Research

The lack of physicians in poorer areas is a matter of concern in developed and developing countries. This paper exploits location choices and individual characteristics of all generalist physicians who graduated in Brazil between 2001 and 2013 to study policies that aim at increasing the supply of physicians in underserved areas. We estimate physicians’ locational preferences using a random coefficients discrete choice model. We find that physicians have substantial utility gains if they work close to the region they were born or from where they graduated. We show that wages and health infrastructure, though relevant, are not the main drivers of physicians’ location choices. Simulations from the model indicate that quotas in medical schools for students born in underserved areas and the opening of vacancies in medical schools in deprived areas improve the spatial distribution of physicians at lower costs than financial incentives or investments in health infrastructure.

This study assess socioeconomic-related inequalities in health and healthcare utilization among the elderly in Brazil.  We evaluated the Brazilian National Health Survey data collected in 2019 and computed the prevalence of measures of health conditions and healthcare utilization by age-bracket and markers of socioeconomic status—income, educational attainment, and race/ethnicity—among individuals aged 60 or older. We further employed logistic regression models, adjusted for a wide set of covariates, to estimate the relationship between socioeconomic status and those outcomes. Results from regression models showed strong associations with income and educational attainment for most health conditions: health status, physical activity, difficulties with activities of daily living and instrumental activities of daily living, and depression. For most conditions, weaker or no associations with race/ethnicity were found. Individuals in the highest income quintile and that completed higher education also had higher odds of having consulted a physician, while high-income individuals had lower odds of having received emergency care at home. The findings of this study highlight the significant socioeconomic inequalities in the health of the elderly population in Brazil. 

The Brazilian private health insurance market is the second largest in the world, covering approximately 47 million people in 2019. This paper documents how physicians' inpatient reimbursement fees vary in Brazil and analyzes their relationship with health providers and health insurance market concentrations. We implement a fixed-effects panel regression and take advantage of an unprecedented database that contains information on national administrative records of inpatient procedures paid by health insurance companies in 2016. We find a positive correlation between reimbursement for ICU procedures and providers' market share and a negative correlation for insurers. We also document substantial variation in procedure prices between and within Brazilian states and that more competitive markets are more populous and richer in terms of GDP. These results suggest that more concentrated providers' markets tend to practice higher procedure fees, but that can be compensated by the insurers' bargain power. The study contributes to a better understanding of these dynamics in a developing country context and may help policymakers implement adequate regulation to guarantee access to healthcare.

Power is an important factor in assessing the likely validity of a statistical estimate. An analysis with low power is unlikely to produce convincing evidence of a treatment effect even when one exists. Of greater concern, a statistically significant estimate from a low-powered analysis is likely to misstate the true effect size, including finding estimates of the wrong sign or that are several times too large. Yet statistical power is rarely reported in published economics work. This is in part because many modern research designs are complex enough that power cannot be easily ascertained using simple formulae. Power can also be difficult to estimate in observational settings. Using an applied example–the link between gaining health insurance and mortality–we conduct a simulated power analysis to outline the importance of power and ways to estimate power in complex research settings. We find that standard difference-in-differences and triple differences analyses of Medicaid expansions using county or state mortality data would need to induce reductions in population mortality of at least 2% to be well powered. While there is no single, correct method for conducting a simulated power analysis, our manuscript outlines how applied researchers can conduct simulations appropriate to their settings. 

In this Article, we present a comprehensive analysis of health-system preparedness and response to COVID-19 in Brazil. We examine the relationship between the availability of health-care resources in different parts of the country, the socioeconomic characteristics of the population (eg, income, housing, and employment status), risk factors for adverse COVID-19 outcomes (age and burden of chronic disease), and socioeconomic vulnerability, with the pattern of spread, response, and outcomes of the epidemic, as measured by the number of deaths by state and municipality.  Our results show that the initial spread of COVID-19 was mostly affected by patterns of socioeconomic vulnerability as measured by the SVI rather than population age structure and prevalence of health risk factors. The states with a high (greater than median) SVI were able to expand hospital capacity, to enact stringent COVID-19-related legislation, and to increase physical distancing adherence in the population, although not sufficiently to prevent higher COVID-19 mortality during the initial phase of the epidemic compared with states with a low SVI. Death rates accelerated until June, 2020, particularly in municipalities with the highest socioeconomic vulnerability. Throughout the following months, however, differences in policy response converged in municipalities with lower and higher SVIs, while physical distancing remained relatively higher and death rates became relatively lower in the municipalities with the highest SVIs compared with those with lower SVIs. 

Hospitals are under increasing pressure as they bear a growing burden of chronic disease while also dealing with emergency cases that do not all require hospital care. Many countries have responded by introducing alternative facilities that provide 24/7 care for basic and medium-complexity cases. Using administrative data, we investigate the impacts of opening these intermediate facilities (UPA) in Rio de Janeiro in Brazil. We find that an UPA opening in the catchment area of a hospital reduces hospital outpatient procedures and admissions and that this is associated with improved hospital performance. There is a decline in inpatient mortality, particularly mortality from the more complex conditions that hospitals are best equipped to deal with. There is no discernible change in the risk profile of cases going to hospital, and no concurrent policy changes that can account for these findings. In order to capture displacement effects, we investigate city-level population outcomes. We find that two-thirds of the decline in hospital mortality is offset by deaths in UPAs. Looking at individual death causes, we see a net decline in deaths from congestive heart failure.