Estimates of the numbers and rates of acute decompensated heart failure (ADHF) hospitalization are central to understanding health-care utilization and efforts to improve patient care. We comprehensively estimated the frequency, rate, and trends of ADHF hospitalization in the United States. Based on Atherosclerosis Risk in Communities (ARIC) Study surveillance adjudicating 12,450 eligible hospitalizations during 2005-2010, we developed prediction models for ADHF separately for 3 International Classification of Diseases, Ninth Revision, Clinical Modification (ICD-9-CM) code 428 discharge diagnosis groups: 428 primary, 428 nonprimary, or 428 absent. We applied the models to data from the National Inpatient Sample (11.5 million hospitalizations of persons aged ≥55 years with eligible ICD-9-CM codes), an all-payer, 20% probability sample of US community hospitals. The average estimated number of ADHF hospitalizations per year was 1.76 million (428 primary, 0.80 million; 428 nonprimary, 0.83 million; 428 absent, 0.13 million). During 1998-2004, the rate of ADHF hospitalization increased by 2.0%/year (95% confidence interval (CI): 1.8, 2.5) versus a 1.4%/year (95% CI: 0.8, 2.1) increase in code 428 primary hospitalizations (P < 0.001). In contrast, during 2005-2011, numbers of ADHF hospitalizations were stable (-0.5%/year; 95% CI: -1.4, 0.3), while the numbers of 428-primary hospitalizations decreased by -1.5%/year (95% CI: -2.2, -0.8) (P for contrast = 0.03). In conclusion, the estimated number of hospitalizations with ADHF is approximately 2 times higher than the number of hospitalizations with ICD-9-CM code 428 in the primary position. The trend increased more steeply prior to 2005 and was relatively flat after 2005.
Keywords: International Classification of Diseases codes; United States; acute decompensated heart failure; adjudicated heart failure; community surveillance; hospitalizations; national inpatient sample; secular trends.
© The Author 2016. Published by Oxford University Press on behalf of the Johns Hopkins Bloomberg School of Public Health. All rights reserved. For permissions, please e-mail: firstname.lastname@example.org.