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Policy Points In two respects, quality of care tends to be higher at major teaching hospitals: process of care and long‐term survival of cancer patients following initial diagnosis. There is also evidence that short‐term (30‐day) mortality is lower on average at such hospitals, although the quality of evidence is somewhat lower. Quality of care is mulitdimensional. Empirical evidence by teaching status on dimensions other than survival is mixed. Higher Medicare payments for care provided by major teaching hospitals are partially offset by lower payments to nonhospital providers. Nevertheless, the payment differences between major teaching and nonteaching hospitals for hospital stays, especially for complex cases, potentially increase prices other insurers pay for hospital care. Context The relative performance of teaching hospitals has been discussed for decades. For private and public insurers with provider networks, an issue is whether having a major teaching hospital in the network is a “must.” For traditional fee‐for‐service Medicare, there is an issue of adequacy of payment of hospitals with various attributes, including graduate medical education (GME) provision. Much empirical evidence on relative quality and cost has been published. This paper aims to (1) evaluate empirical evidence on relative quality and cost of teaching hospitals and (2) assess what the findings indicate for public and private insurer policy. Methods Complementary approaches were used to select studies for review. (1) Relevant studies highly cited in Web of Science were selected. (2) This search led to studies cited by these studies as well as studies that cited these studies. (3) Several literature reviews were helpful in locating pertinent studies. Some policy‐oriented papers were found in Google under topics to which the policy applied. (4) Several papers were added based on suggestions of reviewers. Findings Quality of care as measured in process of care studies and in longitudinal studies of long‐term survival of cancer patients tends to be higher at major teaching hospitals. Evidence on survival at 30 days post admission for common conditions and procedures also tends to favor such hospitals. Findings on other dimensions of relative quality are mixed. Hospitals with a substantial commitment to graduate medical education, major teaching hospitals, are about 10% to 20% more costly than nonteaching hospitals. Private insurers pay a differential to major teaching hospitals at this range's lower end. Inclusive of subsidies, Medicare pays major teaching hospitals substantially more than 20% extra, especially for complex surgical procedures. Conclusions Based on the evidence on quality, there is reason for patients to be willing to pay more for inclusion of major teaching hospitals in private insurer networks at least for some services. Medicare payment for GME has long been a controversial policy issue. The actual indirect cost of GME is likely to be far less than the amount Medicare is currently paying hospitals.

This article reviews economic studies based on data from high income countries published from 2007 to early 2024 to address three questions: (1) How accurate are subjective beliefs, mainly measured by subjective probabilities, compared to their objective counterparts? Objective evidence comes from another source (e.g., life table, empirical study, expert opinion), or subsequent realizations of beliefs elicited at baseline. (2) How are subjective beliefs determined? (3) Do subjective beliefs affect health behaviors? Several domains are included: survival, and health behaviors—smoking, alcohol consumption and impaired driving, preventive care, diet, and COVID-19 precautions. Results on a single domain, (e.g., survival), do not generalize to, e.g., COVID-19 results. Subjective probabilities embody private information (e.g., self-assessed health, parent longevity). However, individuals seem insufficiently informed about population-level probabilities. There is no systematic overestimation or underestimation of objective probabilities. Several determinants of beliefs are identified (demographic characteristics, education, cognition, current self-assessed health, health histories), but evidence on underlying mechanisms is lacking, how determinants, (e.g., education), affect beliefs. Subjective beliefs, even with substantial noise, often affect health behaviors. Given prior evidence that beliefs are influenced by health shocks, this article reviews research on effects of health shocks on health behaviors. A major health shock to an individual—a new diagnosis (e.g., diabetes) or a serious adverse health event (e.g., heart attack), by changing subjective probabilities leads to some healthier behaviors, however, sometimes only temporarily. Behaviors may also be influenced by utility loss following a health shock, e.g., learning about pecuniary and non-pecuniary costs of hospitalization.

This study uses a dynamic discrete choice model to examine the degree of present bias and naivete about present bias in individuals' health care decisions. Clinical guidelines exist for several common chronic diseases. Although the empirical evidence for some guidelines is strong, many individuals with these diseases do not follow the guidelines. Using persons with diabetes as a case study, we find evidence of substantial present bias and naivete. Counterfactual simulations indicate the importance of present bias and naivete in explaining low adherence rates to health care guidelines.

BackgroundThe 2016 presidential election and the controversial policy agenda of its victor have raised concerns about how the election may have impacted mental health.ObjectiveAssess how mental health changed from before to after the November 2016 election and how trends differed in states that voted for Donald Trump versus Hillary Clinton.DesignPre- versus post-election study using monthly cross-sectional survey data.ParticipantsA total of 499,201 adults surveyed in the Behavioral Risk Factor Surveillance System from May 2016 to May 2017.ExposureResidence in a state that voted for Trump versus state that voted for Clinton and the candidate’s margin of victory in the state.Main MeasuresSelf-reported days of poor mental health in the last 30 days and depression rate.Key ResultsCompared to October 2016, the mean days of poor mental health in the last 30 days per adult rose from 3.35 to 3.85 in December 2016 in Clinton states (0.50 days difference, p = 0.005) but remained statistically unchanged in Trump states, moving from 3.94 to 3.78 days (− 0.17 difference, p = 0.308). The rises in poor mental health days in Clinton states were driven by older adults, women, and white individuals. The depression rate in Clinton states began rising in January 2017. A 10–percentage point higher margin of victory for Clinton in a state predicted 0.41 more days of poor mental health per adult in December 2016 on average (p = 0.001).ConclusionsIn states that voted for Clinton, there were 54.6 million more days of poor mental health among adults in December 2016, the month following the election, compared to October 2016. Clinicians should consider that elections could cause at least transitory increases in poor mental health and tailor patient care accordingly, especially with the 2020 election upon us.

Objectives. To explore associations between in utero exposure to the 1918 influenza pandemic and hospitalization rates in old age (≥ 70 years) in the United States. Methods. We identified individuals exposed (mild and deadly waves) and unexposed in utero to the 1918 influenza pandemic (a natural experiment) by using birth dates from the Asset and Health Dynamics Among the Oldest Old survey. We analyzed differences in hospitalization rates by exposure status with multivariate linear regression. Results. In utero exposure to the deadly wave of the 1918 influenza pandemic increased the number of hospital visits by 10.0 per 100 persons. For those exposed in utero to the deadliest wave of the influenza pandemic, high rates of functional limitations are shown to drive the higher rates of hospitalizations in old age. Conclusions. In utero exposure to the influenza pandemic increased functional limitations and hospitalization rates in old age. Public Health Implications. To determine investments in influenza pandemic prevention programs that protect fetal health, policymakers should include long-term reductions in hospitalizations in their cost–benefit evaluations.

The 2003 Medicare Modernization Act introduced income-related premiums on Medicare coverage for professional services (Part B) for the first time. Beginning in 2007, higher-income households were required to pay higher premiums for Part B coverage, which raises the price of Medicare relative to employer-sponsored health insurance for these households. The authors exploit this exogenous change in Medicare policy to examine the impact of Part B premiums on the labor supply decisions of older adults. They find that higher Medicare premiums delay retirement. Findings have important implications for Medicare policy and labor markets.

Analyze relationships between adherence to guidelines for diabetes care – regular screening; physical activity; and medication – and diabetes complications and mortality. Outcomes were onset of congestive heart failure (CHF), stroke, renal failure, moderate complications of lower extremities, lower-limb amputation, proliferative diabetic retinopathy (PDR), and mortality during follow-up. Participants were persons aged 65+ in the Health and Retirement Study (HRS) 2003 Diabetes Study and had Medicare claims in follow-up period (2004–8). Adherence to screening recommendations decreased risks of developing CHF (odds ratio (OR)=0.83; 95% confidence interval (CI): 0.72–0.96), stroke (OR=0.80; 95% CI: 0.68–0.94); renal failure (OR=0. 82; 95% CI: 0.71–0.95); and death (OR=0.86; 95% CI: 0.74–0.99). Adherence to physical activity recommendation reduced risks of stroke (OR=0.64; 95% CI: 0.45–0.90), renal failure (OR=0.71; 95% CI: 0.52–0.97), moderate lower-extremity complications (OR=0.71; 95% CI: 0.51–0.99), having a lower limb amputation (OR=0.31, 95% CI: 0.11–0.85), and death (OR=0.56, 95% CI: 0.41–0.77). Medication adherence was associated with lower risks of PDR (OR=0.35, 95% CI: 0.13–0.93). Adherence to screening, physical activity and medication guidelines was associated with lower risks of diabetes complications and death. Relative importance of adherence differed among outcome measures.

Objectives. This study determined the life extension obtained from stopping smoking at various ages. Methods. We estimated the relation between smoking and mortality among 877 243 respondents to the Cancer Prevention Study II. These estimates were applied to the 1990 US census population to examine the longevity benefits of smoking cessation. Results. Life expectancy among smokers who quit at age 35 exceeded that of continuing smokers by 6.9 to 8.5 years for men and 6.1 to 7.7 years for women. Smokers who quit at younger ages realized greater life extensions. However, even those who quit much later in life gained some benefits: among smokers who quit at age 65 years, men gained 1.4 to 2.0 years of life, and women gained 2.7 to 3.7 years. Conclusions. Stopping smoking as early as possible is important, but cessation at any age provides meaningful life extensions. (Am J Public Health. 2002;92:990–996)

China has made profound progress in advancing universal health coverage (UHC) over the past two decades. New Cooperative Medical Scheme (NCMS) was initiated in 2003 to provide health insurance coverage to rural population. Its benefit packages and cost-sharing mechanism have changed significantly over time. This study aims to assess the impact of changing NCMS policies on NCMS enrollees’ service utilisation, medical financial burden and equity between 2003 and 2013. Data are from China National Health Services Survey (NHSS) which is conducted every 5 years. We used the subsample of NHSS that were enrolled in NCMS in 2003, 2008 and 2013. From 2003 to 2013, we found increased service utilisation and an elimination of inequity in service utilisation with respect to income. Contradicting prior findings of increasing financial burden after the NCMS implementation, we identified significant protective effect of NCMS against financial risks, and a reduction in percentage of households with high medical expenditure in the middle-income and high-income quintiles. The rural residents from the low-income groups have high financial risk, therefore, should be the priority target for future reforms. In pursuit of UHC globally, many countries struggle to provide good coverage to the disadvantaged rural population and balance between the competing priorities of various UHC dimensions. Our trend analysis revealed China’s two-stage approach with NCMS reform that first focused on expanding population coverage, then on service coverage and financial risk protection. This path could potentially be replicated in other middle-income and low-income countries to pave the way for UHC.