Maria Fatima Marinho1, Elisabeth Barboza França2, Renato Azeredo Teixeira3, Lenice Harumi Ishitani3, Carolina Cândida da Cunha3, Mayara Rocha Dos Santos3, Ashley Frederes4, Juan José Cortez-Escalante5, Daisy Maria Xavier de Abreu6. 1. Instituto de Estudos Avançados, Universidade de São Paulo - São Paulo (SP), Brasil. 2. Programa de Pós-graduação em Saúde Pública, Universidade Federal de Minas Gerais - Belo Horizonte (MG), Brasil. 3. Grupo de Pesquisas em Epidemiologia e Avaliação em Saúde, Universidade Federal de Minas Gerais - Belo Horizonte (MG), Brasil. 4. Vital Strategies - New York (NY), Estados Unidos. 5. Organização Pan-Americana da Saúde, Organização Mundial da Saúde - Brasília (DF), Brasil. 6. Núcleo de Educação em Saúde Coletiva, Faculdade de Medicina, Universidade Federal de Minas Gerais - Belo Horizonte (MG), Brasil.
Abstract
INTRODUCTION: Knowing the number of deaths and their causes is relevant information for public health managers. However, the cause of death is often classified with codes that are not useful for mortality analysis, called garbage codes (GC). OBJECTIVE: To describe and evaluate the impact of investigation of the underlying cause of poorly classified deaths on death certificates in 2017. METHODS: Based on a standardized protocol, GC deaths from 60 municipalities were investigated, mainly in hospital records and autopsy services. Managers at the state level of the Mortality Information System also developed procedures to improve the classification of causes of death, with the consequent adherence of other municipalities (n = 4022). This made it possible to compare the results of GC research between these two groups of municipalities. RESULTS: In the country, among the 108,826 GC investigated in 2017, 48% were reclassified to specific causes. In the 60 focus municipalities, 58% of the 35,366 investigated deaths from GC were reclassified. After the intervention, the proportion of deaths classified as GC decreased by 11% in the country and 17% in the municipalities. DISCUSSION: The research in hospital records enabled almost half of the deaths from GC investigated to be reclassified. This is the first study to investigate GC in hospital records of more than 100,000 deaths. The 60 cities targeted by the intervention had better results than the other cities. CONCLUSION: The intervention proved to be an appropriate initiative to improve the quality of information on cause of death and should be encouraged.
INTRODUCTION: Knowing the number of deaths and their causes is relevant information for public health managers. However, the cause of death is often classified with codes that are not useful for mortality analysis, called garbage codes (GC). OBJECTIVE: To describe and evaluate the impact of investigation of the underlying cause of poorly classified deaths on death certificates in 2017. METHODS: Based on a standardized protocol, GC deaths from 60 municipalities were investigated, mainly in hospital records and autopsy services. Managers at the state level of the Mortality Information System also developed procedures to improve the classification of causes of death, with the consequent adherence of other municipalities (n = 4022). This made it possible to compare the results of GC research between these two groups of municipalities. RESULTS: In the country, among the 108,826 GC investigated in 2017, 48% were reclassified to specific causes. In the 60 focus municipalities, 58% of the 35,366 investigated deaths from GC were reclassified. After the intervention, the proportion of deaths classified as GC decreased by 11% in the country and 17% in the municipalities. DISCUSSION: The research in hospital records enabled almost half of the deaths from GC investigated to be reclassified. This is the first study to investigate GC in hospital records of more than 100,000 deaths. The 60 cities targeted by the intervention had better results than the other cities. CONCLUSION: The intervention proved to be an appropriate initiative to improve the quality of information on cause of death and should be encouraged.
Authors: Camila de Moraes Paulino; Lorrayne Belotti; Moises Kim Zanotto de Azevedo; Paulo Frazão Journal: Rev Saude Publica Date: 2022-04-08 Impact factor: 2.106