Article: Patient related risks and outcome assessments on interhospital surgical site infection rates Journal: International Journal of Medical Engineering and Informatics (IJMEI) 2023 Vol.15 No.2 pp.177

Authors: Vibha Gujar; Shankar Srinivasan; Dinesh P. Mital; Frederick D. Coffman

Addresses: Department of Health Informatics Rutgers – School of Health Professions, Piscataway, New Jersey 08854, USA ' Department of Health Informatics Rutgers – School of Health Professions, Piscataway, New Jersey 08854, USA ' Department of Health Informatics Rutgers – School of Health Professions, Piscataway, New Jersey 08854, USA ' Department of Health Informatics Rutgers – School of Health Professions, Piscataway, New Jersey 08854, USA

Abstract: Propensity scores and regression reduces confounding bias in medical research. This paper employs these methods to examine secondary data available through the healthcare cost and utilisation project (HCUP, year 2008-2012), for surgical site infection (SSI) risks and outcomes amongst the patient population across multi-level structural hierarchy in hospitals. Results indicated that large hospitals were significantly efficient in infection prevention and had lesser cost burden than small hospitals. Propensity scores matching analysis also obtained small hospitals at rural locations charged SSI patients up to 33.4% (average: $30,891), about 12% more than urban hospitals within 15 to 30 days of hospital stay. SSI and its impact on outcomes appeared to be mediated by age, disease severity, neighbourhood or economic conditions, elective, and transferred admissions for specific hospital size.

Keywords: surgical site infection; hospital size; secondary data; propensity score; case definition; total charges.

DOI: 10.1504/IJMEI.2023.10051948

International Journal of Medical Engineering and Informatics, 2023 Vol.15 No.2, pp.177 - 190

Received: 11 Oct 2020Accepted: 14 Mar 2021Published online: 07 Mar 2023 *