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INTRODUCTION: Residency interviews have traditionally been conducted in person; however, COVID-19 forced programs to shift to virtual interviewing. This study delineated the nationwide trends observed after virtual interviewing across multiple application cycles on both surgical residency applicant competitiveness and program workload. METHODS: Publicly available National Residency Matching Program applicant and program data were retrospectively reviewed. Applicant competitiveness was assessed using a validated competitive index (# positions ranked/match rate). Interview types included in-person (2010-2020) or virtual (2021-2023), and programs were classified as general surgery (GS), surgical subspecialty (SS) - orthopedics, otolaryngology and neurosurgery, and integrated specialty (IS) - plastic, thoracic, and vascular surgery. RESULTS: When comparing in-person to virtual cohorts, the competitive index has increased in GS (0.97 ± 0.00 to 1.05 ± 0.01, P < 0.001), SS (0.97 ± 0.02 to 1.06 ± 0.01 P < 0.001), and IS (0.93 ± 0.06 to 1.12 ± 0.03, P = 0.001). United Sates Medical Licensing Examination Step scores and research experiences increased over time in GS and SS (P < 0.05). Program workload, represented by number of applications received per program increased in GS, IS, and SS (P < 0.05), as well as the number of interviews conducted in GS and SS (P < 0.05). Importantly, match rate remained stable in GS and IS, with a decrease in SS (0.69 ± 0.03 to 0.63 ± 0.02, P = 0.04). CONCLUSIONS: The residency application process has been irrevocably changed due to COVID-19. The rise in applicant volume and competitiveness places unique strains on applicants and programs. Additional modifications such as signaling and ACGME guidance are needed to help alleviate strain and ensure that residents and programs alike find their best fit.
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OBJECTIVE: Modern health care requires patients, staff, and equipment to navigate complex environments to deliver quality care efficiently. Real-time locating systems (RTLS) are local tracking systems that identify the physical locations of personnel and equipment in real time. Applications and analytic strategies to utilize RTLS-produced data are still under development. The objectives of this systematic review were to describe and analyze the key features of RTLS applications and demonstrate their potential to improve care delivery. MATERIALS AND METHODS: We searched MEDLINE, SCOPUS, and IEEE following PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines. Inclusion criteria were articles that utilize RTLS to evaluate or influence workflow in a healthcare setting. We summarized aspects of relevant articles, identified key themes in the challenges of applying RTLS to workflow improvement, and thematically reviewed the state of quantitative analytic methodologies. RESULTS: We included 42 articles in the final qualitative synthesis. The most frequent study design was observational (n = 24), followed by descriptive (n = 12) and experimental (n = 6). The most common clinical environment for study was the emergency department (n = 12), followed by entire hospital (n = 7) and surgical ward (n = 6). DISCUSSION: The focus of studies changed over time from early experience to optimization to evaluation of an established system. Common narrative themes highlighted lessons learned regarding evaluation, implementation, and information visibility. Few studies have developed quantitative techniques to effectively analyze RTLS data. CONCLUSIONS: RTLS is a useful and effective adjunct methodology in process and quality improvement, workflow analysis, and patient safety. Future directions should focus on developing enhanced analysis to meaningfully interpret RTLS data.
