Predictors for day case surgery in shoulder arthroplasty: a study using the National Joint Registry and Hospital Episode Statistics for England.

INTRODUCTION: As shoulder arthroplasty volume increases in the UK, capacity challenges within a stretched health service mean that day case shoulder arthroplasty offers a value based solution. Patient selection for this is crucial and there is lack of evidence that informs guidance on patient selection for day case surgery. This study aims to use a large population reflective database, The National Joint Registry (NJR), to identify independent predictors for day case shoulder arthroplasty as well as develop a statistical tool that aids patient selection. METHOD: All shoulder arthroplasty procedures were requested from 1st April 2012 to 31st March 2022 from the NJR. These were then linked to the Hospital Episode Statistics for England (HES) to identify patient co-morbidities. A multivariable regression model was used to identify independent predictors of day case surgery. These predictors were then used to develop a clinical tool to predict likelihood of day case surgery with clinician inputted parameters. RESULTS: There were 40,877 patients available for analysis. Younger age, being male having a lower ASA score, being operated on Monday-Thursday and having a Total Shoulder Arthroplasty or a Hemiarthroplasty rather than a Reverse Shoulder arthroplasty were significant predictors of having day case surgery. Having a diagnosis of dementia or paraplegia reduced the risk of having day case surgery. Using these predictive variables an excel prediction tool was developed with moderate predictive ability (AUC 0.65 GOF 0.82). CONCLUSION: This study has identified independent predictors for day case surgery and has developed a tool that can act as an adjunct for clinicians selecting patients for day case shoulder arthroplasty.