Measuring the economic impact of hospital-acquired complications on an acute health service
AuthorFernando-Canavan, L; Gust, A; Hsueh, A; Tran-Duy, A; Kirk, M; Brooks, P; Knight, J
Source TitleAustralian Health Review
University of Melbourne Author/sTran, An Duy; Hsueh, Ya-Seng; Brooks, Peter; Knight, Andrew; Fernando-Canavan, Liam
AffiliationMelbourne School of Population and Global Health
Document TypeJournal Article
CitationsFernando-Canavan, L., Gust, A., Hsueh, A., Tran-Duy, A., Kirk, M., Brooks, P. & Knight, J. (2020). Measuring the economic impact of hospital-acquired complications on an acute health service. AUSTRALIAN HEALTH REVIEW, 45 (2), pp.135-142. https://doi.org/10.1071/AH20126.
Access StatusOpen Access
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 93 056 inpatient 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 careassociated 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$17 173). 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.
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