The US hospital-acquired condition reduction program: A linear and logistic regression analysis of domains and penalty status

Abstract

ABSTRACT Background Section 3008 of the 2010 Patient Protection and Affordable Care Act established the Hospital-Acquired Condition Reduction Program (HACRP). Objective The objective of this study is to reasonably decipher those factors that make a hospital vulnerable to be positioned in the bottom quartile of all reporting hospitals; and therefore, be partially reimbursed. Methods Data was sourced from CMS QualityNet public use data files and the American Hospital Directory® website. Linear and logistic regression models were used to analyze continuous and categorical dependent variables, respectively. Results For a one unit increase in inpatient days and the length of stay, the Total HACRP score increased by 0.02 (95% CI: 0.01 0.03 P = .00), and 0.04 (95% CI: −0.02 −0.06 P = .00) units, respectively, when all other variables were held constant. The odds of incurring penalty was 2% less likely (odds ratio = 98 95% CI: 0.97 0.99 P = .00) if the hospital had lesser as opposed to having a greater number of Total Discharges. The odds of incurring penalty was 3% more likely (odds ratio = 1.03 95% CI: 1.02 1.04 P = .00) if the hospital had more as opposed to less Inpatient Days, when all other variables are held constant. Conclusion We infer that greater number of total discharges and inpatient days are predictors of acquiring a far from conducive HACRP score. We, furthermore, infer that greater the number of total discharges and more inpatient days, greater is the likelihood of incurring a reimbursement penalty under this policy.