摘要：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. 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. 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%. 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.
关键词：Heart Failure ; Death Certificate ; Multinomial Logistic Regression ; Average Relative Error ; Hypertensive Heart Disease
