Man vs. machine: Predicting hospital bed demand from an emergency department

Generalizability of a simple approach for predicting hospital admission from an emergency department.

OBJECTIVES The objective was to test the generalizability, across a range of hospital sizes and demographics, of a previously developed method for predicting and aggregating, in real time, the probabilities that emergency department (ED) patients will be admitted to a hospital inpatient unit. METHODS Logistic regression models were developed that estimate inpatient admission probabilities of ...

Predicting Hospital Patients' Admission to Reduce Emergency Department Boarding

Predicting Emergency Department Visits

High utilizers of emergency departments account for a disproportionate number of visits, often for nonemergency conditions. This study aims to identify these high users prospectively. Routinely recorded registration data from the Indiana Public Health Emergency Surveillance System was used to predict whether patients would revisit the Emergency Department within one month, three months, and six...

Predicting emergency department admissions.

OBJECTIVE To develop and validate models to predict emergency department (ED) presentations and hospital admissions for time and day of the year. METHODS Initial model development and validation was based on 5 years of historical data from two dissimilar hospitals, followed by subsequent validation on 27 hospitals representing 95% of the ED presentations across the state. Forecast accuracy wa...

An emergency department tackles bed management and home-based care.

Ipswich Hospital Emergency Department played a vital role in the Post Acute Treatment in the Home Program (PATH) of West Moreton District Health Service. PATH used two strategies to reduce the district reliance on acute hospital beds: a short-stay unit for rapid assessment, treatment and early discharge of patients with simple conditions; and a hospital-in-the-home program utilising community h...