Scores Predict Readmission Likelihood
What's more, it allows hospital teams to identify these patients at or before discharge, before they left the hospital, and before their health status was jeopardized again.
The formula they designed weighs seven factors:
- Hemoglobin levels at discharge
- Whether the patient was discharged from an Oncology service
- Sodium level at discharge
- The Procedure performed during the admission
- The Type of index admission,
- The frequency of Admissions in the prior 12 months
- The Length of the patient's hospital stay
Lined up, the algorithm's components spell HOSPITAL, which makes it easy to remember and score, Donzé said.
In response to questions, co-author Jeffrey L. Schnipper, MD, also of Brigham and Women's, in an e-mail, elaborated on how the equation would work for a hospital where 22.3% of 1,000 patients were readmitted within 30 days, or 223 patients.
Out of those 1,000 patients, those whose HOSPITAL scores were in the top 25% would be identified. From that group, 18% would have a potentially avoidable readmissions.
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