The novel coronavirus pandemic, also known as severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), has placed an immense strain on healthcare systems across the entire world. Consequently, multiple federal and state governments have placed restrictions on hospitals such as limiting “elective surgery” and recommending social or physical distancing. We review the literature on several areas that have been affected including surgical selection, inpatient care, and physician well-being. These areas affecting inpatient paradigms include surgical priority, physical or social distancing, file sharing for online clinical communications, and physician wellness. During this crisis, it is important that orthopaedic departments place an emphasis on personnel safety and slowing the spread of the virus so that the department can still maintain vital functions. Physical distancing and emerging technologies such as inpatient telemedicine and online file sharing applications can enable orthopaedic programs to still function while attempting to protect medical staff and patients from the novel coronavirus spread. This literature review sought to provide evidence-based guidance to orthopaedic departments during an unprecedented time. Orthopaedic surgeons should follow the Centers for Disease Control and Prevention guidelines, wear personal protective equipment (PPE) when appropriate, have teams created using physical distancing, understand the department's policy on elective surgery, and engage in routines which enhance physician wellness.

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The COVID-19 pandemic swept across the world, altering the structure and existence of graduate medical education programs across all disciplines. Orthopaedic residency programs can adapt during these unprecedented times to continue providing meaningful education to trainees and to continue providing high-quality patient care, all while keeping both residents and patients safe from disease. The purpose of this review was to evaluate the literature and describe evidence-based changes that can be made in an orthopaedic residency program to ensure patient and resident safety while sustaining the principles of graduate medical education during the COVID-19 pandemic. We describe measures that can be enacted now or during future pandemics, including workforce and occupational modifications, personal protective equipment, telemedicine, online didactic education, resident wellness, return to elective surgery, and factors affecting medical students and fellows. After a review of these strategies, programs can make changes for sustainable improvements and adapt to be ready for second-wave events or future pandemics. Level of Evidence: Level V.

(1) Background: Length of stay (LOS) is a commonly reported metric used to assess surgical success, patient outcomes, and economic impact. The focus of this study is to use a variety of machine learning algorithms to reliably predict whether a patient undergoing posterior spinal fusion surgery treatment for Adult Spine Deformity (ASD) will experience a prolonged LOS. (2) Methods: Patients undergoing treatment for ASD with posterior spinal fusion surgery were selected from the American College of Surgeon’s NSQIP dataset. Prolonged LOS was defined as a LOS greater than or equal to 9 days. Data was analyzed with the Logistic Regression, Decision Tree, Random Forest, XGBoost, and Gradient Boosting functions in Python with the Sci-Kit learn package. Prediction accuracy and area under the curve (AUC) were calculated. (3) Results: 1281 posterior patients were analyzed. The five algorithms had prediction accuracies between 68% and 83% for posterior cases (AUC: 0.566–0.821). Multivariable regression indicated that increased Work Relative Value Units (RVU), elevated American Society of Anesthesiologists (ASA) class, and longer operating times were linked to longer LOS. (4) Conclusions: Machine learning algorithms can predict if patients will experience an increased LOS following ASD surgery. Therefore, medical resources can be more appropriately allocated towards patients who are at risk of prolonged LOS.