Evaluation of statistical process control charts for infant mortality monitoring in Brazilian cities with different population sizes.

Autor: Souza J; Federal Center for Technological Education of Rio de Janeiro, CEFET/RJ, Rio de Janeiro, Brazil. jessica.souza@eic.cefet-rj.br., Boccolini C; Institute of Scientific and Technological Communication and Information in Health, Oswaldo Cruz Foundation, Fiocruz, Rio de Janeiro, Brazil., Baroni L; Federal Center for Technological Education of Rio de Janeiro, CEFET/RJ, Rio de Janeiro, Brazil., Belloze K; Federal Center for Technological Education of Rio de Janeiro, CEFET/RJ, Rio de Janeiro, Brazil., Bezerra E; Federal Center for Technological Education of Rio de Janeiro, CEFET/RJ, Rio de Janeiro, Brazil., Pedroso M; Institute of Scientific and Technological Communication and Information in Health, Oswaldo Cruz Foundation, Fiocruz, Rio de Janeiro, Brazil., Alves RFS; Institute of Scientific and Technological Communication and Information in Health, Oswaldo Cruz Foundation, Fiocruz, Rio de Janeiro, Brazil., Ogasawara E; Federal Center for Technological Education of Rio de Janeiro, CEFET/RJ, Rio de Janeiro, Brazil.
Jazyk: angličtina
Zdroj: BMC research notes [BMC Res Notes] 2024 Oct 08; Vol. 17 (1), pp. 299. Date of Electronic Publication: 2024 Oct 08.
DOI: 10.1186/s13104-024-06943-0
Abstrakt: Objectives: The control chart is a classic statistical technique in epidemiology for identifying trends, patterns, or alerts. One meaningful use is monitoring and tracking Infant Mortality Rates, which is a priority both domestically and for the World Health Organization, as it reflects the effectiveness of public policies and the progress of nations. This study aims to evaluate the applicability and performance of this technique in Brazilian cities with different population sizes using infant mortality data.
Results: In this article, we evaluate the effectiveness of the statistical process control chart in the context of Brazilian cities. We present three categories of city groups, divided based on population size and classified according to the quality of the analyses when subjected to the control method: consistent, interpretable, and inconsistent. In cities with a large population, the data in these contexts show a lower noise level and reliable results. However, in intermediate and small-sized cities, the technique becomes limited in detecting deviations from expected behaviors, resulting in reduced reliability of the generated patterns and alerts.
(© 2024. The Author(s).)
Databáze: MEDLINE
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