Negative Patient-Experience Comments After Total Shoulder Arthroplasty.

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.