Predicting Postoperative Course after Total Shoulder Arthroplasty Using a Medical-Social Evaluation Model

Introduction:The ability to predict successful outcomes is important for patient satisfaction and optimal results after shoulder arthroplasty. We hypothesize that a medical-social scoring tool will predict resource requirements in doing total shoulder arthroplasty (TSA).Methods:A retrospective analysis of 453 patients undergoing TSA was undertaken. Preoperatively, medical and social surveys were completed by each patient. Demographics, comorbidity scores, hospital course, postdischarge disposition, and readmissions were collected.Results:The average length of stay was 1.6 days (0 to 7). There was an association with utilization of home care or inpatient rehabilitation and both the medical (7.3 versus 3.9; P = 0.0002) and social (7.1 versus 3.4; P < 0.0001) components of the survey. There was a weak correlation between hospital length of stay and the social component of the survey (R = 0.29; P < 0.001), but not the medical component (R = 0.04; P = 0.38). No variable was predictive of readmission. Social score of eight was found to be predictive of postoperative requirement of home care or rehabilitation.Conclusion:This study found that Medical and Social Survey Scores can stratify patients who are at risk of requiring more advanced postdischarge care and/or a longer hospital stay. With this, we can match patients to the most appropriate level of postoperative care.