Evidence map›Paper›PMID 39380055›Full record

ArticleBMC research notes2024

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

Jéssica Souza, Cristiano Boccolini, Lais Baroni, Kele Belloze, Eduardo Bezerra, Marcel Pedroso, Ronaldo Fernandes Santos Alves, Eduardo Ogasawara

Abstract read
In one paragraph

Article in BMC research notes, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

8 authors.

Jéssica SouzaFederal Center for Technological Education of Rio de Janeiro, CEFET/RJ, Rio de Janeiro, Brazil. jessica.souza@eic.cefet-rj.br.
Cristiano BoccoliniInstitute of Scientific and Technological Communication and Information in Health, Oswaldo Cruz Foundation, Fiocruz, Rio de Janeiro, Brazil.
Lais BaroniFederal Center for Technological Education of Rio de Janeiro, CEFET/RJ, Rio de Janeiro, Brazil.
Kele BellozeFederal Center for Technological Education of Rio de Janeiro, CEFET/RJ, Rio de Janeiro, Brazil.
Eduardo BezerraFederal Center for Technological Education of Rio de Janeiro, CEFET/RJ, Rio de Janeiro, Brazil.
Marcel PedrosoInstitute of Scientific and Technological Communication and Information in Health, Oswaldo Cruz Foundation, Fiocruz, Rio de Janeiro, Brazil.
Ronaldo Fernandes Santos AlvesInstitute of Scientific and Technological Communication and Information in Health, Oswaldo Cruz Foundation, Fiocruz, Rio de Janeiro, Brazil.
Eduardo OgasawaraFederal Center for Technological Education of Rio de Janeiro, CEFET/RJ, Rio de Janeiro, Brazil.

Funding

Bill and Melinda Gates Foundation 027961Coordenação de Aperfeiçoamento de Pessoal de Nível Superior 001
6 · The paper itself

Abstract

objectivesThe 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.

resultsIn 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.

Indexed as

CitiesInfant MortalityPopulation DensityBrazilHumansInfantInfant, NewbornBrazilControl chartDiagnosis of health situationInfant mortalityRoutinely collected health dataStatistical process control

Identifiers

PMID39380055
PMCPMC11462655

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.