Background: An understanding of financial trends is important to advance agreeable reimbursement models in plastic surgery. This study aimed to evaluate trends in Medicare reimbursement rates for the 20 most commonly billed reconstructive plastic surgery procedures from 2000 to 2019. Methods: The Centers for Medicare and Medicaid Services Physician and Other Supplier Public Use File was used to identify the 20 reconstructive procedures most commonly billed to Medicare by plastic surgeons in 2016. Reimbursement data were extracted from The Physician Fee Schedule Look-Up Tool from the Centers for Medicare and Medicaid Services for each CPT code. Monetary data were adjusted for inflation to 2019 U.S. dollars. Average annual and total percentage changes in reimbursement were calculated based on these adjusted trends. Results: The average adjusted reimbursement for all procedures decreased by 14.0 percent from 2000 to 2019. The greatest mean decrease was observed in complex wound repair of the scalp, arms, or legs (−33.2 percent). The only procedure with an increased adjusted reimbursement rate was layer-closure of the scalp, axillae, trunk, and/or extremities (6.5 percent). From 2000 to 2019, the adjusted reimbursement rate for all procedures decreased by an average of 0.8 percent annually. Conclusions: This is the first comprehensive study evaluating trends in Medicare reimbursement in plastic surgery. When adjusted for inflation, Medicare reimbursement for the included procedures has steadily decreased from 2000 to 2019. Increased consideration of these trends will be important for U.S. policymakers, hospitals, and surgeons to ensure continued access to meaningful reconstructive plastic surgery care.

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.