Literature DB >> 32313968

Assessing the impact of a doctor in remote areas of Brazil.

Joana Raquel Raposo Dos Santos1,2, Hellen Geremias Dos Santos3, Carlos Manuel Matias Dias4,5, Alexandre Dias Porto Chiavegatto Filho6.   

Abstract

OBJECTIVES: The More Doctors Program (MDP) is an ongoing Brazilian policy that aims to improve healthcare by providing physicians to the most vulnerable municipalities. We aimed to measure the impact of MDP in mortality and infant mortality rate, the proportion of live births with low weight, prenatal appointments, childbirths at first and fifth min Apgar, public health investment and immunization in Brazil.
METHODS: Municipal health indicators were collected before and after the intervention (2012 and 2015). Effects were measured by applying propensity score matching with difference-in-differences.
RESULTS: Our findings show that infant mortality presented the highest improvement during the period (a decrease in 11 infant deaths per 1000 live births, p < 0.01). A significant effect, albeit smaller, was also found for the age-standardized total mortality (a decrease in five deaths per 10,000 residents), proportion of children with Apgar score lower than 8 in the fifth min and children with low birth weight.
CONCLUSIONS: MDP contributed to improve important health indicators, highlighting the importance of a doctor in remote areas of Brazil.

Entities:  

Keywords:  Mais médicos; Propensity score; Public health; Public policy

Mesh:

Year:  2020        PMID: 32313968     DOI: 10.1007/s00038-020-01360-z

Source DB:  PubMed          Journal:  Int J Public Health        ISSN: 1661-8556            Impact factor:   3.380


  13 in total

1.  Primary care, infant mortality, and low birth weight in the states of the USA.

Authors:  L Shi; J Macinko; B Starfield; J Xu; J Regan; R Politzer; J Wulu
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2.  Campbell and Rubin: A primer and comparison of their approaches to causal inference in field settings.

Authors:  William R Shadish
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3.  Propensity score matching approach to test the association of income inequality and mortality in Sao Paulo, Brazil.

Authors:  Alexandre Dias Porto Chiavegatto Filho; Ichiro Kawachi; Sabina Léa Davidson Gotlieb
Journal:  J Epidemiol Community Health       Date:  2010-10-05       Impact factor: 3.710

4.  Matching methods for causal inference: A review and a look forward.

Authors:  Elizabeth A Stuart
Journal:  Stat Sci       Date:  2010-02-01       Impact factor: 2.901

5.  Human resources and health outcomes: cross-country econometric study.

Authors:  Sudhir Anand; Till Bärnighausen
Journal:  Lancet       Date:  2004 Oct 30-Nov 5       Impact factor: 79.321

6.  Methods for constructing and assessing propensity scores.

Authors:  Melissa M Garrido; Amy S Kelley; Julia Paris; Katherine Roza; Diane E Meier; R Sean Morrison; Melissa D Aldridge
Journal:  Health Serv Res       Date:  2014-04-30       Impact factor: 3.402

7.  Prognostic score-based balance measures can be a useful diagnostic for propensity score methods in comparative effectiveness research.

Authors:  Elizabeth A Stuart; Brian K Lee; Finbarr P Leacy
Journal:  J Clin Epidemiol       Date:  2013-08       Impact factor: 6.437

8.  Optimal caliper widths for propensity-score matching when estimating differences in means and differences in proportions in observational studies.

Authors:  Peter C Austin
Journal:  Pharm Stat       Date:  2011 Mar-Apr       Impact factor: 1.894

9.  An Introduction to Propensity Score Methods for Reducing the Effects of Confounding in Observational Studies.

Authors:  Peter C Austin
Journal:  Multivariate Behav Res       Date:  2011-06-08       Impact factor: 5.923

10.  Primary care physicians and infant mortality: Evidence from Brazil.

Authors:  Letícia Xander Russo; Anthony Scott; Peter Sivey; Joilson Dias
Journal:  PLoS One       Date:  2019-05-31       Impact factor: 3.240

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  1 in total

1.  Assessing the performance of beneficiary targeting in Brazil's More Doctors Programme.

Authors:  Ece A Özçelik; Adriano Massuda; Margaret McConnell; Marcia C Castro
Journal:  Health Policy Plan       Date:  2021-03-26       Impact factor: 3.344

  1 in total

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