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Review
, 55 (2), 223-228

Digital Transformation of Academic Medicine: Breaking Barriers, Borders, and Boredom

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Review

Digital Transformation of Academic Medicine: Breaking Barriers, Borders, and Boredom

Rachel E Hanke et al. J Pediatr Surg.

Abstract

Academic medicine is experiencing an exponential increase in knowledge, evidenced by approximately 2.5 million new articles published each year. As a result, staying apprised of practice-changing findings as a busy clinician is nearly impossible. The traditional methods of staying up to date through reading textbooks and journal articles or attending an annual conference are no longer enough. These old approaches do not distribute knowledge equally around the world or inform practitioners adequately of what they need to provide the best patient care. Luckily, digital technology, which contributed to our ability to generate this explosion in research, also holds the solution. We believe the improved filtration and curation of new knowledge will come through the combination of three elements: machine learning, crowd-sourcing, and new digital platforms. Machine learning can be harnessed to identify high-quality research while avoiding unconscious bias towards authors, institutions, or positions, and to create personalized reading lists that encompass essential articles while also addressing personal knowledge gaps. The crowd can also serve to curate the best research through an open-source platform that exposes each step of the research process, from developing questions through discussion of findings, functionally replacing editorial boards with crowd peer-review. Finally, embracing new digital platforms and multimedia delivery formats will move academic medicine into the 21st century, broadening its reach to diverse, international, and multigenerational learners. The digital age will continue to change life as we know it, but we have the power - and the responsibility - to control how it transforms academic medicine. LEVEL OF EVIDENCE: V (Expert).

Keywords: Academic medicine; Artificial intelligence; Transformation.

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