Importance The value of robotically assisted surgery for mitral valve disease is questioned because the high cost of care associated with robotic technology may outweigh its clinical benefits. Objective To investigate conditions under which benefits of robotic surgery mitigate high technology costs. Design Clinical cohort study comparing costs of robotic vs. three contemporaneous conventional surgical approaches for degenerative mitral disease. Surgery was performed from 2006–2011, and comparisons were based on intent-to-treat, with propensity-matching used to reduce selection bias. Setting Large multi-specialty academic medical center. Participants 1,290 patients aged 57±11 years, 27% women, underwent mitral repair for regurgitation from posterior leaflet prolapse. Robotic surgery was used in 473, complete sternotomy in 227, partial sternotomy in 349, and anterolateral thoracotomy in 241. Three propensity-matched groups were formed based on demographics, symptoms, cardiac and noncardiac comorbidities, valve pathophysiology, and echocardiographic measurements: robotic vs. sternotomy (n=198 pairs) vs. partial sternotomy (n=293 pairs) vs. thoracotomy (n=224 pairs). Interventions Mitral valve repair. Main Outcome Measures Cost of care, expressed as robotic capital investment, maintenance, and direct technical hospital cost, and benefit of care, based on differences in recovery time. Results Median cost of care for robotically assisted surgery exceeded the cost of alternative approaches by 27% (−5%, 68%), 32% (−6%, 70%), and 21% (−2%, 54%) (median [15th, 85th percentiles]) for complete sternotomy, partial sternotomy, and anterolateral thoracotomy, respectively. Higher operative costs were partially offset by lower postoperative costs and earlier return to work: median 35 days for robotic surgery, 49 for complete sternotomy, 56 for partial sternotomy, and 42 for anterolateral thoracotomy. Resulting net differences in cost of robotic surgery vs. the three alternatives were 16% (−15%, 55%), 16% (−19%, 51%), and 15% (−7%, 49%), respectively. Beyond a volume threshold of 55–100 robotic cases per year, confidence limits for the cost of robotic surgery broadly overlapped those of conventional approaches. Conclusions In exchange for higher procedural costs, robotically assisted mitral valve surgery offers the clinical benefit of least invasive surgery, lowest postoperative cost, and fastest return to work. The value of robotically assisted surgery comparable to conventional approaches can only be realized in high-volume centers.
Introduction: Patient selection for outpatient total shoulder arthroplasty (TSA) is important to optimizing patient outcomes. This study aims to develop a machine learning tool that may aid in patient selection for outpatient total should arthroplasty based on medical comorbidities and demographic factors. Methods: Patients undergoing elective TSA from 2011 to 2016 in the American College of Surgeons National Surgical Quality Improvement Program were queried. A random forest machine learning model was used to predict which patients had a length of stay of 1 day or less (short stay). A multivariable logistic regression was then used to identify which variables were significantly correlated with a short or long stay. Results: From 2011 to 2016, 4,500 patients were identified as having undergone elective TSA and having the necessary predictive features and outcomes recorded. The machine learning model was able to successfully identify short stay patients, producing an area under the receiver operator curve of 0.77. The multivariate logistic regression identified numerous variables associated with a short stay including age less than 70 years and male sex as well as variables associated with a longer stay including diabetes, chronic obstructive pulmonary disease, and American Society of Anesthesiologists class greater than 2. Conclusions: Machine learning may be used to predict which patients are suitable candidates for short stay or outpatient TSA based on their medical comorbidities and demographic profile.
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