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Published in: Population Health Metrics 1/2010

Open Access 01-12-2010 | Research

Deaths from heart failure: using coarsened exact matching to correct cause-of-death statistics

Authors: Gretchen A Stevens, Gary King, Kenji Shibuya

Published in: Population Health Metrics | Issue 1/2010

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Abstract

Background

Incomplete information on death certificates makes recorded cause-of-death data less useful for public health monitoring and planning. Certifying physicians sometimes list only the mode of death without indicating the underlying disease or diseases that led to the death. Inconsistent cause-of-death assignment among cardiovascular causes of death is of particular concern. This can prevent valid epidemiologic comparisons across countries and over time.

Methods

We propose that coarsened exact matching be used to infer the underlying causes of death where only the mode of death is known. We focus on the case of heart failure in US, Mexican, and Brazilian death records.

Results

Redistribution algorithms derived using this method assign the largest proportion of heart failure deaths to ischemic heart disease in all three countries (53%, 26%, and 22% respectively), with larger proportions assigned to hypertensive heart disease and diabetes in Mexico and Brazil (16% and 23% vs. 7% for hypertensive heart disease, and 13% and 9% vs. 6% for diabetes). Reassigning these heart failure deaths increases the US ischemic heart disease mortality rate by 6%.

Conclusions

The frequency with which physicians list heart failure in the causal chain for various underlying causes of death allows for inference about how physicians use heart failure on the death certificate in different settings. This easy-to-use method has the potential to reduce bias and increase comparability in cause-of-death data, thereby improving the public health utility of death records.
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Metadata
Title
Deaths from heart failure: using coarsened exact matching to correct cause-of-death statistics
Authors
Gretchen A Stevens
Gary King
Kenji Shibuya
Publication date
01-12-2010
Publisher
BioMed Central
Published in
Population Health Metrics / Issue 1/2010
Electronic ISSN: 1478-7954
DOI
https://doi.org/10.1186/1478-7954-8-6

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