Journal of Health Economics最新文献

Traffic fatalities are the leading cause of mortality in the United States despite being preventable. While several policies have been introduced to improve traffic safety and their effects have been well documented, the role of transitory health shocks or situational factors at explaining variations in fatal traffic accidents has been understudied. Exploring daily variation in city-specific pollen counts, this study finds novel evidence that traffic fatalities increase on days in which the local pollen count is particularly high. We find that the effects are present in accidents involving private vehicles and occur most frequently on the weekends, suggesting potentially the missed opportunity to avoid these fatalities. We do not find similar effects for fleet vehicles. These findings remain robust to alternative specifications and alternative definitions of high pollen count. Taken together, this study finds evidence that a prevalent and transitory exogenous health-shock, namely pollen allergies, increases traffic fatalities. Given our lack of evidence of avoidance, these effects are not mechanical and are likely driven by cognitive impairments that arise as a result of seasonal allergies.

We analyse a model of optimal risk adjustment in competitive health-insurance markets which suffer from both ex-ante adverse selection and ex-post moral hazard. We find, firstly, that, unlike in an adverse-selection-only market, in an environment where also moral hazard is important, removing insurers' selection incentives requires risk-adjustment payments that do not fully equalize costs among consumer types. Current practice of attempting to correct for all predictable cost differences among consumers is then misguided. Secondly, if the sponsor of the risk-adjustment system is not only concerned with eliminating selection distortions, but also wants to redistribute towards high-risk consumers, the required higher risk-adjustment payments will introduce selection distortions in high-risk consumers' contracts. This leads to excessive equilibrium provision of care for those suffering severe health shocks. Finally, insurer market power creates countervailing incentives, helping the risk adjuster to combat selection distortions but working against a risk-adjustment regulation that also cares about redistribution.

Employing more than 2 million emergency department (ED) records, we combine machine learning and regression discontinuity to document novel distortions in triage nurses' assessments of patients' conditions and investigate the short- and medium-term consequences for patients. We show that triage nurses progressively become more lenient during their shifts, and identical ED patients arriving just after a shift change are thus assigned a lower priority. We show that these patients receive lower levels of care and require additional emergency care afterward. We conclude that distortions in nurses' initial assessments of urgency bias' medical staff's perceptions.

We examine whether ridesharing provides a meaningful transportation alternative for those who require ongoing healthcare. Specifically, we combine variation in UberX entry across the U.S. with the Treatment Episode Data Set to estimate the effect of ridesharing on admissions to substance use disorder treatment. People needing such treatment report transportation as a barrier to receiving care. We find that UberX entry into a Core Based Statistical Area has no effect on the overall number of treatment admissions. However, we find a decline in non-intensive outpatient treatment which is fully offset by an increase in intensive outpatient treatment. Given the required relative frequency of non-intensive and intensive outpatient treatment in terms of visits per week, our findings indicate that UberX helps to reduce transportation barriers to accessing healthcare. Event-studies show parallel trends in outcomes before UberX entry and results are robust to numerous sensitivity checks.

We explore the role of epigenetic biological age in predicting subsequent health care utilisation. We use longitudinal data from the UK Understanding Society panel, capitalising on the availability of baseline epigenetic biological age measures along with data on general practitioner (GP) consultations, outpatient (OP) visits, and hospital inpatient (IP) care collected 5-12 years from baseline. Using least absolute shrinkage and selection operator (LASSO) regression analyses and accounting for participants' pre-existing health conditions, baseline biological underlying health, and socio-economic predictors we find that biological age is selected as a predictor of future GP consultations and IP care, while chronological rather than biological age is selected for future OP visits. Post-selection prediction analysis and Shapley-Shorrocks decompositions, comparing our preferred prediction models to models that replace biological age with chronological age, suggest that biological ageing has a stronger role in the models predicting future IP care as opposed to "gatekeeping" GP consultations.

This study examines the causal effects of sunlight exposure on suicide rates. Leveraging county-month-year data on solar insolation and suicide rates in the U.S. from 1979 to 2004, we provide first robust evidence that insufficient sunlight increases suicide rates. We also find that insufficient sunlight increases Google searches containing depressive language, suggesting a potential adverse impact on mental well-being. Importantly, our findings favor a biological pathway over alternative mechanisms. The estimated effect of sunlight on suicide, often exceeding other interventions in magnitude, sheds new light on sunlight as a significant risk factor in suicide incidence.

We conduct a randomized experiment (n = 600) to evaluate a Supported Employment (SE) program that, through intensive job coaching and follow-along support, aims to increase work activity of Belgian Disability Insurance (DI) recipients with mental health conditions. The control group gets regular vocational rehabilitation. After a 30-month follow-up period, we find that SE increases the probability of working while claiming DI by 7.5 percentage points and reduces the amount of DI benefit received by 110 euros per month (-9.5 percent).

Policies that increase contraceptive access for young women and their partners are a potentially low-cost way of reducing unintended pregnancies and improving later life outcomes. Several states have recently implemented laws that allow pharmacists to prescribe contraceptives to women without the need to see a physician. We study the effect of these state laws on fertility rates. Using US Natality files for 2014-2020, we employ a difference-in-differences strategy using the 13 states that had enacted a law until the first quarter of 2020 as the treated group, and the 15 policy-implementing states post-2020 quarter 1 as the control group. We find approximately 0.5 fewer births per 1000 women aged 15-49 per quarter occur post law implementation, compared to control states. The effect of the policy appears to be focused among women aged 25-34 and 40-44 and women with a high school education or less.