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Five Years' Experience With a Medical Scribe Fellowship: Shaping Future Health Professions Students While Addressing
Steven Lin1, Anthony Duong2, Cathina Nguyen3
1S. Lin is clinical associate professor and executive director, Stanford Medical Scribe Fellowship, Division of Primary Care and Population Health, Department of Medicine, Stanford University School of Medicine, Stanford, California.
Abstract:
Professional burnout has reached epidemic levels among U.S. medical providers. One key driver is the burden of clinical documentation in the electronic health record, which has given rise to medical scribes. Despite the demonstrated benefits of scribes, many providers-especially those in academic health systems-have been unable to make an economic case for them. With the aim of creating a cost-effective scribe program in which premedical students gain skills that better position them for professional schooling, while providers at risk of burnout obtain documentation support, the authors launched the Clinical Observation and Medical Transcription (COMET) Program in June 2015 at Stanford University School of Medicine. COMET is a new type of postbaccalaureate premedical program that combines an apprenticeship-like scribing experience and a package of teaching, advising, application support, and mentored scholarship that is supported by student tuition. Driven by strong demand from both participants and faculty, the program grew rapidly during its first 5 years (2015-2020). Program evaluations indicated high levels of satisfaction among participants and faculty with their mentors and mentees, respectively; that participants felt the experience better positioned them for professional schooling; and that faculty reported improved joy of practice. In summary, tuition-supported medical scribe programs, like COMET, appear to be feasible and cost-effective. The COMET model may have the potential to help shape future health professions students, while simultaneously combating provider burnout. While scalability and generalizability remain uncertain, this model may be worth exploring at other institutions.
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