Electronic health record-based prediction models may help identify patients who are at risk for readmission within 30 days of discharge, according to a study published in the Journal of Hospital Medicine.
Researchers found a single risk factor, at least two hospital admissions in a 12-month period, accurately predicted elevated risk of readmission in retrospective EHR data. After assessing readmission risk with current electronic health record data, they found the same risk factor predicted elevated readmission risk as accurately as in the retrospective data analysis.
Researchers concluded the secondary use of EHR data to automatically identify patients with high risk of readmission when they are admitted to a hospital can help improve patient care and reduce readmission rates.
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