Redistribution of heart failure deaths using two methods: linkage of hospital records with death certificate data and multiple causes of death data.


Journal

Cadernos de saude publica
ISSN: 1678-4464
Titre abrégé: Cad Saude Publica
Pays: Brazil
ID NLM: 8901573

Informations de publication

Date de publication:
2019
Historique:
received: 14 08 2017
accepted: 30 11 2018
entrez: 6 6 2019
pubmed: 6 6 2019
medline: 10 4 2020
Statut: ppublish

Résumé

Heart failure is considered a garbage code when assigned as the underlying cause of death. Reassigning garbage codes to plausible causes reduces bias and increases comparability of mortality data. Two redistribution methods were applied to Brazilian data, from 2008 to 2012, for decedents aged 55 years and older. In the multiple causes of death method, heart failure deaths were redistributed based on the proportion of underlying causes found in matched deaths that had heart failure listed as an intermediate cause. In the hospitalization data method, heart failure deaths were redistributed based on data from the decedents' corresponding hospitalization record. There were 123,269 (3.7%) heart failure deaths. The method with multiple causes of death redistributed 25.3% to hypertensive heart and kidney diseases, 22.6% to coronary heart diseases and 9.6% to diabetes. The total of 41,324 heart failure deaths were linked to hospitalization records. Heart failure was listed as the principal diagnosis in 45.8% of the corresponding hospitalization records. For those, no redistribution occurred. For the remaining ones, the hospitalization data method redistributed 21.2% to a group with other (non-cardiac) diseases, 6.5% to lower respiratory infections and 9.3% to other garbage codes. Heart failure is a frequently used garbage code in Brazil. We used two redistribution methods, which were straightforwardly applied but led to different results. These methods need to be validated, which can be done in the wake of a recent national study that will investigate a big sample of hospital deaths with garbage codes listed as underlying causes.

Identifiants

pubmed: 31166417
pii: S0102-311X2019000605010
doi: 10.1590/0102-311x00135617
pii:
doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Pagination

e00135617

Auteurs

Ana Luiza Bierrenbach (AL)

Instituto Sírio-Libanês de Ensino e Pesquisa, São Paulo, Brasil.

Gizelton Pereira Alencar (GP)

Escola de Saúde Pública, Universidade de São Paulo, São Paulo, Brazil.

Cátia Martinez (C)

Centro de Informações Estratégicas em Saúde, Secretaria de Saúde de São Paulo, São Paulo, Brazil.

Maria de Fátima Marinho de Souza (MFM)

Secretaria de Vigilância em Saúde, Ministério da Saúde, Brasília, Brazil.

Gabriela Moreira Policena (GM)

Instituto de Patologia Tropical e Saúde Pública, Universidade Federal de Goiás, Goiânia, Brazil.

Elisabeth Barboza França (EB)

Faculdade de Medicina, Universidade de Minas Gerais, Belo Horizonte, Brazil.

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Classifications MeSH