Predicting Length of Stay and Discharge Destination for Surgical Patients: A Cohort Study

Fabrizio Bert, Omar Kakaa, Alessio Corradi, Annamaria Mascaro, Stefano Roggero, Daniela Corsi, Antonio Scarmozzino and Roberta Siliquini
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Fabrizio Bert: Department of Public Health Sciences, University of Torino, 10126 Torino, Italy
Omar Kakaa: Department of Public Health Sciences, University of Torino, 10126 Torino, Italy
Alessio Corradi: Department of Public Health Sciences, University of Torino, 10126 Torino, Italy
Annamaria Mascaro: Department of Public Health Sciences, University of Torino, 10126 Torino, Italy
Stefano Roggero: Department of Quality and Safety of Care, A.O.U. City of Health and Science of Torino, 10126 Torino, Italy
Daniela Corsi: Department of Quality and Safety of Care, A.O.U. City of Health and Science of Torino, 10126 Torino, Italy
Antonio Scarmozzino: Department of Quality and Safety of Care, A.O.U. City of Health and Science of Torino, 10126 Torino, Italy
Roberta Siliquini: Department of Public Health Sciences, University of Torino, 10126 Torino, Italy

IJERPH, 2020, vol. 17, issue 24, 1-10

Abstract: Discharge planning is important to prevent surgical site infections, reduce costs, and improve the hospitalization experience. The identification of early variables that can predict a longer-than-expected length of stay or the need for a discharge with additional needs can improve this process. A cohort study was conducted in the largest hospital of Northern Italy, collecting discharge records from January 2017 to January 2020 and pre-admission visits in the last three months. Socio-demographic and clinical data were collected. Linear and logistic regression models were fitted. The main outcomes were the length of stay (LOS) and discharge destination. The main predictors of a longer LOS were the need for additional care at discharge (+10.76 days), hospitalization from the emergency department (ED) (+5.21 days), and age (+0.04 days per year), accounting for clinical variables ( p < 0.001 for all variables). Each year of age and hospitalization from the ED were associated with a higher probability of needing additional care at discharge (OR 1.02 and 1.77, respectively, p < 0.001). No additional findings came from pre-admission forms. Discharge difficulties seem to be related mainly to age and hospitalization procedures: those factors are probably masking underlying social risk factors that do not show up in patients with planned admissions.

Keywords: discharge planning; surgery; cohort study; early prediction; difficult discharge; length of stay (search for similar items in EconPapers)
JEL-codes: I I1 I3 Q Q5 (search for similar items in EconPapers)
Date: 2020
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