The HOMR-Now! Model Accurately Predicts 1-Year Death Risk for Hospitalized Patients on Admission - 26/07/17
, Alan J. Forster, MD, MSc a, b, dAbstract |
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 1 year of admission to the hospital. This study derived and internally validated a HOMR modification using data that are available when the patient is admitted to the 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 |
Of 2,06,396 patients, 32,112 (15.6%) died within 1 year of admission to the 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 that 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 the hospital.
Le texte complet de cet article est disponible en PDF.Keywords : Administrative data, Calibration, Discrimination, Hospitalization, Mortality, Multivariate logistic regression, Risk index, Risk model, Risk score, Survival
Plan
| Funding: This study was supported by the Institute for Clinical Evaluative Sciences (ICES), which is funded by an annual grant from the Ontario Ministry of Health and Long-Term Care (MOHLTC). The opinions, results, and conclusions reported in this paper are those of the authors and are independent from the funding sources. No endorsement by ICES or the Ontario MOHLTC is intended or should be inferred. Parts of this material are based on data and information compiled and provided by Canadian Institute for Health Information (CIHI). However, the analyses, conclusions, opinions, and statements expressed herein are those of the author, and not necessarily those of CIHI. |
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| Conflict of Interest: Neither author has any conflicts of interest to declare. |
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| Authorship: Both authors had access to the data and played a role in writing the manuscript. |
Vol 130 - N° 8
P. 991.e9-991.e16 - août 2017 Retour au numéro
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