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Development and validation of a predictive model for all-cause hospital readmissions in Winnipeg, Canada
Yang Cui1, Colleen Metge2, Xibiao Ye2
1The George and Fay Yee Centre for Healthcare Innovation, Winnipeg, Manitoba, Canada Winnipeg Regional Health Authority, Winnipeg, Manitoba, Canada Department of Community Health Sciences, Faculty of Medicine, University of Manitoba, Winnipeg, Manitoba, Canada umcui@myumanitoba.ca.
Objective:
A number of predictive models have been developed to identify patients at risk of hospital readmission. Most of these have focused on readmission within 30 days of discharge. We used population-based health administrative data to develop a predictive model for hospital readmission within 12 months of discharge in Winnipeg, Canada.
Methods:
This was a retrospective cohort study with derivation and validation data sets. Multivariable logistic regression analyses were performed and factors significantly associated with readmission were selected to construct a risk scoring tool.
Results:
Several variables were identified that predicted readmission (i.e. older age, male, at least one hospital admission in the previous two years, an emergent (index) hospital admission, Charlson comorbidity score >0 and length of stay). Discrimination power was acceptable (C statistic =0.701). At a median risk score threshold, the sensitivity, specificity, positive and negative predictive values were 45.5%, 79%, 68.8% and 58.6%.
Conclusions:
This predictive model demonstrated that hospital readmission within 12 months of discharge can be reasonably well predicted based on administrative data. It will help health care providers target interventions to prevent unnecessary hospital readmissions.
