Dataset Information

Challenges facing the More Doctors program (Programa Mais Medicos) in vulnerable and peri-urban areas in Greater Brasilia, Brazil

ABSTRACT:

Background

A shortage of physicians, especially in vulnerable and peri-urban areas, is a global phenomenon that has serious implications for health systems, demanding policies to assure the provision and retention of health workers. The aim of this study was to analyze the strategies employed by the More Doctors Program (Programa Mais Médicos) to provide primary care physicians in vulnerable and peri-urban parts of Greater Brasilia.

Methods

The study used a qualitative approach based on the precepts of social constructivism. Forty-nine semi-structured interviews were conducted: 24 with physicians employed as part of the More Doctors program, five with program medical supervisors, seven with secondary care physicians, twelve with primary care coordinators, and one federal administrator. The interviews occurred between March and September 2019. The transcripts of the interviews were submitted to thematic content analysis.

Results

The partnership between the Ministry of Health and local authorities was essential for the provision of doctors—especially foreign doctors, most from Cuba, to assist vulnerable population groups previously without access to the health system. There was a notable presence of doctors with experience working with socioeconomically disadvantaged populations, which was important for gaining a better understanding of the effects of the endemic urban violence in the region. The incentives and other institutional support, such as enhanced salaries, training, and housing, transportation, and food allowances, were factors that helped provide a satisfactory working environment. However, the poor state of the infrastructure at some of the primary care units and limitations of the health service as a whole were factors that hampered the provision of comprehensive care, constituting a cause of dissatisfaction.

Conclusions

More Doctors introduced a range of novel strategies that helped ensure a supply of primary care doctors in vulnerable and peri-urban parts of Greater Brasilia. The inclusion of foreign doctors, most from Cuba, was crucial for the success of the health services provided for the local communities, who subsist in violent and socioeconomically deprived urban areas. However, it became clear that barriers from within the health service itself hampered the physicians’ capacity to provide a satisfactory service. As such, what is needed for primary care to be effective is not just the recruitment, training, and deployment of doctors, but also investment in the organization of the whole health system.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12960-021-00672-2.

SUBMITTER: Shimizu H

PROVIDER: S-EPMC8559374 | biostudies-literature |

REPOSITORIES: biostudies-literature

ACCESS DATA

Similar Datasets

Project description:BackgroundThe "Mais Médicos (More Doctors) Program" established in 2013 by the Brazilian Government aimed to reduce inequalities by means of an emergency provision of physicians, the improvement of medical care service in the Brazilian Unified Health System, and the expansion of medical education training in Brazil. In this context, equity should be considered when defining priorities and allocating resources. This study describes the distribution of physicians for the Program in five Brazilian metropolitan regions (MRs) and analyses whether the most vulnerable areas within each one of these regions had been prioritized in compliance with the legislation framework of the program.MethodsThis is a quantitative cross-sectional study. Official secondary data was analyzed to verify the relationship between the Index of Social Vulnerability, set up by the Institute of Applied Economic Research, and the physician allocation provided by the Program. The data were organized into categories and quintiles. For spatialization purposes, the QGIS 3.4 Madeira software was used.ResultsThere are 2592 primary health care units, (in Portuguese, UBS), within the five MRs studied; 981 of these hosted at least one physician from the Program. In the Manaus, Recife, and the DF MRs, the 4th and 5th quintiles (the most vulnerable ones) hosted physicians in more significant proportions than the other quintiles, namely, 71.4%, 71.4%, and 52.2%, respectively, exceeding the national average (51.7%). It is worth mentioning that in the São Paulo MR, the units located in the most vulnerable quintiles (4th and 5th) also hosted physicians in proportions significantly higher than others (45.8%); however, this proportion did not reach 50%. There was no significant difference in the allocation of physicians in the Porto Alegre MR, indicating that there was no prioritization of the UBS according to vulnerability.ConclusionsThese results appoint to the enormous gaps of vulnerability existing both between the analyzed MRs and internally in each one of them. It emphasizes the need for criteria for the allocation of physicians so as not to increase inequities. It also highlights the importance of the continuity of the "Mais Médicos (More Doctors) Program" in the metropolitan regions, above all, in areas of extreme vulnerabilities. On the other hand, they contribute to the national debate about the importance of public policies regarding constitutional rights related to access to health care and the relevance of primary care and the "Mais Médicos (More Doctors) Program" for the reduction of disparities regarding access to health care, especially for the citizens who live in regions of greater vulnerability, whether it is inside or outside large metropolitan regions.

Project description:Algorithmic scoring methods are widely used in the finance industry for several decades in order to prevent risk and to automate and optimize decisions. Regulatory requirements as given by the Basel Committee on Banking Supervision (BCBS) or the EU data protection regulations have led to an increasing interest and research activity on understanding black box machine learning models by means of explainable machine learning. Even though this is a step into a right direction, such methods are not able to guarantee for a fair scoring as machine learning models are not necessarily unbiased and may discriminate with respect to certain subpopulations such as a particular race, gender, or sexual orientation-even if the variable itself is not used for modeling. This is also true for white box methods like logistic regression. In this study, a framework is presented that allows analyzing and developing models with regard to fairness. The proposed methodology is based on techniques of causal inference and some of the methods can be linked to methods from explainable machine learning. A definition of counterfactual fairness is given together with an algorithm that results in a fair scoring model. The concepts are illustrated by means of a transparent simulation and a popular real-world example, the German Credit data using traditional scorecard models based on logistic regression and weight of evidence variable pre-transform. In contrast to previous studies in the field for our study, a corrected version of the data is presented and used. With the help of the simulation, the trade-off between fairness and predictive accuracy is analyzed. The results indicate that it is possible to remove unfairness without a strong performance decrease unless the correlation of the discriminative attributes on the other predictor variables in the model is not too strong. In addition, the challenge in explaining the resulting scoring model and the associated fairness implications to users is discussed.

Project description:Since 2015 Brazil has experienced the social repercussions of the Zika virus epidemic, thus raising a debate about: difficulties of diagnosis; healthcare access for children with Zika Congenital Syndrome (ZCS); the search for benefits by affected families; social and gender inequalities; and a discussion on reproductive rights, among others. The objective of this article is to analyse access to specialized health services for the care of children born with ZCS in three North-eastern states of Brazil. This is an exploratory cross-sectional study which analyses recorded cases of microcephaly at the municipal level between 2015 and 2017. Most of the cases of ZCS were concentrated on the Northeast coast. Rio Grande do Norte and Paraiba had the highest incidence of microcephaly in the study period. The states of Bahia, Paraiba and Rio Grande do Norte were selected for their high incidence of microcephaly due to the Zika Virus. Socio-territorial vulnerability was stratified using access to microcephaly diagnosis and treatment indicators. The specialized care network was mapped according to State Health Secretaries Protocols. A threshold radius of 100 km was stablished as the maximum distance from municipalities centroids to specialised health care for children with microcephaly. Prenatal coverage was satisfactory in most of the study area, although availability of ultrasound equipment was uneven within states and health regions. Western Bahia had the lowest coverage of ultrasound equipment and lacked health rehabilitation services. ZCS's specialized health services were spread out over large areas, some of which were outside the affected patients' home municipalities, so displacements were expensive and very time consuming, representing an extra burden for the affected families. This study is the first to address accessibility of children with microcephaly to specialised health care services and points to the urgent need to expand coverage of these services in Brazil, especially in the northeastern states, which are most affected by the epidemic.