Measuring the economic impact of hospital-acquired complications on an acute health service

Abstract

Objective This study determined the economic impact of 16 'high-priority' hospital-acquired complications (HACs), as defined by the Australian Commission on Safety and Quality in Health Care, from the perspective of an individual Australian health service. Methods A retrospective cohort study was performed using a deidentified patient dataset containing 93056 in-patient separations in Northern Health (Victoria, Australia) from 1 July 2016 to 30 June 2017. Two log-linked generalised linear regression models were used to obtain additional costs and additional length of stay (LOS) for 16 different HACs, with the main outcome measures being the additional cost and LOS for all 16 HACs. Results In all, 1700 separations involving HACs (1.83%) were identified. The most common HAC was health care-associated infections. Most HACs were associated with a statistically significant risk of increased cost (15/16 HACs) and LOS (11/16 HACs). HACs involving falls resulting in fracture or other intracranial injury were associated with the highest additional cost (A$17173). The biggest increase in additional LOS was unplanned admissions to the intensive care unit (5.42 days). Conclusions This study shows the economic impact of HACs from the perspective of an individual health service. The methodology used demonstrates how other health services could determine safety priorities corresponding to their own casemix. What is known about the topic? HACs are a major issue in Australian health care; however, their effect on cost and LOS at the individual health service level is not well quantified. What does this paper add? Additional cost and LOS implications for 16 high-priority HACs have been quantified within an Australian health service. There is substantial variation in terms of the number of HACs and the economic impact of each HAC. What are the implications for practitioners? This study provides a template for other health services to assess the economic impact of HACs corresponding to their own casemix and to inform targeted patient safety programs.