Hospital Standardised Length of Stay Ratio

ObjectiveHospital length of stay (LOS) is a key indicator of hospital efficiency and quality of care, but a reliable metric for benchmarking LOS remains problematic. This report describes the methodology to generate a standardised hospital LOS ratio (HSLR). DesignRetrospective observational analysis of LOS from an administrative dataset using a survival (time-to-event) analytic approach to generate average (aLOS) and risk-adjusted LOS (pLOS), and the HSLR (= [sum observed LOS]/[sum total pLOS]). Setting334 (public and private) hospitals in the state of Victoria, Australia, adult population 5.28 million. Participants2.73 million adult multi-day acute-care hospital separations and 15.53 million bed-days over five years, July 2019 - June 2024. Main outcomesHospital aLOS, pLOS, and HSLR at the provider level with model fit assessed for calibration (Cox-Snell residuals), classification (aLOS and HSLR results for each hospital-years compared to benchmark), variance (intra-class correlation coefficient [ICC]) and dispersion (value [{phi}] and random effect standard deviation [{tau}]) characteristics. ResultsLOS was markedly right skewed and autocorrelated (p<0.001); population median 3.94 (interquartile range: 2.48-6.76); aLOS 5.68 {+/-}4.98 days. LOS prediction model included six demographic covariates (age, sex, aged-care residency, emergent, admission source, unplanned transfer) and 12,145 separate principal diagnoses aggregated into nine ranked LOS risk-categories. 572 (61% of 940 hospital-year) aLOS values were outside {+/-}3SD benchmark; whereas 936 (99.5%) HSLR values within {+/-}3SD; 98% within {+/-}2SD. Model dispersion ({phi} = 2.80; {tau} = 0.15) and ICC at provider level (0.025) were low. ConclusionsaLOS is a simple descriptor but poor comparator. Time-to-event survival analytic models furnish risk-adjusted pLOS and HSLR metrics which indicate that majority of LOS variation is due to patient-related, not hospital, factors.