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Home / Publications / Health Surveillance and safety in maternal and neonatal care: proposal of logic model

Health Surveillance and safety in maternal and neonatal care: proposal of logic model

  • Authors: Ana Maria Bourguignon, Zulmira Hartz, Dirceia Moreira
  • Publication Year: 2020
  • Journal: Monitoramento & Avaliação em Vigilância Sanitária Vol.8 Nº4
  • Link: https://doi.org/10.22239/2317-269x.01657
Introduction: The promotion of patient safety in maternal and neonatal care services is a priority area for health policy in Brazil, because it contributes to reducing the morbidity and mortality of women and newborns. Objective: To elaborate a logical model based on the handbook Maternal and Neonatal Care Services: Safety and Quality, in which the National Health Surveillance Agency compiles specific recommendations for services whose target audience is pregnant and puerperal women, as well as their sons and daughters. Method: This is a qualitative, descriptive study, which used documentary analysis as a methodological procedure. The normative assessment sought to answer a script with twelve questions prepared by Bezerra et al. for program modeling. Results: It was evidenced that the integration between Health Surveillance and obstetric and neonatal care services is necessary, so that the desired effects can be achieved. Conclusions: The proposed logical model can be a useful tool, both for the organization and permanent
monitoring of services, and for professionals working in Health Surveillance. Additionally, it may enhance the recognition of the health surveillance contribution to the promotion
of maternal and infant health.

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About GHTM

GHTM is a R&D Unit that brings together researchers with a track record in Tropical Medicine and International & Global Health. It aims at strengthening Portugal's role as a leading partner in the development and implementation of a global health research agenda. Our evidence-based interventions contribute to the promotion of equity in health and to improve the health of populations.

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