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Background: The emergency medicine (EM) landscape has evolved due to the increasing number of programs paired with fewer applicants. This study analyzed the characteristics of EM residency programs associated with unfilled positions during the 2024 Match and compared them with data from the 2023 Match to identify persistent and emerging trends influencing these outcomes. Methods: In this cross-sectional, observational study, we investigated factors associated with unfilled EM residency positions in the 2024 Match. We used publicly accessible data from the National Resident Matching Program. To identify program-level predictors of unfilled positions, we constructed a Bayesian hierarchical logistic regression model, incorporating data from the 2023 Match season. Results: In 2024, 54 out of 281 (19.2%) residency programs remained unfilled. Our Bayesian analysis reaffirmed that smaller program size, geographical location, prior osteopathic accreditation, and corporate ownership continue to be significant factors. Programs with vacancies in the previous year were also more likely to remain unfilled. Thus, several factors identified in 2023 remained associated with this year's Match outcomes, with the impact of previous unfilled positions being particularly pronounced. Conclusions: This study identified several factors associated with a greater likelihood of having unfilled EM residency positions, with previous unfilled positions emerging as the most significant predictor. These findings offer critical insights for residency programs and governing bodies, providing a basis for enhancing recruitment strategies, addressing the cyclical nature of unfilled positions, and tackling workforce challenges in EM.
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ABSTRACT: Letters of reference (LORs) are a common component of the application process for residency training programs. With the United States Medical Licensing Examination Step 1 transitioning to pass/fail grading and with the increasing use of holistic review, the potential role of LORs is rising in importance. Among some key benefits are the ability to provide a broader and more holistic view of applicants, which can include highlighting elements of experiences or skills that could be missed in their application, as well as providing a third-party assessment of the applicant external to their rotation experiences. However, LORs also face issues, including variation in quality, challenges with comparability, and risk of bias. In this article, the authors discuss the unique benefits, limitations, and best practice recommendations for LORs in academic medicine. The authors also discuss future directions, including the role of artificial intelligence, unblinded, and co-created LORs.
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Objectives: Letters of recommendation (LORs) are essential within academic medicine, affecting a number of important decisions regarding advancement, yet these letters take significant amounts of time and labor to prepare. The use of generative artificial intelligence (AI) tools, such as ChatGPT, are gaining popularity for a variety of academic writing tasks and offer an innovative solution to relieve the burden of letter writing. It is yet to be determined if ChatGPT could aid in crafting LORs, particularly in high-stakes contexts like faculty promotion. To determine the feasibility of this process and whether there is a significant difference between AI and human-authored letters, we conducted a study aimed at determining whether academic physicians can distinguish between the two. Methods: A quasi-experimental study was conducted using a single-blind design. Academic physicians with experience in reviewing LORs were presented with LORs for promotion to associate professor, written by either humans or AI. Participants reviewed LORs and identified the authorship. Statistical analysis was performed to determine accuracy in distinguishing between human and AI-authored LORs. Additionally, the perceived quality and persuasiveness of the LORs were compared based on suspected and actual authorship. Results: A total of 32 participants completed letter review. The mean accuracy of distinguishing between human- versus AI-authored LORs was 59.4%. The reviewer's certainty and time spent deliberating did not significantly impact accuracy. LORs suspected to be human-authored were rated more favorably in terms of quality and persuasiveness. A difference in gender-biased language was observed in our letters: human-authored letters contained significantly more female-associated words, while the majority of AI-authored letters tended to use more male-associated words. Conclusions: Participants were unable to reliably differentiate between human- and AI-authored LORs for promotion. AI may be able to generate LORs and relieve the burden of letter writing for academicians. New strategies, policies, and guidelines are needed to balance the benefits of AI while preserving integrity and fairness in academic promotion decisions.
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Negro o Afroamericano , Internado y Residencia , Racismo Sistemático , Humanos , Población Negra , Internado y Residencia/organización & administración , Internado y Residencia/normas , Estados Unidos , Racismo Sistemático/etnología , Racismo Sistemático/prevención & control , Racismo Sistemático/psicologíaRESUMEN
INTRODUCTION: Trainees underrepresented in medicine (URiM) face additional challenges seeking community in predominantly white academic spaces, as they juggle the effects of institutional, interpersonal, and internalized racism while undergoing medical training. To offer support and a space to share these unique experiences, mentorship for URiM trainees is essential. However, URiM trainees have limited access to mentorship from URiM faculty. To address this gap, we developed a national virtual mentoring program that paired URiM trainees interested in emergency medicine (EM) with experienced mentors. METHODS: We describe the implementation of a virtual Diversity Mentoring Initiative (DMI) geared toward supporting URiM trainees interested in EM. The program development involved 1) partnering of national EM organizations to obtain funding; (2) identifying a comprehensive platform to facilitate participant communication, artificial intelligence-enabled matching, and ongoing data collection; 3) focusing on targeted recruitment of URiM trainees; and (4) fostering regular leadership meeting cadence to customize the platform and optimize the mentorship experience. CONCLUSION: We found that by using a virtual platform, the DMI enhanced the efficiency of mentor-mentee pairing, tailored matches based on participants' interests and the bandwidth of mentors, and successfully established cross-institutional connections to support the mentorship needs of URiM trainees.
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Medicina de Emergencia , Tutoría , Humanos , Mentores , Inteligencia Artificial , Encuestas y CuestionariosRESUMEN
Improving the diversity and representation in the medical workforce requires intentional and deliberate efforts to improve the pipeline and pathway for underrepresented in medicine (UIM) applicants. Diversity enhances educational experiences and improves patient care and outcomes. Through a critical review of the literature, in this article we offer evidence-based guidelines for physician pipeline and pathway programs (PP). Recommendations are provided regarding considerations on the types of programs and surrounding implementation to ensure a sound infrastructure and framework. We believe this guide will be valuable for all leaders and faculty members seeking to grow the UIM applicant pool in our efforts to advance diversity, equity, and inclusion within medicine.
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Medicina de Emergencia , Internado y Residencia , Médicos , Medicina de Emergencia/educación , HumanosRESUMEN
Advancement of diversity, equity, and inclusion (DEI) in emergency medicine can only occur with intentional recruitment of residency applicants underrepresented in medicine (UIM). Shared experiences from undergraduate and graduate medical education highlight considerations and practices that can contribute to improved diversity in the resident pool, such as holistic review and mitigating bias in the recruitment process. This review, written by members of the Council of Residency Directors in Emergency Medicine (CORD) Best Practices Subcommittee, offers best practice recommendations for the recruitment of UIM applicants. Recommendations address pre-interview readiness, interview approach, and post-interview strategies that residency leadership may use to implement holistic review and mitigate bias for recruitment of a diverse class.
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Medicina de Emergencia , Internado y Residencia , Educación de Postgrado en Medicina , Medicina de Emergencia/educación , HumanosRESUMEN
BACKGROUND: Shift work is associated with sleep disorders, which impair alertness and increase risk of chronic physical and mental health disease. In health care workers, shift work and its associated sleep loss decrease provider wellness and can compromise patient care. Pharmacological sleep aids or substances such as alcohol are often used to improve sleep with variable effects on health and well-being. OBJECTIVE: We tested whether use of noise-masking earbuds can improve reported sleep quality, sleepiness, and stress level in health care shift workers, and increase alertness and reaction time post night shift. METHODS: Emergency medicine resident physicians were recruited for a prospective, single-subject design study. Entrance surveys on current sleep habits were completed. For 14 days, participants completed daily surveys reporting sleep aid use and self-rated perceived sleepiness, tension level, and last nights' sleep quality using an 8-point Likert scale. After overnight shifts, 3-minute psychomotor vigilance tests (PVT) measuring reaction time were completed. At the end of 14 days, participants were provided noise-masking earbuds, which they used in addition to their baseline sleep regimens as they were needed for sleep for the remainder of the study period. Daily sleep surveys, post-overnight shift PVT, and earbud use data were collected for an additional 14 days. A linear mixed effects regression model was used to assess changes in the pre- and postintervention outcomes with participants serving as their own controls. RESULTS: In total, 36 residents were recruited, of whom 26 participants who completed daily sleep surveys and used earbuds at least once during the study period were included in the final analysis. The median number of days of earbud use was 5 (IQR 2-9) days of the available 14 days. On days when residents reported earbud use, previous nights' sleep quality increased by 0.5 points (P<.001, 95% CI 0.23-0.80), daily sleepiness decreased by 0.6 points (P<.001, 95% CI -0.90 to -0.34), and total daily tension decreased by 0.6 points (P<.001, 95% CI -0.81 to -0.32). These effects were more pronounced in participants who reported worse-than-average preintervention sleep scores. CONCLUSIONS: Nonpharmacological noise-masking interventions such as earbuds may improve daily sleepiness, tension, and perceived sleep quality in health care shift workers. Larger-scale studies are needed to determine this interventions' effect on other populations of shift workers' post-night shift alertness, users' long-term physical and mental health, and patient outcomes.
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Improving the recruitment, retention, and leadership advancement of faculty who are under-represented in medicine is a priority at many academic institutions to ensure excellence in patient care, research, and health equity. Here we provide a critical review of the literature and offer evidence-based guidelines for faculty recruitment, retention, and representation in leadership. Recommendations for recruitment include targeted recruitment to expand the candidate pool with diverse candidates, holistic review of applications, and incentivizing stakeholders for success with diversity efforts. Retention efforts should establish a culture of inclusivity, promote faculty development, and evaluate for biases in the promotion and tenure process. We believe this guide will be valuable for all leaders and faculty members seeking to advance diversity, equity, and inclusion in their institutions.