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Scientific evidence regularly guides policy decisions1, with behavioural science increasingly part of this process2. In April 2020, an influential paper3 proposed 19 policy recommendations (claims) detailing how evidence from behavioural science could contribute to efforts to reduce impacts and end the COVID-19 pandemic. Here we assess 747 pandemic-related research articles that empirically investigated those claims. We report the scale of evidence and whether evidence supports them to indicate applicability for policymaking. Two independent teams, involving 72 reviewers, found evidence for 18 of 19 claims, with both teams finding evidence supporting 16 (89%) of those 18 claims. The strongest evidence supported claims that anticipated culture, polarization and misinformation would be associated with policy effectiveness. Claims suggesting trusted leaders and positive social norms increased adherence to behavioural interventions also had strong empirical support, as did appealing to social consensus or bipartisan agreement. Targeted language in messaging yielded mixed effects and there were no effects for highlighting individual benefits or protecting others. No available evidence existed to assess any distinct differences in effects between using the terms physical distancing and social distancing. Analysis of 463 papers containing data showed generally large samples; 418 involved human participants with a mean of 16,848 (median of 1,699). That statistical power underscored improved suitability of behavioural science research for informing policy decisions. Furthermore, by implementing a standardized approach to evidence selection and synthesis, we amplify broader implications for advancing scientific evidence in policy formulation and prioritization.

In 2008, Oregon expanded its Medicaid program using a lottery, creating a rare opportunity to study the effects of Medicaid coverage using a randomized controlled design (Oregon Health Insurance Experiment). Analysis showed that Medicaid coverage lowered the risk of depression. However, this effect may vary between individuals, and the identification of individuals likely to benefit the most has the potential to improve the effectiveness and efficiency of the Medicaid program. By applying the machine learning causal forest to data from this experiment, we found substantial heterogeneity in the effect of Medicaid coverage on depression; individuals with high predicted benefit were older and had more physical or mental health conditions at baseline. Expanding coverage to individuals with high predicted benefit generated greater reduction in depression prevalence than expanding to all eligible individuals (21.5 vs 8.8 percentage-point reduction; adjusted difference = +12.7 [95% CI, +4.6 to +20.8]; P  = 0.003), at substantially lower cost per case prevented ($16 627 vs $36 048; adjusted difference = −$18 598 [95% CI, −156 953 to −3120]; P  = 0.04). Medicaid coverage reduces depression substantially more in a subset of the population than others, in ways that are predictable in advance. Targeting coverage on those most likely to benefit could improve the effectiveness and efficiency of insurance expansion. This article is part of a Special Collection on Mental Health. [ABSTRACT FROM AUTHOR]

BackgroundThere is substantial interest in identifying low-acuity visits to emergency departments (EDs) that could be treated more appropriately in other settings. Systematic differences in illness severity between ED patients and comparable patients elsewhere could make such strategies unsafe, but little evidence exists to guide policy makers.ObjectiveTo compare illness severity between patients visiting EDs and outpatient clinics, by comparing short-term mortality and hospitalization, controlling for patient demographics, comorbidity, and visit acuity.Research designCross-sectional study of outcomes after medical encounters.SubjectsNationally representative 20% sample of Medicare fee-for-service beneficiaries discharged home from ED or clinic visit in 2011, and enrolled continuously for 1 year before the visit.MeasuresAll-cause mortality and hospitalization in the 8, 15, and 30 days after discharge home from ED or clinic visits.ResultsAfter risk-adjusting for patient demographic, comorbidity, disability, and dual-eligibility status, as well as visit acuity as measured by a commonly used algorithm, we found that ED patients were more likely to die (risk-adjusted odds ratio=2.75; 95% confidence interval, 2.56-2.96) or be hospitalized (odds ratio=1.97; 95% confidence interval, 1.95-2.00) after discharge than clinic patients. Differences in short-term outcomes were observed even when comparing patients with the same discharge diagnoses after risk adjustment.ConclusionsPatients presenting to EDs have worse risk-adjusted short-term outcomes than those presenting to outpatient clinics, even after controlling for acuity level of visit or discharge diagnosis. Existing measures of acuity using administrative data may not adequately capture severity of illness, making judgments of the appropriate setting for care difficult.

It is an enormous honor to deliver this lecture, particularly this year. You have just heard from a number of our profession's luminaries about the monumental effect that Marty Feldstein [...]

We use variation in medical malpractice payments driven by the recent “medical malpractice crisis” to identify the causal effect of rising health insurance premiums on wages, employment and the distribution of part-time and full-time work. We estimate that a 10 percent increase in health insurance premiums reduces the aggregate probability of being employed by 1.2 percentage points, reduces hours worked by 2.4 percent, and increases the likelihood that a worker is employed only part-time by 1.9 percentage points. For workers covered by employer provided health insurance, a 10 percent increase in premiums results in an offsetting decrease in wages of 2.3 percent. Thus, rising health insurance premiums may both increase the ranks of the unemployed and place an increasing burden on workers through decreased wages for those with employer health insurance and decreased hours for those who may be moved from full time jobs with benefits to part time jobs without.

Both the federal government and the states use intergovernmental grants to try to change the composition of local spending across different programs, as well as the distribution of resources across localities. Many states are now under court-order to use state education grants to reduce local disparities in education spending. While a substantial body of literature suggests that these court orders increase the level and progressivity of state education spending, there is little evidence on their broader effects on the total resources available not just for schools in low income districts, but for other programs across all localities. We find that states finance the required increase in education spending in part by reducing their aid to localities for other programs, particularly for wealthier districts. Thus, while court-ordered school finance equalizations do increase total state aid to localities for education, they do so at the expense of drawing state intergovernmental aid away from programs like public welfare, health, hospitals, and general services. These findings provide insight into the effectiveness of using earmarked funds to achieve redistribution.

The growth of medical malpractice liability costs has the potential to affect the delivery of health care in the U.S. along two dimensions. If growth in malpractice payments results in higher malpractice insurance premiums for physicians, these premiums may affect the size and composition of the physician workforce. The growth of potential losses from malpractice liability might also encourage physicians to practice "defensive medicine." We use rich new data to examine the relationship between the growth of malpractice costs and the delivery of health care along both of these dimensions. We pose three questions. First, are increases in payments responsible for increases in medical malpractice premiums? Second, do increases in malpractice liability drive physicians to close their practices or not move to areas with high payments? Third, do increases in malpractice liability change the way medicine is practiced by increasing the use of certain procedures? First, we find that increases in malpractice payments made on behalf of physicians do not seem to be the driving force behind increases in premiums. Second, increases in malpractice costs (both premiums overall and the subcomponent factors) do not seem to affect the overall size of the physician workforce, although they may deter marginal entry, increase marginal exit, and reduce the rural physician workforce. Third, there is little evidence of increased use of many treatments in response to malpractice liability at the state level, although there may be some increase in screening procedures such as mammography.

The quality of care received by Medicare beneficiaries varies across areas. We find that states with higher Medicare spending have lower-quality care. This negative relationship may be driven by the use of intensive, costly care that crowds out the use of more effective care. One mechanism for this trade-off may be the mix of the provider workforce: States with more general practitioners use more effective care and have lower spending, while those with more specialists have higher costs and lower quality. Improving the quality of beneficiaries’ care could be accomplished with more effective use of existing dollars.

The quality of care received by Medicare beneficiaries varies across areas. We find that states with higher Medicare spending have lower-quality care. This negative relationship may be driven by the use of intensive, costly care that crowds out the use of more effective care. One mechanism for this trade-off may be the mix of the provider workforce: States with more general practitioners use more effective care and have lower spending, while those with more specialists have higher costs and lower quality. Improving the quality of beneficiaries’ care could be accomplished with more effective use of existing dollars.

The federal government spends billions of dollars each year on programs designed to increase the resources available to hospitals that serve the poor. This paper explores the intended and unintended effects of such targeted funds. First, how do these funds distort the behavior of state and local governments who wish to appropriate the funds for other uses? Second, to the extent that these funds do increase resources in the targeted hospitals, do patients benefit? We use the rapid and uneven growth in Medicaid Disproportionate Share Hospital (DSH) payments across states and hospitals to answer these questions. We identify states that were most able to appropriate DSH funds and show that, while DSH payments to public hospitals in these states were systematically diverted, DSH payments to other hospitals and in other states were not diverted. Additional resources that were made available to hospitals (rather than appropriated by the state) were associated with significant declines in infant and post-heart attack mortality. A range of evidence suggests that these improvements were due to better hospital care. Overall, our analysis implies that public subsidies can be an effective mechanism for improving medical care and outcomes for the poor, but that the impact is limited by the ability of state and local government to divert the targeted funds.