Cargando…

Automated verbal autopsy: from research to routine use in civil registration and vital statistics systems

BACKGROUND: The majority of low- and middle-income countries (LMICs) do not have adequate civil registration and vital statistics (CRVS) systems to properly support health policy formulation. Verbal autopsy (VA), long used in research, can provide useful information on the cause of death (COD) in po...

Descripción completa

Detalles Bibliográficos
Autores principales: Hazard, Riley H., Buddhika, Mahesh P. K., Hart, John D., Chowdhury, Hafizur R., Firth, Sonja, Joshi, Rohina, Avelino, Ferchito, Segarra, Agnes, Sarmiento, Deborah Carmina, Azad, Abdul Kalam, Ashrafi, Shah Ali Akbar, Bo, Khin Sandar, Kwa, Violoa, Lopez, Alan D.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7061477/
https://www.ncbi.nlm.nih.gov/pubmed/32146903
http://dx.doi.org/10.1186/s12916-020-01520-1
_version_ 1783504395836588032
author Hazard, Riley H.
Buddhika, Mahesh P. K.
Hart, John D.
Chowdhury, Hafizur R.
Firth, Sonja
Joshi, Rohina
Avelino, Ferchito
Segarra, Agnes
Sarmiento, Deborah Carmina
Azad, Abdul Kalam
Ashrafi, Shah Ali Akbar
Bo, Khin Sandar
Kwa, Violoa
Lopez, Alan D.
author_facet Hazard, Riley H.
Buddhika, Mahesh P. K.
Hart, John D.
Chowdhury, Hafizur R.
Firth, Sonja
Joshi, Rohina
Avelino, Ferchito
Segarra, Agnes
Sarmiento, Deborah Carmina
Azad, Abdul Kalam
Ashrafi, Shah Ali Akbar
Bo, Khin Sandar
Kwa, Violoa
Lopez, Alan D.
author_sort Hazard, Riley H.
collection PubMed
description BACKGROUND: The majority of low- and middle-income countries (LMICs) do not have adequate civil registration and vital statistics (CRVS) systems to properly support health policy formulation. Verbal autopsy (VA), long used in research, can provide useful information on the cause of death (COD) in populations where physicians are not available to complete medical certificates of COD. Here, we report on the application of the SmartVA tool for the collection and analysis of data in several countries as part of routine CRVS activities. METHODS: Data from VA interviews conducted in 4 of 12 countries supported by the Bloomberg Philanthropies Data for Health (D4H) Initiative, and at different stages of health statistical development, were analysed and assessed for plausibility: Myanmar, Papua New Guinea (PNG), Bangladesh and the Philippines. Analyses by age- and cause-specific mortality fractions were compared to the Global Burden of Disease (GBD) study data by country. VA interviews were analysed using SmartVA-Analyze-automated software that was designed for use in CRVS systems. The method in the Philippines differed from the other sites in that the VA output was used as a decision support tool for health officers. RESULTS: Country strategies for VA implementation are described in detail. Comparisons between VA data and country GBD estimates by age and cause revealed generally similar patterns and distributions. The main discrepancy was higher infectious disease mortality and lower non-communicable disease mortality at the PNG VA sites, compared to the GBD country models, which critical appraisal suggests may highlight real differences rather than implausible VA results. CONCLUSION: Automated VA is the only feasible method for generating COD data for many populations. The results of implementation in four countries, reported here under the D4H Initiative, confirm that these methods are acceptable for wide-scale implementation and can produce reliable COD information on community deaths for which little was previously known.
format Online
Article
Text
id pubmed-7061477
institution National Center for Biotechnology Information
language English
publishDate 2020
publisher BioMed Central
record_format MEDLINE/PubMed
spelling pubmed-70614772020-03-12 Automated verbal autopsy: from research to routine use in civil registration and vital statistics systems Hazard, Riley H. Buddhika, Mahesh P. K. Hart, John D. Chowdhury, Hafizur R. Firth, Sonja Joshi, Rohina Avelino, Ferchito Segarra, Agnes Sarmiento, Deborah Carmina Azad, Abdul Kalam Ashrafi, Shah Ali Akbar Bo, Khin Sandar Kwa, Violoa Lopez, Alan D. BMC Med Research Article BACKGROUND: The majority of low- and middle-income countries (LMICs) do not have adequate civil registration and vital statistics (CRVS) systems to properly support health policy formulation. Verbal autopsy (VA), long used in research, can provide useful information on the cause of death (COD) in populations where physicians are not available to complete medical certificates of COD. Here, we report on the application of the SmartVA tool for the collection and analysis of data in several countries as part of routine CRVS activities. METHODS: Data from VA interviews conducted in 4 of 12 countries supported by the Bloomberg Philanthropies Data for Health (D4H) Initiative, and at different stages of health statistical development, were analysed and assessed for plausibility: Myanmar, Papua New Guinea (PNG), Bangladesh and the Philippines. Analyses by age- and cause-specific mortality fractions were compared to the Global Burden of Disease (GBD) study data by country. VA interviews were analysed using SmartVA-Analyze-automated software that was designed for use in CRVS systems. The method in the Philippines differed from the other sites in that the VA output was used as a decision support tool for health officers. RESULTS: Country strategies for VA implementation are described in detail. Comparisons between VA data and country GBD estimates by age and cause revealed generally similar patterns and distributions. The main discrepancy was higher infectious disease mortality and lower non-communicable disease mortality at the PNG VA sites, compared to the GBD country models, which critical appraisal suggests may highlight real differences rather than implausible VA results. CONCLUSION: Automated VA is the only feasible method for generating COD data for many populations. The results of implementation in four countries, reported here under the D4H Initiative, confirm that these methods are acceptable for wide-scale implementation and can produce reliable COD information on community deaths for which little was previously known. BioMed Central 2020-03-09 /pmc/articles/PMC7061477/ /pubmed/32146903 http://dx.doi.org/10.1186/s12916-020-01520-1 Text en © The Author(s) 2020 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.
spellingShingle Research Article
Hazard, Riley H.
Buddhika, Mahesh P. K.
Hart, John D.
Chowdhury, Hafizur R.
Firth, Sonja
Joshi, Rohina
Avelino, Ferchito
Segarra, Agnes
Sarmiento, Deborah Carmina
Azad, Abdul Kalam
Ashrafi, Shah Ali Akbar
Bo, Khin Sandar
Kwa, Violoa
Lopez, Alan D.
Automated verbal autopsy: from research to routine use in civil registration and vital statistics systems
title Automated verbal autopsy: from research to routine use in civil registration and vital statistics systems
title_full Automated verbal autopsy: from research to routine use in civil registration and vital statistics systems
title_fullStr Automated verbal autopsy: from research to routine use in civil registration and vital statistics systems
title_full_unstemmed Automated verbal autopsy: from research to routine use in civil registration and vital statistics systems
title_short Automated verbal autopsy: from research to routine use in civil registration and vital statistics systems
title_sort automated verbal autopsy: from research to routine use in civil registration and vital statistics systems
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7061477/
https://www.ncbi.nlm.nih.gov/pubmed/32146903
http://dx.doi.org/10.1186/s12916-020-01520-1
work_keys_str_mv AT hazardrileyh automatedverbalautopsyfromresearchtoroutineuseincivilregistrationandvitalstatisticssystems
AT buddhikamaheshpk automatedverbalautopsyfromresearchtoroutineuseincivilregistrationandvitalstatisticssystems
AT hartjohnd automatedverbalautopsyfromresearchtoroutineuseincivilregistrationandvitalstatisticssystems
AT chowdhuryhafizurr automatedverbalautopsyfromresearchtoroutineuseincivilregistrationandvitalstatisticssystems
AT firthsonja automatedverbalautopsyfromresearchtoroutineuseincivilregistrationandvitalstatisticssystems
AT joshirohina automatedverbalautopsyfromresearchtoroutineuseincivilregistrationandvitalstatisticssystems
AT avelinoferchito automatedverbalautopsyfromresearchtoroutineuseincivilregistrationandvitalstatisticssystems
AT segarraagnes automatedverbalautopsyfromresearchtoroutineuseincivilregistrationandvitalstatisticssystems
AT sarmientodeborahcarmina automatedverbalautopsyfromresearchtoroutineuseincivilregistrationandvitalstatisticssystems
AT azadabdulkalam automatedverbalautopsyfromresearchtoroutineuseincivilregistrationandvitalstatisticssystems
AT ashrafishahaliakbar automatedverbalautopsyfromresearchtoroutineuseincivilregistrationandvitalstatisticssystems
AT bokhinsandar automatedverbalautopsyfromresearchtoroutineuseincivilregistrationandvitalstatisticssystems
AT kwavioloa automatedverbalautopsyfromresearchtoroutineuseincivilregistrationandvitalstatisticssystems
AT lopezaland automatedverbalautopsyfromresearchtoroutineuseincivilregistrationandvitalstatisticssystems