Prediction of Post-acute Care Demand in Medical and Neurological Inpatients: Diagnostic Assessment of the Post-acute Discharge Score - a Prospective Cohort Study

Background: Early identification of patients requiring transfer to post-acute care (PAC) facilities shortens hospital stays. With a focus on interprofessional assessment of biopsychosocial risk, this study's aim was to assess medical and neurological patients' post-acute care discharge (PACD) scores on days 1 and 3 after hospital admission regarding diagnostic accuracy and effectiveness as an early screening tool. The transfer to PAC facilities served as the outcome ("gold standard").

Methods: In this prospective cohort study, registered at ClinicalTrial.gov (NCT01768494) on January 2013, 1432 medical and 464 neurological patients (total n = 1896) were included consecutively between February and October 2013. PACD scores and other relevant data were extracted from electronic records of patient admissions, hospital stays, and interviews at day 30 post-hospital admission. To gauge the scores' accuracy, we plotted receiver operating characteristic (ROC) curves, calculated area under the curve (AUC), and determined sensitivity and specificity at various cut-off levels.

Results: Medical patients' day 1 and day 3 PACD scores accurately predicted discharge to PAC facilities, with respective discriminating powers (AUC) of 0.77 and 0.82. With a PACD cut-off of ≥8 points, day 1 and 3 sensitivities were respectively 72.6% and 83.6%, with respective specificities of 66.5% and 70.0%. Neurological patients' scores showed lower accuracy both days: using the same cut-off, respective day 1 and day 3 AUCs were 0.68 and 0.78, sensitivities 41.4% and 68.7% and specificities 81.4% and 83.4%.

Conclusion: PACD scores at days 1 and 3 accurately predicted transfer to PAC facilities, especially in medical patients on day 3. To confirm and refine these results, PACD scores' value to guide discharge planning interventions and subsequent impact on hospital stay warrants further investigation.

Trial Registration: ClinialTrials.gov Identifier, NCT01768494 .