What question did this study set out to answer?

The aim is to describe the methodology of the Hospital Outcome Prediction Equation V.7 (HOPE-7) for risk adjustment in mortality assessments.

February 22, 2026Open Access

Hospital standardised mortality ratio: a novel method and approach to risk adjustment

Puntos clave

The aim is to describe the methodology of the Hospital Outcome Prediction Equation V.7 (HOPE-7) for risk adjustment in mortality assessments.
Aggregated principal diagnoses into 406 clinical diagnosis groups (CDGs).
Set aside low case fatality rate CDGs.
Ranked remaining CDGs according to predicted risk.
Fitted final generalised linear model to a training dataset.
Assessed model performance in a validation dataset for various metrics.
12.97 million adult separations were treated by the hospitals.
63,806 in-hospital deaths reported, with a mortality rate of 0.49 per 100 separations.
Developed model included demographic variables and diagnosis-risk categories.
Validation metrics indicated satisfactory calibration and discrimination.
Outlier case fatality rates significantly reclassified as HSMR inliers.

Resumen

Background Hospital standardised mortality ratio (HSMR) is a simple ratio that is plagued by sparsity, dimensionality, overdispersion, exclusions and controversy. Objective Describe Hospital Outcome Prediction Equation V.7 (HOPE-7) methodology. Setting State of Victoria (Australia), population 6.8 million. Methods Multiphase process: (a) principal diagnoses aggregated into 406 clinical diagnosis groups (CDGs); (b) low case fatality rate (CFR0.05, AUCROC>0.80, AUCPRC>0.30, φ~1 and τ~0. Classification assessed by proportion of outlier CFR reclassified as inlier HSMR. Results 315 hospitals treated 12.97 million adult separations and 152 (48.3%) reported 63 806 in-hospital deaths, 0.49 (95% CI 0.48 to 0.50) per 100 separations. 10 722 principal diagnoses allocated to 198 non-significant CDGs, 45 low-risk CDGs (5.05 million cases) assigned zero risk and 163 significant CDGs aggregated to 20 risk ranks. Final model (development cohort 9.73 million) included demographic variables (age, birth sex, emergency, aged-care resident, hospital transfer, relationship status), one interaction term (emergency transfer) and 20 diagnosis-risk categories. Validation metrics (cohort 3.24 million): Brier score 0.015; H 10 p value 0.09; AUCROC 0.90 (95% CI 0.87 to 0.92); AUCPRC 0.28 (95% CI 0.25 to 0.31); φ=4.31 and τ=0.24. Study hospitals generated 2192 hospital quarters with 2053 (95.7%) outlier CFR values, of which 1975 (96.2%) reclassified as HSMR inliers. Conclusions HOPE-7 is a parsimonious and pragmatic HSMR model based on administrative data common to many jurisdictions that displayed satisfactory calibration, classification and discrimination metrics and addressed frequent HSMR limitations.

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