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On the direct and spillover effects of Hospital-acquired conditions (HACs)

Dr. Haileab Hilafu
Associate Professor of Business Analytics and Statistics
The University of Tennessee
Friday, November 13, 2020
3:30-4:30pm  via Zoom


ABSTRACT: Hospital-acquired conditions (HACs) are adverse events experienced by patients as a result of the care they receive in a hospital. HACs represent a significant safety concern for patients, and can be a burden to the financial health of the healthcare system. The Centers for Medicare and Medicaid Services (CMS) designed and implemented several policies over time to motivate hospitals to reduce the prevalence of HACs. One such legislation is the Hospital Acquired Conditions Reduction Program (HACRP) that penalizes hospitals which fall in the bottom quartile for their risk-adjusted prevalence of select HACs. Consistent with the HACRP initiatives, we investigate the relationship between HACs and hospital resource usage and operational efficiency, as measured by the deviation of a patient’s hospital length of stay (LOS) from evidence-based standard LOS (i.e. geometric mean LOS, GMLOS). We also investigate the direct and mediated (via LOS) effect of HACs on the 30-day readmission risk. We conduct rigorous empirical analysis using patient visit-level dataset, for patients treated for acute myocardial infarction (AMI), from the state inpatient database for the state of Florida, to offer insights into these research questions. Our findings indicate that the presence of HACRP targeted HACs have negative ramifications on a hospitals’ ability to comply with standard LOS practice guidelines, that is, HACs are associated with a larger LOS deviation from GMLOS. We also observe that HACs experienced during the index hospitalization increase the risk of future readmissions, thus establishing HACs as an additional determinant of patient readmissions.

BIO: Dr. Haileab Hilafu is an Associate Professor of Business Analytics and Statistics at the university of Tennessee Knoxville. He completed his MS and PhD in Statistics in 2011 and 2014, respectively, at the University of Georgia. He joined UTK as an Assistant Professor upon completing his PhD in 2014. His conducts research two steams: methodological research – developing dimension reduction and variable selection methods to facilitate analysis of high-dimensional datasets; applied research in the area of healthcare operations.


He was born in Eritrea, a small East African country, and enjoys playing Football (aka soccer).