Background -Coronary heart disease(CHD) represents the largest share of cardiovascular disease in the United States, but there are conspicuous discrepancies between CHD and total cardiovascular death rates across the states, possibly due in part to variations in physician assignment of causes of death. Our aim was to identify exogenous individual-and community-level predictors of cause-of-death assignment and variability and to use these predictors to improve the comparability of CHD mortality estimates across states. Methods and Results -We performed a multinomial logistic regression analysis to estimate the effect of individual-and community-level factors on the likelihood of a death being certified as 1 of 3 ill-defined clusters(general atherosclerosis and unspecified heart disease, heart failure, and cardiac arrest) relative to being certified as CHD. The individual-level variables were the decedent’s race, sex, age, education, and place of death; the community-level variable was the number of cardiologists per capita. We used the model to estimate state-level CHD rates that are standardized with regard to the levels of individual-and community-level determinants of cause-of-death assignment. Decedents who died in hospitals and in counties with more cardiologists per capita were more likely to be assigned to CHD than to the ill-defined categories, as were white males relative to other race-sex combinations. Adjustment for these factors resulted in substantially improved correlation between death rates for CHD and all cardiovascular causes. Increases in CHD death rates across states after adjustment for external predictors of cause-of-death assignment ranged from 2%(North Dakota) to 72%(Washington,DC); NewYork had a decrease(1%) in CHD death rates after adjustment. Nationally, CHD death rates increased 10%for males and 15%for females. The total number of deaths in 2001 attributed to CHD in patients over 30 years of age rose from 433 625 to 489 836 after adjustment. Conclusions -Greater presence of medical knowledge at the time of death, reflected by place of death and cardiologists per capita, reduces the use of the ill-defined cardiovascular clusters. Racial and gender effects on CHD assignment may reflect disparities in access to care and quality of care. By adjusting for differentials in these parameters, a comparable and consistent set of CHD mortality estimates can be created. The role of the exogenous predictors in validity and comparability of cause-of-death statistics should be confirmed in carefully designed validation autopsy studies. Background -Coronary heart disease (CHD) represents the largest share of cardiovascular disease in the United States, but there are conspicuous discrepancies between CHD and total cardiovascular death rates across the states, possibly due in part to variations in physician assignment of causes of death. Our aim was to identify exogenous individual-and community-level predictors of cause-of-death assignment and variability and to use these predictors to improve the comparability of CHD mortality estimates across states. Methods and Results -We performed a multinomial logistic regression analysis to estimate the effect of individual-and community-level factors on the likelihood of a death is certified as 1 of 3 ill-defined clusters (general atherosclerosis and unspecified heart disease, heart failure, and cardiac arrest) relative to being certified as CHD. The individual-level variables were the decedent’s race, sex, age, education, and place of death; the community-level variable was the number of cardiologists per capita. We used the model to estimate state-level CHD rates that are standardized with regard to the levels of individual-and community-level determinants of cause-of-death assignment. Decedents who died in hospitals and in counties with more cardiologists per capita were more likely to be assigned to CHD than to the ill-defined combinations, as were white males relative to other race-sex combinations. Adjustment for these factors resulted in substantially improved correlation between death rates for CHD and all cardiovascular causes. Increases in CHD death rates across states after adjustment for external predictors of cause-of-death assignment ranged from 2% (North Dakota) to 72% (Washington, DC); New York had a decrease (1%) in CHD death rates after adjustment. Nationally, CHD death rates increased 10% for males and 15% for females. The total number of deaths in 2001 attributed to CHD in patients over 30 years of age rose from 433 625 to 489 836 after adjustm ent. Conclusions -Greater presence of medical knowledge at the time of death, reflected by place of death and cardiologists per capita, reduces the use of the ill-defined cardiovascular clusters. Racial and gender effects on CHD assignment may reflect disparities in access to care and quality of care. By adjusting for differentials in these parameters, a comparable and consistent set of CHD proponents can be created. The role of the exogenous predictors in validity and comparability of cause-of-death statistics should be confirmed in carefully designed validation autopsy studies.