Trends in AMI in Young Patients by Sex and Race
Trends in AMI in Young Patients by Sex and Race
We obtained data from the Agency for Healthcare Research and Quality's Healthcare Cost and Utilization Project (HCUP) NIS files between 2001 and 2010. It is the largest all-payer inpatient database publicly available in the United States, comprising discharge data from more than 1,000 hospitals across 44 states. The database was designed to approximate a 20% stratified sample of U.S. community hospitals, representing more than 95% of the U.S. population (including urban and rural hospitals across all geographic locations). Statistical sampling weights provided by the NIS allow extrapolation to calculate expected hospitalization rates within the United States. The NIS includes all claims from each selected hospital regardless of payer or insurance status, because it is derived from state-mandated hospital discharge reports. We classified a hospital admission as AMI if the principal discharge diagnosis code was International Classification of Diseases-Ninth Revision-Clinical Modification 410.xx, excluding cases for which the last digit was 2 (410.x2), which does not indicate an acute event.
From an initial sample of all discharges in the HCUP NIS from 2001 through 2010 (n = 79,171,880), we excluded the following hospitalizations: those with missing data on patient age, sex, length of stay (LOS), or in-hospital death (n = 278,653); discharges in which patients were <30 or >54 years of age (n = 58,687,675); discharges in which patients were admitted and discharged alive the same day (n = 474,676), as they may not reflect diagnoses of AMI; and discharges in which patients were admitted from other hospitals (n = 419,817) to avoid duplication of records, leaving a cohort of 19,311,059 discharges. Secondary analyses stratified by age, race, and sex subgroups were conducted in a subset of patients hospitalized in 21 states that reported complete data on patient race during this time period, leaving a cohort of 12,059,714 discharges. These states represent approximately 60% of the U.S. population and include approximately 60% of Caucasians and 60% of African Americans of the national population, which may not be representative of the entire country. However, an Agency for Healthcare Research and Quality study comparing the HCUP NIS database with the National Hospital Discharge Survey database showed that there were no significant differences in the discharge estimates for the white and black subgroups. Additionally, different states do not compare uniformly for inclusion criteria for the "other race" subgroup. We did not include the "other races" in our analyses, because they include many missing values and are very heterogeneous for comparison.
We examined subgroups of age by 5-year categories (30 to 34, 35 to 39, 40 to 44, 45 to 49, and 50 to 54 years of age), sex (women and men), and race (white and black). We identified clinical comorbidities using International Classification of Diseases-Ninth Revision-Clinical Modification secondary diagnosis codes and classified them according to hierarchical condition categories, similar to those used by the Centers for Medicare & Medicaid Services for calculating their 30-day AMI mortality measure.
We used survey analysis methods that used hospital-level discharge weights provided by the NIS to estimate the number of AMI hospitalizations on a national level. We examined AMI hospitalization rates among subgroups of age, sex, and ethnicity for each year between 2001 and 2010 and reported them as the rates per 100,000 persons. We assessed the annual trend over time in AMI hospitalization rates using Poisson regression that included a variable representing the time of the year.
We evaluated in-hospital mortality and LOS among AMI admissions for patients in subgroups of age (30 to 34, 35 to 39, 40 to 44, 45 to 49, and 50 to 54 years of age), sex (women and men), and race (white and black). We also examined trends in these outcomes stratified by age, sex, and race. We assessed annual changes in in-hospital mortality rate and mean LOS using linear regression.
All p values were 2-sided, with a significance threshold of p < 0.05. Statistical analyses were performed using SAS version 9.2 (SAS Institute Inc., Cary, North Carolina). Yale University's Institutional Review Board approved the study protocol.
Methods
Data Sources and Coding
We obtained data from the Agency for Healthcare Research and Quality's Healthcare Cost and Utilization Project (HCUP) NIS files between 2001 and 2010. It is the largest all-payer inpatient database publicly available in the United States, comprising discharge data from more than 1,000 hospitals across 44 states. The database was designed to approximate a 20% stratified sample of U.S. community hospitals, representing more than 95% of the U.S. population (including urban and rural hospitals across all geographic locations). Statistical sampling weights provided by the NIS allow extrapolation to calculate expected hospitalization rates within the United States. The NIS includes all claims from each selected hospital regardless of payer or insurance status, because it is derived from state-mandated hospital discharge reports. We classified a hospital admission as AMI if the principal discharge diagnosis code was International Classification of Diseases-Ninth Revision-Clinical Modification 410.xx, excluding cases for which the last digit was 2 (410.x2), which does not indicate an acute event.
Study Cohort and Patient Characteristics
From an initial sample of all discharges in the HCUP NIS from 2001 through 2010 (n = 79,171,880), we excluded the following hospitalizations: those with missing data on patient age, sex, length of stay (LOS), or in-hospital death (n = 278,653); discharges in which patients were <30 or >54 years of age (n = 58,687,675); discharges in which patients were admitted and discharged alive the same day (n = 474,676), as they may not reflect diagnoses of AMI; and discharges in which patients were admitted from other hospitals (n = 419,817) to avoid duplication of records, leaving a cohort of 19,311,059 discharges. Secondary analyses stratified by age, race, and sex subgroups were conducted in a subset of patients hospitalized in 21 states that reported complete data on patient race during this time period, leaving a cohort of 12,059,714 discharges. These states represent approximately 60% of the U.S. population and include approximately 60% of Caucasians and 60% of African Americans of the national population, which may not be representative of the entire country. However, an Agency for Healthcare Research and Quality study comparing the HCUP NIS database with the National Hospital Discharge Survey database showed that there were no significant differences in the discharge estimates for the white and black subgroups. Additionally, different states do not compare uniformly for inclusion criteria for the "other race" subgroup. We did not include the "other races" in our analyses, because they include many missing values and are very heterogeneous for comparison.
We examined subgroups of age by 5-year categories (30 to 34, 35 to 39, 40 to 44, 45 to 49, and 50 to 54 years of age), sex (women and men), and race (white and black). We identified clinical comorbidities using International Classification of Diseases-Ninth Revision-Clinical Modification secondary diagnosis codes and classified them according to hierarchical condition categories, similar to those used by the Centers for Medicare & Medicaid Services for calculating their 30-day AMI mortality measure.
Statistical Analyses
We used survey analysis methods that used hospital-level discharge weights provided by the NIS to estimate the number of AMI hospitalizations on a national level. We examined AMI hospitalization rates among subgroups of age, sex, and ethnicity for each year between 2001 and 2010 and reported them as the rates per 100,000 persons. We assessed the annual trend over time in AMI hospitalization rates using Poisson regression that included a variable representing the time of the year.
We evaluated in-hospital mortality and LOS among AMI admissions for patients in subgroups of age (30 to 34, 35 to 39, 40 to 44, 45 to 49, and 50 to 54 years of age), sex (women and men), and race (white and black). We also examined trends in these outcomes stratified by age, sex, and race. We assessed annual changes in in-hospital mortality rate and mean LOS using linear regression.
All p values were 2-sided, with a significance threshold of p < 0.05. Statistical analyses were performed using SAS version 9.2 (SAS Institute Inc., Cary, North Carolina). Yale University's Institutional Review Board approved the study protocol.
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