Hospital 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 a time-to-event methodology to generate a hospital standardised LOS ratio (HSLR).

Retrospective observational analysis of LOS from a jurisdictional administrative dataset using a time-to-event (hazard of discharge) analytic approach to generate risk-adjusted LOS (predicted LOS—pLOS), and the HSLR (= (sum observed LOS)/(sum total pLOS)).

219 (public and private) acute-care hospitals in the State of Victoria, Australia, adult population 5.28 million.

2.73 million adult multiday separations and 15.53 million bed-days from July 2019 to June 2024.

Nil.

Descriptive statistics for annual mean LOS (aLOS), pLOS and HSLR at the hospital level with model fit assessed for calibration (Cox-Snell residuals), classification (aLOS and HSLR results for hospital-years compared to benchmark), variance (intraclass correlation coefficient (ICC) at provider level) and model dispersion (value () and random effect SD ()) characteristics.

Observed LOS was markedly right skewed and autocorrelated (p3 SD of benchmark); whereas 936 (99.5%) HSLR values were inliers (

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.

Prehospital emergency care (PEC) requires rapid evidence-based decisions to maximise the effectiveness of care and to improve clinical outcomes. There are multiple challenges related to clinical research performed in the PEC setting. The aim of our study is to systematically review and assess the characteristics, quality of reporting, risk of bias and pragmatism in recent PEC trials, thereby identifying potential gaps and strengths that can guide the design of future prehospital studies.

We will systematically search databases MEDLINE, Embase and Cochrane CENTRAL to identify all randomised controlled trials conducted in the field of PEC and published in English language between 2010 and 2024. No restrictions will be made to the participants, interventions and outcomes. Risk of bias will be evaluated using the Cochrane Risk of Bias 2 tool. The level of pragmatism will be assessed using the Pragmatic-Explanatory Continuum Indicator Summary-2 score. Exploratory data analysis will be used to investigate and summarise main patterns. Differences in characteristics between PEC fields, study designs, publication year and associations between pragmatism levels, risk of bias and quality of reporting will be the primary focus.

There are no ethical concerns directly relevant to this review. This study has been previously registered with the Open Science Framework (osf.io/rzn9j). The manuscript will be submitted for publication to a relevant, peer-reviewed journal.