Jarvis, Tyler L.

Background: Research regarding financial trends in craniofacial trauma surgery is limited. Understanding these trends is important to the evolvement of suitable reimbursement models in craniofacial plastic surgery. The purpose of this study was to evaluate the trends in Medicare reimbursement rates for the top 20 most utilized surgical procedures for facial trauma. Methods: The 20 most commonly utilized Current Procedural Terminology (CPT) codes for facial trauma repairs in 2018 were queried from The National Summary Data File from the Centers for Medicare & Medicaid Services (CMS). Reimbursement data for each procedure was then extracted from The Physician Fee Schedule Lookup Tool. Changes to the United States consumer price index (CPI) were used to adjust all gathered data for inflation to 2021 US dollars (USD). The average annual and the total percent change in reimbursement were calculated for the included procedures based on the adjusted trends from the years 2000 to 2021. Results: From 2000 to 2021, the average reimbursement for all procedures decreased by 16.6% after adjusting for inflation. Closed treatment of temporomandibular joint dislocation and closed treatment of nasal bone fractures without manipulation demonstrated the greatest decrease in mean adjusted reimbursement at −48.7% and −48.3%, respectively, while closed treatment of nasal bone fractures without stabilization demonstrated the smallest mean decrease at −1.4% during the study period. Open treatment of nasal septal fractures with or without stabilization demonstrated the greatest increase in mean adjusted reimbursement at 18.9%, while closed treatment of nasal septal fractures with or without stabilization demonstrated the smallest increase at 1.2%. The average reimbursement for all closed procedures in the top 20 decreased by 19.3%, while that for all open procedures decreased by 15.5%. The adjusted reimbursement rate for all top 20 procedures decreased by an average of 0.8% each year. Conclusions: To the best of our knowledge, this is the first study to comprehensively evaluate trends in Medicare reimbursement for facial trauma surgical repairs. Adjusting for inflation, Medicare reimbursement for the top 20 most commonly utilized procedures has largely decreased from 2000 to 2021. Consideration of these trends by surgeons, hospital systems, and policymakers will be important to assure continued access to meaningful surgical facial trauma care in the United States.

Background: Artificial intelligence (AI) in healthcare delivery has become an important area of research due to the rapid progression of technology, which has allowed the growth of many processes historically reliant upon human input. AI has become particularly important in plastic surgery in a variety of settings. This article highlights current applications of AI in plastic surgery and discusses future implications. We further detail ethical issues that may arise in the implementation of AI in plastic surgery. Methods: We conducted a systematic literature review of all electronically available publications in the PubMed, Scopus, and Web of Science databases as of February 5, 2020. All returned publications regarding the application of AI in plastic surgery were considered for inclusion. Results: Of the 89 novel articles returned, 14 satisfied inclusion and exclusion criteria. Articles procured from the references of those of the database search and those pertaining to historical and ethical implications were summarized when relevant. Conclusions: Numerous applications of AI exist in plastic surgery. Big data, machine learning, deep learning, natural language processing, and facial recognition are examples of AI-based technology that plastic surgeons may utilize to advance their surgical practice. Like any evolving technology, however, the use of AI in healthcare raises important ethical issues, including patient autonomy and informed consent, confidentiality, and appropriate data use. Such considerations are significant, as high ethical standards are key to appropriate and longstanding implementation of AI.