Priya S. Garg

Artificial intelligence (AI) driven by machine learning (ML) algorithms is a branch in computer science that is rapidly gaining popularity within the healthcare sector. Recent regulatory approvals of AI-driven companion diagnostics and other products are glimmers of a future in which these tools could play a key role by defining the way medicine will be practiced. Educating the next generation of medical professionals with the right ML techniques will enable them to become part of this emerging data science revolution.

BACKGROUND: Healthcare-focused hackathons are 48-hour platforms intended to accelerate novel medical technology. However, debate exists about how much they contribute to medical technology innovation. The Consortium for Affordable Medical Technologies (CAMTech) has developed a three-pronged model to maximise their effectiveness. To gauge the success of this model, we examined follow-up outcomes. METHODS: Outcomes of 12 hackathons from 2012 to 2015 in India, Uganda and the USA were measured using emailed surveys. To minimise response bias, non-responding teams were coded as having made no progress. RESULTS: 331 individuals provided information on 196 of 356 projects (55.1% response rate), with no difference in responses from teams participating in different countries (Cramer's V=0.09, p=0.17). 30.3% of projects had made progress after a mean of 12.2 months. 88 (24.7%) teams had initiated pilot testing, with 42 (11.8%) piloting with care providers and 24 (6.7%) with patients. Overall, 97 teams (8.1 per hackathon) drafted business plans, 22 (1.8 per hackathon) had filed patents on their innovations and 15 (1.3 per hackathon) had formed new companies. Teams raised US$64.08 million in funding (average US$5.34 million per hackathon; median award size of $1800). In addition, 108 teams (30.3%) reported at least one member working on additional technologies with people they met at a hackathon. Individual confidence to address medical technology challenges was significantly increased after attending (t(1282)=192.77, p 0.001). CONCLUSION: CAMTech healthcare hackathons lead to consistent output with respect to medical technology innovation, including clinical trials, business plan development, securing investment capital/funding and new company formation.

In the context of current U.S. racial justice movements, analysis of racism in medicine within medical education is a critical task for all institutions. To educate the next generation of physicians about racism in medicine and out of concern that the curriculum required critical assessment and change, a group of students and faculty at Boston University School of Medicine (BUSM) initiated a longitudinal curricular analysis through a vertical integration group, commissioned by the Medical Education Committee, from May 2019 to June 2020. The curriculum analysis and the major outcomes and guiding principles that emerged from it are described as a path forward, toward a more inclusive curriculum. The major elements of this analysis included a comprehensive internal curricular assessment and an external assessment of peer institutions that led to the development of key curricular recommendations and overarching equity and specific racially focused equity competencies. The curricular recommendations fall into the following domains: (1) challenging the persistence of biological/genetic notions of race, (2) embedding structural practices in medical education to dismantle racism in medicine, and (3) promoting institutional climate change. Initial steps to implement these recommendations are described. The authors believe that the historic and present reality of racism in America and in medicine has impacted medical education specifically, and more broadly, the practice of medicine, trainee experience, and patient outcomes. The key findings of the BUSM analysis are transferable to other medical education institutions, and the described review process can support peer institutions as they engage in the imperative work of institutional reflection and addressing the salient ideas and practices that uphold racism in medicine.

PURPOSE: Physician assistants (PAs) and medical degree students (MDs) often lack training in addressing the social determinants of health (SDOH). Social work students (SWs), meanwhile, have extensive SDOH training; however, few medical professionals have opportunities to engage in interprofessional training with SWs. This study examined the feasibility, acceptability, and students' perceptions of an interprofessional virtual reality (VR) simulated learning environment (SLE) for teaching health professions students about the SDOH. METHOD: In January 2020, 15 students at Boston University School of Medicine attended web-based video conferences focused on SDOH, health equity, and team-based care. Subsequently, student dyads participated in a case-based learning activity using an immersive VR SLE to develop teamwork skills. Evaluation included a postsurvey and a focus group examining their experiences in the course to gauge feasibility and acceptability. Thematic analysis of open-ended survey responses from the postsurvey and focus group data was conducted. RESULTS: A total of 8 VR simulations were run. Findings indicated both MD and PA students learned patient engagement strategies from SW students, who enhanced their health care leadership capacity. Participants found the means of instruction acceptable, valued the hands-on VR interprofessional training, and expressed interest in learning more about the scope of one another's roles and the community resources available to patients. CONCLUSIONS: VR SLE is a feasible and acceptable means of instruction. It allowed students to connect across programmatic and geographic boundaries in a collaborative working environment mimicking the team approach to care they will use in their professional life. This experience illustrated for students the strengths a multidisciplinary team has to offer.