Background Early identification of patients who need post-acute care (PAC) may improve
discharge planning. The purposes of the study were to develop and validate a score …

Objective To propose an easy predictive model for the risk of rehospitalization, built from
hospital administrative data, in order to prevent repeated admissions and to improve …

Objectives Although hospital clinicians strive to effectively refer patients who require post-
acute care (PAC), their discharge planning processes often vary greatly, and typically are …

Objectives This study aims to determine the risk factors predicting rehospitalization by
comparing three models and selecting the most successful model. Methods In order to …

Results: After sharing the D2S2 results, the percentage of referral or high-risk patients
readmitted by 30 and 60 days decreased by 6% and 9%, respectively, representing a 26 …

Objective To derive and validate a model to predict a patient's probability of skilled nursing
facility (SNF) discharge using data available from day 1 of hospitalization. Design Using a …

Background Previous work has suggested that given a hospital's need to admit more
patients from the emergency department (ED), high inpatient bed occupancy may …

BACKGROUND, OBJECTIVE Patients' self‐reported preparedness for discharge has been
shown to predict readmission. It is unclear what differences exist in the predictive abilities of …

Rationale: Provider decisions about patients to be discharged from the intensive care unit
(ICU) are often based on subjective intuition, sometimes leading to premature discharge and …

OBJECTIVE: To develop and validate a prediction rule screening instrument, easily
incorporated into the routine hospital admission assessment, that could facilitate discharge …