Promising solution for standardised length of hospital stay based on time-to-event models and contemporary Australian administrative data
aLOS is a simple descriptor but poor comparator. Time-to-event survival analytic models furnish risk-adjusted pLOS and HSLR metrics which indicate that the majority of LOS variation is due to patient-related, not hospital, factors.
Authors
- Graeme Duke (ORCID: https://orcid.org/0000-0003-4790-6750)
- Andrew Hamilton (ORCID: https://orcid.org/0000-0001-7242-5209)
- T. Kim Le (ORCID: https://orcid.org/0000-0001-5755-7473)
- Dasamal Tharanga Fernando (ORCID: https://orcid.org/0000-0003-2423-3784)
- Carla Read
- Steven Hirth (ORCID: https://orcid.org/0000-0002-6856-2048)
- John Santamaria
- Rosangela Merlo
- Elsa Lapiz
- Zhuoyang Li
Institutions
- The University of Melbourne (AU)
- Victorian Health Promotion Foundation (AU)
- St Vincent's Hospital Melbourne (AU)
- Eastern Health (AU)
Publication Details
- Journal
- BMJ Open
- Published
- 2025-12-01
- DOI
- https://doi.org/10.1136/bmjopen-2025-108020
- Primary Topic
- Sepsis Diagnosis and Treatment
- Type
- article
- Field-Weighted Citation Impact
- 0.00