The BASH score: A novel predictor for optimizing discharge timing in hip and knee arthroplasty

Abstract Background Total knee and hip arthroplasty procedures are increasingly transitioning to outpatient settings, emphasizing the need for precise discharge planning to optimize patient safety and healthcare resource utilization. Traditional risk assessments, such as the Blaylock Risk Assessment Screening Score (BRASS), provide a foundation for identifying patients at risk of prolonged hospital stays. This study evaluates BRASS's role in predicting discharge outcomes and introduces the BASH score, a refined tool to enhance discharge planning in modern joint arthroplasty. Methods This retrospective cohort study assessed 447 patients undergoing primary total knee or hip arthroplasty for osteoarthritis. The BASH score was developed based on multivariable logistic regression modeling, incorporating BRASS, age, sex, and arthroplasty type. Additional evaluations included body mass index (BMI), the Pictorial Fit-Frail Scale (PFFS), and surgical timing. Each factor's predictive value for same-day discharge was assessed using simple and multivariable logistic regression models, with results validated using bootstrapping. Results The BASH score significantly predicted same-day discharge, with a median score of 4.0 (IQR 3.5–6.0, p < 0.001). Patients with higher BASH scores were less likely to achieve same-day discharge (OR 2.47, 95 % CI 1.46–4.15). Among evaluated factors, BMI and most PFFS components, excluding pain, did not robustly predict same-day discharge. Multivariable analysis demonstrated an R² of 0.113, with bootstrapped models confirming stability (Hosmer-Lemeshow goodness-of-fit p = 0.612). Conclusion The BASH score provides a simplified and effective tool for predicting same-day discharge in joint arthroplasty patients. By incorporating key predictive factors, including BRASS, age, sex, and arthroplasty type, the BASH score enhances discharge planning and resource allocation. However, further prospective studies are needed to validate its utility across diverse clinical settings. Next steps include prospectively assessing the utility of this scoring system in multiple centres.