A seven-factor prediction model can identify hospital patients at risk for 30-day readmission, according to a study in JAMA Internal Medicine.
Researchers developed a prediction model for potentially avoidable 30-day hospital readmissions in medical patients. The model is based on data from patient discharges from three hospitals of Boston-based Partners HealthCare from 2009 to 2010.
The prediction score, called the HOSPITAL score, includes seven independent factors:
1. Hemoglobin at discharge
2. Discharge from an oncology service
3. Sodium level at discharge
4. Procedure during the index admission
5. Index type of admission
6. Number of admissions during the last 12 months
7. Length of stay
"The HOSPITAL score had fair discriminatory power and had good calibration," according to the study. The authors suggest hospitals can use this tool to identify patients at high risk for readmission early and take measures to prevent readmissions.
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Researchers developed a prediction model for potentially avoidable 30-day hospital readmissions in medical patients. The model is based on data from patient discharges from three hospitals of Boston-based Partners HealthCare from 2009 to 2010.
The prediction score, called the HOSPITAL score, includes seven independent factors:
1. Hemoglobin at discharge
2. Discharge from an oncology service
3. Sodium level at discharge
4. Procedure during the index admission
5. Index type of admission
6. Number of admissions during the last 12 months
7. Length of stay
"The HOSPITAL score had fair discriminatory power and had good calibration," according to the study. The authors suggest hospitals can use this tool to identify patients at high risk for readmission early and take measures to prevent readmissions.
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