دورية أكاديمية
أعرض في EDS

Factors associated with the quality of death certification in Brazilian municipalities: A data-driven non-linear model.

التفاصيل البيبلوغرافية
العنوان: Factors associated with the quality of death certification in Brazilian municipalities: A data-driven non-linear model.
المؤلفون: Zimeo Morais GA; Department of Big Data, Hospital Israelita Albert Einstein, São Paulo, São Paulo, Brazil., Miraglia JL; Department of Big Data, Hospital Israelita Albert Einstein, São Paulo, São Paulo, Brazil., de Oliveira BZ; Department of Big Data, Hospital Israelita Albert Einstein, São Paulo, São Paulo, Brazil., Mistro S; Multidisciplinary Institute of Health, Federal University of Bahia, Vitoria da Conquista, Bahia, Brazil., Hisatugu WH; Department of Computing and Electronics, Federal University of Espirito Santo, Vitoria, Espírito Santo, Brazil., Greffin D; Sabin Diagnostic Medicine, Brasilia, Federal District, Brazil., Marques CB; NeuralMed, São Paulo, São Paulo, Brazil., Reis EP; Department of Big Data, Hospital Israelita Albert Einstein, São Paulo, São Paulo, Brazil., de Lima HM; Samel Group, Manaus, Amazonas, Brazil., Szlejf C; Department of Big Data, Hospital Israelita Albert Einstein, São Paulo, São Paulo, Brazil.
المصدر: PloS one [PLoS One] 2023 Aug 31; Vol. 18 (8), pp. e0290814. Date of Electronic Publication: 2023 Aug 31 (Print Publication: 2023).
نوع المنشور: Journal Article; Research Support, Non-U.S. Gov't
اللغة: English
بيانات الدورية: Publisher: Public Library of Science Country of Publication: United States NLM ID: 101285081 Publication Model: eCollection Cited Medium: Internet ISSN: 1932-6203 (Electronic) Linking ISSN: 19326203 NLM ISO Abbreviation: PLoS One Subsets: MEDLINE
أسماء مطبوعة: Original Publication: San Francisco, CA : Public Library of Science
مواضيع طبية MeSH: Death Certificates* , Nonlinear Dynamics*, Humans ; Brazil ; Cities ; Retrospective Studies ; Seizures
مستخلص: Studies evaluating the local quality of death certification in Brazil focused on completeness of death reporting or inappropriate coding of causes of death, with few investigating missing data. We aimed to use missing and unexpected values in core topics to assess the quality of death certification in Brazilian municipalities, to evaluate its correlation with the percentage of garbage codes, and to employ a data-driven approach with non-linear models to investigate the association of the socioeconomic and health infrastructure context with quality of death statistics among municipalities. This retrospective study used data from the Mortality Information System (2010-2017), and municipal data regarding healthcare infrastructure, socioeconomic characteristics, and death rates. Quality of death certification was assessed by missing or unexpected values in the following core topics: dates of occurrence, registration, and birth, place of occurrence, certifier, sex, and marital status. Models were fit to classify municipalities according to the quality of death certification (poor quality defined as death records with missing or unexpected values in core topics ≥ 80%). Municipalities with poor quality of death certification (43.9%) presented larger populations, lower death rates, lower socioeconomic index, healthcare infrastructure with fewer beds and physicians, and higher proportion of public healthcare facilities. The correlation coefficients between quality of death certification assessed by missing or unexpected values and the proportion of garbage codes were weak (0.11-0.49), but stronger for municipalities with lower socioeconomic scores. The model that best fitted the data was the random forest classifier (ROC AUC = 0.76; precision-recall AUC = 0.78). This innovative way of assessing the quality of death certification could help quality improvement initiatives to include the correctness of essential fields, in addition to garbage coding or completeness of records, especially in municipalities with lower socioeconomic status where garbage coding and the correctness of core topics appear to be related issues.
Competing Interests: Laboratório Sabin de Análises Clínicas SA, NeuralMed LLC, and Samel Serviços de Assistência Médico Hospitalar LTDA provided support in the form of salaries for some of the authors, but did not have any additional role in the study design, data collection and analysis, decision to publish, or preparation of the manuscript. This does not alter our adherence to PLOS ONE policies on sharing data and materials.
(Copyright: © 2023 Zimeo Morais et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.)
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تواريخ الأحداث: Date Created: 20230831 Date Completed: 20230904 Latest Revision: 20230905
رمز التحديث: 20240628
مُعرف محوري في PubMed: PMC10470916
DOI: 10.1371/journal.pone.0290814
PMID: 37651355
قاعدة البيانات: MEDLINE
الوصف
تدمد:1932-6203
DOI:10.1371/journal.pone.0290814