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Identifying patients at increased risk for unplanned readmission
Elizabeth H Bradley1, Olga Yakusheva, Leora I Horwitz
1Department of Health Policy and Management, Yale School of Public Health, New Haven, CT 06520, USA. elizabeth.bradley@yale.edu
Medical Care
|August 15, 2013
Summary
The Rothman Index (RI) can identify patients at high risk for unplanned readmissions. Patients in the highest RI risk category had over double the odds of readmission within 30 days.
Area of Science:
- Healthcare Analytics
- Patient Safety
- Clinical Informatics
Background:
- Reducing hospital readmissions is a national healthcare priority.
- Hospitals need effective tools to identify patients at high risk for unplanned readmissions.
- Current methods for identifying at-risk patients are often insufficient.
Purpose of the Study:
- To determine the association between the Rothman Index (RI) and 30-day unplanned hospital readmissions.
- To evaluate the RI as a predictive tool for patient readmission risk.
Main Methods:
- Adult medical and surgical patients from a teaching hospital were analyzed.
- The Rothman Index (RI), a composite electronic health record measure, was calculated.
- Logistic regression was used to assess the RI's association with readmission, adjusting for covariates.
Main Results:
- 16% of patients experienced an unplanned readmission within 30 days.
- Patients in the highest RI risk category (RI<70) had over twice the odds of readmission.
- The RI demonstrated a significant association with unplanned readmissions.
Conclusions:
- The Rothman Index (RI) can effectively identify patients at high risk for readmission.
- Clinicians can utilize the RI to target interventions and support services.
- Implementing the RI can aid hospitals in reducing unplanned readmissions.
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