Background — The Hospital-patient One-year Mortality Risk (HOMR) score is an externally validated index using health administrative data to accurately predict the risk of death within one year of admission to hospital. This study derived and internally validated a HOMR modification using data that are available when the patient is admitted to hospital.
Methods — From all adult hospitalizations at our tertiary-care teaching hospital between 2004 and 2015, we randomly selected one per patient. We added to all HOMR variables that could be determined from our hospital's data systems on admission other factors that might prognosticate. Vital statistics registries determined vital status at 1-year from admission.
Results — 32, 112 of 206, 396 patients (15.6%) died within 1 year of admission to hospital. The HOMR-now! model included patient (sex, comorbidities, living and cancer clinic status, and 1-year death risk from population-based life-tables) and hospitalization factors (admission year, urgency, service and laboratory-based acuity score). The model explained more than half of the total variability (Regenkirke's R2 value of 0.53), was very discriminative (c-statistic 0.92), and accurately predicted death risk (calibration slope 0.98).
Conclusion — One-year risk of death can be accurately predicted using routinely collected data available when patients are admitted to hospital.
View full text
Research and statistical methods