants and research organizations, and academics. Nine single-payer plans from 6 studies were excluded for the following reasons: age limits on single-payer, varied benefits across individuals, balance billing, inclusion of private insurers or intermediaries in the plan or analysis, and lack of specification of assumptions regarding utilization and savings.
Net cost or savings in the first year of single-payer operation varies from an increase of 7. The median finding was a net savings of 3. Net costs reflect the balance of added costs due to higher utilization by eliminating uninsurance and in some studies also capturing the increase due to ending underinsurance and savings via payment simplification, lower drug prices, and other factors. Higher utilization increases costs by 2. Total savings range from 3.
The cost increase due to expansion of insurance coverage varies due to the number of newly covered individuals and generosity of coverage benefits, but also reflects policy components and expert assessment. Additionally, cost-control choices such as copays vary across plans. The mix of projected savings from single-payer shows both consistent and variable elements across studies Fig 3. All studies estimate lower costs due to simplified payment administration, but vary in the size of these savings and in the inclusion and magnitude of other savings.
Administrative savings vary from 1. Savings from lowered prices for medications and durable medical equipment are included in 12 models and range from 0. Savings from reduced fraud and waste are included in 10 models and range from 0. Savings due to a shift to Medicare payment rates are included in 8 models and range from 1. Over time, utilization increases are stable and projected savings grow, leading to larger estimates for potential savings.
Plans listed in order by year. Simplified payment administration was the greatest source of savings, for a median of 8. In the long term, projected net savings increase, due to a more tightly controlled rate of growth.
For the 10 studies with projections for up to 11 years, each year resulted in a mean 1. At this rate, the 3 studies that find net costs in the first year would achieve net savings by 10 years. Fig 4 presents net costs or savings alongside a color-coded summary of key plan features and model assumptions. We next assessed whether the inclusion of different analysis features yes or no was associated with net costs, based on univariate regressions Fig 5.
Cost sharing did not have a significant association with net costs across all studies 2. Inclusion of medication and equipment savings in the model was associated with lower net costs by 7. Inclusion of a shift to Medicare payment rates was not a strong predictor of net costs. We cannot assess the association between net costs and presence or absence of administrative savings in these dichotomous analyses because all studies include these savings.
The number of different analysis features included in the model was also associated with lower net costs. For each additional analysis feature included, net costs were reduced by 2. Each estimate comes from a separate linear regression of net costs and a binary predictor. In univariate regressions of net savings against the magnitude of inputs, several relationships emerge Fig 6.
A 1-point increase in utilization rate was associated with higher net costs of 9.
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