Cargando…
Monitoring progress with national and subnational health goals by integrating verbal autopsy and medically certified cause of death data
INTRODUCTION: The measurement of progress towards many Sustainable Development Goals (SDG) and other health goals requires accurate and timely all-cause and cause of death (COD) data. However, existing guidance to countries to calculate these indicators is inadequate for populations with incomplete...
Autores principales: | , , , , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BMJ Publishing Group
2021
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8169488/ https://www.ncbi.nlm.nih.gov/pubmed/34059494 http://dx.doi.org/10.1136/bmjgh-2021-005387 |
_version_ | 1783702070692413440 |
---|---|
author | Adair, Tim Firth, Sonja Phyo, Tint Pa Pa Bo, Khin Sandar Lopez, Alan D |
author_facet | Adair, Tim Firth, Sonja Phyo, Tint Pa Pa Bo, Khin Sandar Lopez, Alan D |
author_sort | Adair, Tim |
collection | PubMed |
description | INTRODUCTION: The measurement of progress towards many Sustainable Development Goals (SDG) and other health goals requires accurate and timely all-cause and cause of death (COD) data. However, existing guidance to countries to calculate these indicators is inadequate for populations with incomplete death registration and poor-quality COD data. We introduce a replicable method to estimate national and subnational cause-specific mortality rates (and hence many such indicators) where death registration is incomplete by integrating data from Medical Certificates of Cause of Death (MCCOD) for hospital deaths with routine verbal autopsy (VA) for community deaths. METHODS: The integration method calculates population-level cause-specific mortality fractions (CSMFs) from the CSMFs of MCCODs and VAs weighted by estimated deaths in hospitals and the community. Estimated deaths are calculated by applying the empirical completeness method to incomplete death registration/reporting. The resultant cause-specific mortality rates are used to estimate SDG Indicator 23: mortality between ages 30 and 70 years from cardiovascular diseases, cancers, chronic respiratory diseases and diabetes. We demonstrate the method using nationally representative data in Myanmar, comprising over 42 000 VAs and 7600 MCCODs. RESULTS: In Myanmar in 2019, 89% of deaths were estimated to occur in the community. VAs comprised an estimated 70% of community deaths. Both the proportion of deaths in the community and CSMFs for the four causes increased with older age. We estimated that the probability of dying from any of the four causes between 30 and 70 years was 0.265 for men and 0.216 for women. This indicator is 50% higher if based on CSMFs from the integration of data sources than on MCCOD data from hospitals. CONCLUSION: This integration method facilitates country authorities to use their data to monitor progress with national and subnational health goals, rather than rely on estimates made by external organisations. The method is particularly relevant given the increasing application of routine VA in country Civil Registration and Vital Statistics systems. |
format | Online Article Text |
id | pubmed-8169488 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | BMJ Publishing Group |
record_format | MEDLINE/PubMed |
spelling | pubmed-81694882021-06-17 Monitoring progress with national and subnational health goals by integrating verbal autopsy and medically certified cause of death data Adair, Tim Firth, Sonja Phyo, Tint Pa Pa Bo, Khin Sandar Lopez, Alan D BMJ Glob Health Original Research INTRODUCTION: The measurement of progress towards many Sustainable Development Goals (SDG) and other health goals requires accurate and timely all-cause and cause of death (COD) data. However, existing guidance to countries to calculate these indicators is inadequate for populations with incomplete death registration and poor-quality COD data. We introduce a replicable method to estimate national and subnational cause-specific mortality rates (and hence many such indicators) where death registration is incomplete by integrating data from Medical Certificates of Cause of Death (MCCOD) for hospital deaths with routine verbal autopsy (VA) for community deaths. METHODS: The integration method calculates population-level cause-specific mortality fractions (CSMFs) from the CSMFs of MCCODs and VAs weighted by estimated deaths in hospitals and the community. Estimated deaths are calculated by applying the empirical completeness method to incomplete death registration/reporting. The resultant cause-specific mortality rates are used to estimate SDG Indicator 23: mortality between ages 30 and 70 years from cardiovascular diseases, cancers, chronic respiratory diseases and diabetes. We demonstrate the method using nationally representative data in Myanmar, comprising over 42 000 VAs and 7600 MCCODs. RESULTS: In Myanmar in 2019, 89% of deaths were estimated to occur in the community. VAs comprised an estimated 70% of community deaths. Both the proportion of deaths in the community and CSMFs for the four causes increased with older age. We estimated that the probability of dying from any of the four causes between 30 and 70 years was 0.265 for men and 0.216 for women. This indicator is 50% higher if based on CSMFs from the integration of data sources than on MCCOD data from hospitals. CONCLUSION: This integration method facilitates country authorities to use their data to monitor progress with national and subnational health goals, rather than rely on estimates made by external organisations. The method is particularly relevant given the increasing application of routine VA in country Civil Registration and Vital Statistics systems. BMJ Publishing Group 2021-05-31 /pmc/articles/PMC8169488/ /pubmed/34059494 http://dx.doi.org/10.1136/bmjgh-2021-005387 Text en © Author(s) (or their employer(s)) 2021. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ. https://creativecommons.org/licenses/by-nc/4.0/This is an open access article distributed in accordance with the Creative Commons Attribution Non Commercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited, appropriate credit is given, any changes made indicated, and the use is non-commercial. See: http://creativecommons.org/licenses/by-nc/4.0/ (https://creativecommons.org/licenses/by-nc/4.0/) . |
spellingShingle | Original Research Adair, Tim Firth, Sonja Phyo, Tint Pa Pa Bo, Khin Sandar Lopez, Alan D Monitoring progress with national and subnational health goals by integrating verbal autopsy and medically certified cause of death data |
title | Monitoring progress with national and subnational health goals by integrating verbal autopsy and medically certified cause of death data |
title_full | Monitoring progress with national and subnational health goals by integrating verbal autopsy and medically certified cause of death data |
title_fullStr | Monitoring progress with national and subnational health goals by integrating verbal autopsy and medically certified cause of death data |
title_full_unstemmed | Monitoring progress with national and subnational health goals by integrating verbal autopsy and medically certified cause of death data |
title_short | Monitoring progress with national and subnational health goals by integrating verbal autopsy and medically certified cause of death data |
title_sort | monitoring progress with national and subnational health goals by integrating verbal autopsy and medically certified cause of death data |
topic | Original Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8169488/ https://www.ncbi.nlm.nih.gov/pubmed/34059494 http://dx.doi.org/10.1136/bmjgh-2021-005387 |
work_keys_str_mv | AT adairtim monitoringprogresswithnationalandsubnationalhealthgoalsbyintegratingverbalautopsyandmedicallycertifiedcauseofdeathdata AT firthsonja monitoringprogresswithnationalandsubnationalhealthgoalsbyintegratingverbalautopsyandmedicallycertifiedcauseofdeathdata AT phyotintpapa monitoringprogresswithnationalandsubnationalhealthgoalsbyintegratingverbalautopsyandmedicallycertifiedcauseofdeathdata AT bokhinsandar monitoringprogresswithnationalandsubnationalhealthgoalsbyintegratingverbalautopsyandmedicallycertifiedcauseofdeathdata AT lopezaland monitoringprogresswithnationalandsubnationalhealthgoalsbyintegratingverbalautopsyandmedicallycertifiedcauseofdeathdata |