@article {SteKinShi,
	title = {Deaths From Heart Failure: Using Coarsened Exact Matching to Correct Cause of Death Statistics},
	journal = {Population Health Metrics},
	volume = {8},
	number = {6},
	year = {2010},
	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 (and in particular, list heart failure) without indicating the underlying disease(s) that gave rise to the death. This can prevent valid epidemiologic comparisons across countries and over time. Methods and Results: 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 U.S., Mexican and Brazilian death records. 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\%), 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 US ischemic heart disease mortality rates 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. Key Words: vital statistics, heart failure, population health, mortality, epidemiology},
	author = {Gretchen Stevens and Gary King and Kenji Shibuya}
}
