Background: As payment models shift toward a focus on value, an accurate understanding of surgical costs and preoperative correlates of high-cost patients is important for effective implementation of cost-saving strategies. This study used time-driven activity-based costing (TDABC) to explore inpatient cost of total shoulder arthroplasty (TSA) and to identify preoperative characteristics of high-cost patients. Methods: Using TDABC, we calculated the cost of inpatient care for 415 patients undergoing elective primary TSA between 2016 and 2017. Patients in the top decile of cost were defined as high-cost patients. Multivariable logistic regression modeling was employed to determine preoperative characteristics (e.g., demographics, comorbidities, American Society of Anesthesiologists [ASA] score, and American Shoulder and Elbow Surgeons [ASES] score) associated with high-cost patients. Results: Implant purchase price was the main driver (57%) of total inpatient costs, followed by personnel cost from patient check-in through the time in the operating room (20%). There was a 1.3-fold variation in total cost between patients in the 90th percentile for cost and those in the 10th percentile; the widest cost variation was in personnel cost from the post-anesthesia care unit through discharge (2.5-fold) and in medication cost (2.4-fold). High-cost patients were more likely to be women and chronic opioid users and to have diabetes, depression, an ASA score of ≥3, a higher body mass index (BMI), and a lower preoperative ASES score than non-high-cost patients. After multivariable adjustment, the 3 predictors of high-cost patients were female sex, an ASA score of ≥3, and a lower ASES score. Total inpatient cost correlated strongly with the length of the hospital stay but did not correlate with operative time. Conclusions: Our study provides actionable data to contain costs in the perioperative TSA setting. From the hospital’s perspective, efforts to reduce implant purchase prices may translate into rapid substantial cost savings. At the patient level, multidisciplinary initiatives aimed at reducing length of stay and controlling medication expenses for patients at risk for high cost (e.g., infirm women with poor preoperative shoulder function) may prove effective in narrowing the existing patient-to-patient variation in costs. Level of Evidence: Economic and Decision Analysis Level IV. See Instructions for Authors for a complete description of levels of evidence.

Background: There is growing interest in enhancing the patient experience after discretionary orthopaedic surgery. Patient narratives are a potentially valuable but largely unscrutinized source of information. Using machine learning to understand sentiment within patient-experience comments, we explored the content of negative comments after total shoulder arthroplasty (TSA), their associated factors, and their relationship with traditional measures of patient satisfaction and with perioperative outcomes. Methods: An institutional registry was used to link the records of 186 patients who had undergone elective primary TSA between 2016 and 2017 with vendor-supplied patient satisfaction data, which included patient comments and the Hospital Consumer Assessment of Healthcare Providers and Systems (HCAHPS) survey. Using a machine-learning-based natural language processing approach, all patient comments were mined for sentiment and classified as positive, negative, mixed, or neutral. Negative comments were further classified into themes. Multivariable logistic regression was employed to determine characteristics associated with providing a negative comment. Results: Most patients (71%) provided at least 1 comment; 32% of the comments were negative, 62% were positive, 5% were mixed, and 1% were neutral. The themes of the negative comments were room condition (27%), time management (17%), inefficient communication (13%), lack of compassion (12%), difficult intravenous (IV) insertion (10%), food (10%), medication side effects (6%), discharge instructions (4%), and pain management (2%). Women and sicker patients were more likely to provide negative comments. Patients who made negative comments were more likely to be dissatisfied with overall hospital care and with pain management (2 HCAHPS core items), but there were no differences in any of the studied outcomes (peak pain intensity, opioid intake, operative time, hospital length of stay, discharge disposition, or 1-year American Shoulder and Elbow Surgeons [ASES] score) between those who provided negative comments and those who did not. Conclusions: Patient-narrative analysis can shed light on the aspects of the process of care that are most critiqued by patients. While patient satisfaction may not be a surrogate for effectiveness of care or functional outcomes, efforts to improve the hospital environment, enhance nontechnical skills, and reduce unnecessary delays are important in providing high-quality, patient-centered care after TSA.

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