Risk assessment model used to predict discharge care after total hip and total knee arthroplasty: A population-based
Henrique Alves1,2, Sebastien Di Tommaso1,2, Julien Wegrzyn3
1Institute of Higher Education and Research in Healthcare - IUFRS, Lausanne University Hospital, University of Lausanne, Lausanne, Switzerland.
Background:
Transfer to a post-acute care facility or hospital readmission after total joint arthroplasty represent additional costs and increased surgical and health care resource utilization. Accurate prediction of post-acute care factors could help providers to plan the patient's discharge destination and have a positive impact on postoperative outcomes and readmission rates.
Objective:
To develop a risk assessment model to predict discharge care after total hip arthroplasty (THA) and total knee arthroplasty (TKA).
Design:
A retrospective longitudinal observational study.
Settings:
and participants: This study included 209 patients who underwent primary unilateral THA or TKA at a major academic medical center in Switzerland from January 2018 to December 2019.
Methods:
A collection of computerized- and paper-recorded data identified the discharge destination, socio-demographic factors, comorbidities, and other factors related to the patient. Univariate and multivariate analyses were performed to describe the predictors of post-surgical discharge destinations.
Results:
The characteristics associated with post-acute care after primary unilateral THA or TKA were the absence of a caregiver, advanced age, female gender, presence of walking aids, high ASA score, and comorbidity severity. A prediction model demonstrated that these six characteristics were associated 52 % with discharge to a post-acute care destination.
Conclusions:
This study allowed us to identify predictors of discharge to a post-surgical destination. Predictive models can be efficiently used to better predict which patients are predisposed to post-acute care after hospital discharge. Further studies are needed to determine the optimal criteria for different destinations.
