A HIGHLY PREDICTIVE MACHINE LEARNING MODEL TO IDENTIFY HOSPITALIZED PATIENTS AT RISK FOR 30-DAY READMISSION OR MORTALITY

The gradient boosted machine learning model was built on a large number of predictive features including the OM1 medical burden index (OM1 MBI), which is a standardized measure of the combined effect of current and prior conditions and treatments on current health status, generated from extensive an...

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Bibliographic Details
Published in:Journal of the American College of Cardiology 2018-03, Vol.71 (11), p.A1734-A1734
Main Authors: Su, Zhaohui, Donadio, Gregory, Brecht, Tom, O'Donovan, Francis, Boussios, Costas, Menon, Vandana, Gliklich, Rich
Format: Article
Language:English
Subjects:
Artificial intelligence
Cardiology
Learning algorithms
Machine learning
Online Access:Get full text
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Summary:The gradient boosted machine learning model was built on a large number of predictive features including the OM1 medical burden index (OM1 MBI), which is a standardized measure of the combined effect of current and prior conditions and treatments on current health status, generated from extensive analysis of OM1's longitudinal patient cohort (n>175M). Conclusion Our model generated by advanced machine learning demonstrates superior performance to previously published predictive models, e.g., the established LACE+ index (C-statistic 0.76).
ISSN:0735-1097
1558-3597
DOI:10.1016/S0735-1097(18)32275-7