Are cause of death data fit for purpose? evidence from 20 countries at different levels of socio-economic development.


Journal

PloS one
ISSN: 1932-6203
Titre abrégé: PLoS One
Pays: United States
ID NLM: 101285081

Informations de publication

Date de publication:
2020
Historique:
received: 20 04 2020
accepted: 28 07 2020
entrez: 25 8 2020
pubmed: 25 8 2020
medline: 9 10 2020
Statut: epublish

Résumé

Many countries have used the new ANACONDA (Analysis of Causes of National Death for Action) tool to assess the quality of their cause of death data (COD), but no cross-country analysis has been done to verify how different or similar patterns of diagnostic errors and data quality are in countries or how they are related to the local cultural or epidemiological environment or to levels of development. Our objective is to measure whether the usability of COD data and the patterns of unusable codes are related to a country's level of socio-economic development. We have assessed the quality of 20 national COD datasets from the WHO Mortality Database by assessing their completeness of COD reporting and the extent, pattern and severity of garbage codes, i.e. codes that provide little or no information about the true underlying COD. Garbage codes were classified into four groups based on the severity of the error in the code. The Vital Statistics Performance Index for Quality (VSPI(Q)) was used to measure the overall quality of each country's mortality surveillance system. The proportion of 'garbage codes' varied from 7 to 66% across the 20 countries. Countries with a high SDI generally had a lower proportion of high impact (i.e. more severe) garbage codes than countries with low SDI. While the magnitude and pattern of garbage codes differed among countries, the specific codes commonly used did not. There is an inverse relationship between a country's socio-demographic development and the overall quality of its cause of death data, but with important exceptions. In particular, some low SDI countries have vital statistics systems that are as reliable as more developed countries. However, in low-income countries, where most people die at home, the proportion of unusable codes often exceeds 50%, implying that half of all cause-specific mortality data collected is of little or no use in guiding public policy. Moreover, the cause of death pattern identified from the data is likely to seriously under-represent the true extent of the leading causes of death in the population, with very significant consequences for health priority setting. Garbage codes are prevalent at all ages, contrary to expectations. Further research into effective strategies deployed in these countries to improve data quality can inform efforts elsewhere to improve COD reporting systems.

Sections du résumé

BACKGROUND AND OBJECTIVE
Many countries have used the new ANACONDA (Analysis of Causes of National Death for Action) tool to assess the quality of their cause of death data (COD), but no cross-country analysis has been done to verify how different or similar patterns of diagnostic errors and data quality are in countries or how they are related to the local cultural or epidemiological environment or to levels of development. Our objective is to measure whether the usability of COD data and the patterns of unusable codes are related to a country's level of socio-economic development.
METHODS
We have assessed the quality of 20 national COD datasets from the WHO Mortality Database by assessing their completeness of COD reporting and the extent, pattern and severity of garbage codes, i.e. codes that provide little or no information about the true underlying COD. Garbage codes were classified into four groups based on the severity of the error in the code. The Vital Statistics Performance Index for Quality (VSPI(Q)) was used to measure the overall quality of each country's mortality surveillance system.
FINDINGS
The proportion of 'garbage codes' varied from 7 to 66% across the 20 countries. Countries with a high SDI generally had a lower proportion of high impact (i.e. more severe) garbage codes than countries with low SDI. While the magnitude and pattern of garbage codes differed among countries, the specific codes commonly used did not.
CONCLUSIONS
There is an inverse relationship between a country's socio-demographic development and the overall quality of its cause of death data, but with important exceptions. In particular, some low SDI countries have vital statistics systems that are as reliable as more developed countries. However, in low-income countries, where most people die at home, the proportion of unusable codes often exceeds 50%, implying that half of all cause-specific mortality data collected is of little or no use in guiding public policy. Moreover, the cause of death pattern identified from the data is likely to seriously under-represent the true extent of the leading causes of death in the population, with very significant consequences for health priority setting. Garbage codes are prevalent at all ages, contrary to expectations. Further research into effective strategies deployed in these countries to improve data quality can inform efforts elsewhere to improve COD reporting systems.

Identifiants

pubmed: 32834006
doi: 10.1371/journal.pone.0237539
pii: PONE-D-20-11375
pmc: PMC7446871
doi:

Types de publication

Journal Article Research Support, Non-U.S. Gov't

Langues

eng

Sous-ensembles de citation

IM

Pagination

e0237539

Déclaration de conflit d'intérêts

The authors have declared that no competing interests exist.

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Auteurs

Kim Moesgaard Iburg (KM)

Institute of Public Health, Aarhus University, Aarhus, Denmark.

Lene Mikkelsen (L)

Global Burden of Disease Group, University of Melbourne, Melbourne, Australia.

Tim Adair (T)

Global Burden of Disease Group, University of Melbourne, Melbourne, Australia.

Alan D Lopez (AD)

Global Burden of Disease Group, University of Melbourne, Melbourne, Australia.

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