Published on in Vol 8, No 1 (2022): Jan-Mar

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/32183, first published .
Technology Literacy in Undergraduate Medical Education: Review and Survey of the US Medical School Innovation and Technology Programs

Technology Literacy in Undergraduate Medical Education: Review and Survey of the US Medical School Innovation and Technology Programs

Technology Literacy in Undergraduate Medical Education: Review and Survey of the US Medical School Innovation and Technology Programs

Original Paper

1Department of Medicine, Boston University School of Medicine, Boston, MA, United States

2Department of Family Medicine, Boston University School of Medicine, Boston Medical Center, Boston, MA, United States

3Department of Emergency Medicine, Boston University School of Medicine, Boston Medical Center, Boston, MA, United States

Corresponding Author:

Stephanie Nicole Stapleton, MD

Department of Emergency Medicine

Boston University School of Medicine

Boston Medical Center

1 Boston Medical Center Place

Boston, MA, 02118

United States

Phone: 1 6174144892

Email: snstaple13@gmail.com


Background: Modern innovations, like machine learning, genomics, and digital health, are being integrated into medical practice at a rapid pace. Physicians in training receive little exposure to the implications, drawbacks, and methodologies of upcoming technologies prior to their deployment. As a result, there is an increasing need for the incorporation of innovation and technology (I&T) training, starting in medical school.

Objective: We aimed to identify and describe curricular and extracurricular opportunities for innovation in medical technology in US undergraduate medical education to highlight challenges and develop insights for future directions of program development.

Methods: A review of publicly available I&T program information on the official websites of US allopathic medical schools was conducted in June 2020. Programs were categorized by structure and implementation. The geographic distribution of these categories across US regions was analyzed. A survey was administered to school-affiliated student organizations with a focus on I&T and publicly available contact information. The data collected included the founding year, thematic focus, target audience, activities offered, and participant turnout rate.

Results: A total of 103 I&T opportunities at 69 distinct Liaison Committee on Medical Education–accredited medical schools were identified and characterized into the following six categories: (1) integrative 4-year curricula, (2) facilitated doctor of medicine/master of science dual degree programs in a related field, (3) interdisciplinary collaborations, (4) areas of concentration, (5) preclinical electives, and (6) student-run clubs. The presence of interdisciplinary collaboration is significantly associated with the presence of student-led initiatives (P=.001). “Starting and running a business in healthcare” and “medical devices” were the most popular thematic focuses of student-led I&T groups, representing 87% (13/15) and 80% (12/15) of respondents, respectively. “Career pathways exploration for students” was the only type of activity that was significantly associated with a high event turnout rate of >26 students per event (P=.03).

Conclusions: Existing school-led and student-driven opportunities in medical I&T indicate growing national interest and reflect challenges in implementation. The greater visibility of opportunities, collaboration among schools, and development of a centralized network can be considered to better prepare students for the changing landscape of medical practice.

JMIR Med Educ 2022;8(1):e32183

doi:10.2196/32183

Keywords



The intersection of technology and medicine has continuously transformed health care delivery [1-3]. The medical applications of advancing technologies include the use of deep learning algorithms to power diagnostics [4], automated robotics to perform minimally invasive procedures [5], and computational genomics to inform personalized treatment plans [6]. In 2020, social distancing limitations due to COVID-19 catalyzed unprecedented developments in digital health [7-9]. From video consultation platforms to home testing kits and wearable sensors, patients have been increasingly exposed to a digitally driven health care model [10,11]. The breadth of personal health data that are available to patients is larger than ever before [12,13]. However, physicians are facing an increasing need to guide patients in correctly interpreting these data as well as communicate relevant implications of technology to patients. Moreover, technology literacy in medicine, that is, a basic understanding of how new technologies work and how they can be integrated into more patient-centered and efficient health care delivery systems, may allow for more effective interdisciplinary collaboration with experts in other fields to address clinical needs in innovative ways [14,15].

No matter the objective of an individual physician, speaking the language of technology should be learned during undergraduate medical education—the earliest years of one’s training prior to the completion of an MD degree [16-18]. Some US medical schools have begun to approach the integration of technology into medical education [19-23]. However, a prior study of formal curricular programs in innovation and entrepreneurship demonstrated the lack of any formal competency models or frameworks among institutions working on this challenge [24]. Historically, medical schools have been able to adapt to health care workforce needs by providing students in training with new areas of knowledge. For example, recognizing that a patient’s health is part of a broader social and environmental context facilitated the integration of behavioral and social sciences into medical education. These changes were aimed at enabling students to better understand epidemiology, mental health, and social determinants of health [25,26]. Although integrations like these are still being refined, they can offer an implementation framework that new curricular developments can follow. A remaining challenge will be developing consensus on standards for teaching students about emergent technology. Discussions about clinical applications and implementation are somewhat speculative, as there are less supporting data than what physicians are accustomed to, and requirements differ based on location and specialty.

Medical education has historically had to balance the need for standardization with the benefits of ingenuity and diverse methodologies [27]. Due to the novelty of technology integration, it may be premature to pursue standardization before understanding the approaches that have been tried and the outcomes that they have produced. Herein, we identify and analyze the innovation and technology (I&T) opportunities available at US allopathic medical schools and discuss thematic trends to support the future development of I&T curricula. Compared to the traditional definition of innovation and entrepreneurship, which largely focuses on business and economics, we concentrated on I&T. Our analysis provides a more expansive view on the diverse formats of learning opportunities, including formal curricula as well as extracurricular electives and initiatives. This study aims to quantify and detail the existing I&T opportunities available to medical students at US medical schools to provide insight for future curricular development directions.


The data collection process consisted of a combination of public internet searches and the collection of survey responses from student organizations across the country. Surveys were conducted in June 2020 and asked for objective information, including club characteristics, types of activities, and target audiences.

Ethics Approval

Since no individual information or opinions were collected, this study did not meet the requirements for a human subject review, per our institutional review board’s protocol.

Review of Current Programs

An internet search of all Liaison Committee on Medical Education–accredited US allopathic medical schools [28] was conducted to identify any relevant curricular and extracurricular programs that were offered. The key search terms were medical education, technology, engineering, innovation and entrepreneurship, curriculum, and student activities/organizations. The inclusion criteria were defined as (1) programs officially sanctioned by a medical school (ie, programs that have been recognized by school administrations and other publicly affiliated sources) and (2) programs that mentioned at least 1 of the following in their mission statement: (1) applying engineering research and existing technologies in medicine or (2) inventing and designing technological solutions in medicine. The exclusion criteria included programs without a significant technical or innovative component. These programs may (1) have a primary focus on other topics, such as business, economics, leadership, health policy, and health information management; (2) include a scholarly component on any topic of choice but do not provide a specific focus on I&T; and (3) be doctorate of medicine and philosophy (MD-PhD) programs that undergo a separate application and admission process.

Survey on Student-Led Initiatives

The initial abstraction of public data indicated a lack of organized and publicly available information on student-led I&T organizations and activities. We designed a short, 9-question survey for student groups by using the web-based program Typeform (Typeform SL). The survey was sent electronically to all identified school-affiliated I&T groups whose contact information was publicly available. The survey consisted of 8 total questions that inquired about the (1) founding year, (2) thematic focus, (3) target audience, (4) activities offered, and (5) participant turnout rate. The responses collected contained only objective information and involved no subjective data. Recorded data were securely stored in a protected spreadsheet that was exported from Typeform.

Data Analysis

The data analysis included both aggregated data from the internet search and completed survey responses. Programs that met the inclusion and exclusion criteria were analyzed and classified into 6 categories based on program characteristics. The geographic locations of programs were noted for regional relationships. Survey results and publicly available information, either from the clubs’ own websites or from the schools’ student activity websites, were synthesized. A thematic analysis was performed and included the following information about each program: the number years since its founding, its mission, its target audience, events and activities, and the medical student turnout rate. A statistical analysis was conducted on survey data by using SPSS version 26 (IBM Corporation) for macOS. A chi-square test of independence was performed for any associations between student-led initiatives and other curricular opportunities.


Review of Current Programs

Our investigation of existing programs found varying degrees of curricular integration and various durations and target audiences. A total of 103 programs at 69 distinct schools were identified to have at least 1 program that met our inclusion and exclusion criteria. Further, 6 categories were determined based on the level of administrative and student involvement of these programs (Table 1). Programs were further analyzed by geographical region (Figure 1 and Table 2). The highest ratios of the number of available programs to the number of medical schools were found in the northeast (32 programs to 36 schools; ratio: 0.89) and west (16 programs to 24 schools; ratio: 0.67). The regional subdivision with the highest program density was New England (13 programs to 10 schools; ratio: 1.30). Texas offered the greatest number of programs (8 programs to 12 schools; ratio: 0.67), followed by California (7 programs to 13 schools; ratio: 0.54) and New York (7 programs to 15 schools; ratio: 0.47). Interestingly, 16 states were identified as having 0 I&T programs available to students at their medical schools, and 14 of these states have only 1 or 2 allopathic medical schools. Further, 12 states offer more than 3 programs, with Rhode Island having the greatest number of programs per medical school (3:1 ratio).

Student-led clubs and initiatives were the most common type of opportunity available to students, representing 44.7% (46/103) of the total programs. Curricular tracks or areas of concentration were the next most common type (21/103, 20.4%), followed by interdisciplinary collaborations (14/103, 13.6%), dual degree programs in a related field (12/103, 11.7%), and noncredited elective courses (6/103, 5.8%). Of note, there are 4 special programs with a 4-year integrated curriculum (4/103, 3.9%). Table 3 shows that interdisciplinary collaborations were the only type of program that was significantly associated with the presence of student initiatives (P=.001; χ21=10.6).

Table 1. The six identified innovation and technology program categories and descriptions of each category.
CategoryDescription of categoryNumber of programs (N=103)
4-year integrated programsThe programs exhibit longitudinal themes that are integrated across all 4 years. Admission into each program is separate from admission into the general MD degree program. Other shared characteristics include a graduating project requirement and significant accompanying research involvement. Table 3 provides a more comprehensive analysis of these programs.4
MD/MS dual degree programsFacilitated, and often accelerated (5 years or fewer), dual degree programs offering MS degrees in biomedical engineering or health technology.12
Interdisciplinary collaborationsInstitutes and incubators aimed at encouraging collaboration across different schools within the greater institution.14
Tracks or areas of concentrationThe programs extend over multiple semesters, with final completion being noted in the dean’s letter or official transcript. Many require 1 or more courses and a research component to supplement the regular medical curriculum.21
Noncredited elective coursesSemester-long courses that are available to medical students for enrichment purposes. They are not credited or noted on the official transcript.6
Student-led clubsStudent-run organizations that host regular events for the student body.46
Figure 1. A map representation of innovation and technology programs across the major geographical regions based on the US Census. AOC: area of concentration.
View this figure
Table 2. Overview of innovation and technology programs at accredited US allopathic medical schools.
CharacteristicWest regionaMidwest
regionb
Northeast
regionc
South
regiond
All regions
4-year integrated programs, n11114
MD/MS dual degree programs, n341412
Interdisciplinary collaborations, n524314
Concentration tracks or areas of concentration, n148821
Noncredited elective courses, n11316
Student-led clubs, n57151946
Total programs, n16193236103
Total schools, n24363657153
Ratio of the number of programs to the number of schools0.670.530.890.630.67

aStates per region: Washington, Oregon, California, Montana, Idaho, Wyoming, Nevada, Utah, Colorado, Arizona, and New Mexico.

bStates per region: North Dakota, South Dakota, Nebraska, Kansas, New Mexico, Iowa, Missouri, Wisconsin, Illinois, Michigan, Indiana, and Ohio.

cStates per region: New York, Pennsylvania, New Jersey, Vermont, New Hampshire, Maine, Massachusetts, Connecticut, and Rhode Island.

dStates per region: Oklahoma, Texas, Arizona, Louisiana, Mississippi, Alabama, Tennessee, Kentucky, West Virginia, Virginia, Maryland, Delaware, North Carolina, South Carolina, Georgia, and Florida.

Table 3. Associations among program categories based on the existence of student initiatives.
ProgramPresence of student-led clubsChi-square (df)P value

Yes, nNo, nTotal, n

4-year integrated programa.58b

Yes224


No44105149


Total46107153

Concentration track or area of concentration1.4 (1).23

Yes91322


No3794131


Total46107153

Noncredited elective course.37b

Yes336


No43104147


Total46107153

MD/MS dual degree program0.2 (1).69

Yes3912


No4398141


Total46107153

Interdisciplinary collaborationc10.6 (1).001

Yes10515


No36102138


Total46107153

aNot available.

bDue to the small sample size, we used the P value of a Fisher exact test instead of a chi-square test.

cSignificant at the P<.05 level.

Survey on Student-Led Initiatives

Summary of Survey Results

Of the 46 total student groups, 33 had publicly available contact information and were invited to complete the survey through email. We recorded 15 completions, indicating a 45% (15/33) response rate. The results are summarized in Multimedia Appendix 1.

Age Since Founding

The results from the survey and publicly available information yielded a total of 26 known founding years. Of the 26 student-led initiatives, 20 (77%) were founded in or after 2016, and 8 (31%) were founded in or after 2018. Figure 2 illustrates the chronological growth of these initiatives.

Figure 2. Student-led initiatives sorted based on the founding year. Founding years were either self-reported on our survey or determined based on publicly available information on medical school websites and internet archives.
View this figure
Mission

Among the 15 surveyed organizations with completed responses, student groups’ goals included “starting and running a business in healthcare” (13/15, 87%), “medical devices” (12/15, 80%), “helping students under the challenges associated with bringing ideas to market” (11/15, 73%), and “digital health” (10/15, 67%). A word cloud of club mission statements showed that technology (39 instances), innovation (38 instances), and medicine (30 instances) were the most common words mentioned (Multimedia Appendix 2).

Activities and Events

Talks hosted by either biotechnology and health industry representatives or faculty and physician speakers are the most common form of activity for student groups (13/15, 87%). Other commonly offered activities include “collaboration with schools of other disciplines” (11/15, 73%) and “connecting students to opportunities & resources” (11/15, 73%).

Turnout Rate and Audience

Of the 15 surveyed organizations, 12 (80%) indicated that >10 people routinely attended events. Of these 12 groups, 5 (42%) reported the attendance of between 26 and 50 people, and 1 (8%) reported the attendance of between 51 and 75 people. The events mostly targeted medical students in preclinical years (groups: 13/15, 87%) and graduate students (groups: 10/15, 67%). A minority of organizations (groups: 5/15, 33%) directly involve medical students in clerkship years, resident physicians, attending physicians, and engineering faculty. “Career pathways exploration for students” was the only type of activity that was significantly associated with a high event turnout rate of >26 students per event (P=.03; odds ratio 0.38, 95% CI 0.15-0.92).


Current State of I&T Programs

We found a total of 103 officially sanctioned I&T programs that were available to medical students at the time of this study. These programs span 6 levels of curricular integration, ranging from student-led initiatives to fully integrated MD degree curricula. Geographically, the highest concentration of programs per school are in the northeastern and western regions, particularly in states with a high number of medical schools that highly engage with technology industries [29]. One example of a fully integrated program is EnMed—a tripartite collaboration among Texas A&M’s College of Engineering, College of Medicine, and Houston Methodist Hospital—which integrates “innovation rotations” with researchers, collaborators, and industry partners in the medical technology field within a 4-year MD degree program [30]. However, full curriculum integration is less common. The majority of the identified programs were student-run initiatives (46/103, 44.7%). From 2015 to 2019, the number of these initiatives has seen exponential growth, with greater than a striking 400% increase (6 groups to 26 groups). The majority of student groups emphasized the thematic focuses of health care entrepreneurship (13/15, 87%) and medical devices (12/15, 80%), which were most often supported by events hosted by industrial representatives and faculty speakers. In addition, 40% (6/15) of student groups reported having >26 attendees, demonstrating high student body engagement relative to the average national class size [31].

Call for Action: Increased Interest in I&T Among Medical Students

New generations of medical students have strong interests in the technological advancements in medicine and consider these areas of growth to be essential to future clinical practice [32]. Prior survey studies have demonstrated a significant interest in medical technology and informatics among medical students and residents [33], particularly among those intending to pursue surgical specialties [34]. In another survey study, MacNevin et al [35] showed that 79.2% of second-year medical students were “technology ready,” indicating their propensity to use new technology. However, most students do not receive formal education or training in this area [36]. Our results suggest that students are taking initiative to fill unmet needs at their respective schools, highlighting the importance of developing I&T-based education programs as part of our call for educational reform [37].

Existing literature demonstrates both the benefits and challenges associated with student-led initiatives. There is evidence of student-run electives and journal clubs resulting in positive short-term outcomes [38-40]; however, medical schools need to focus more on equipping students with proper skills and resources for effecting long-lasting advancements [41]. One major challenge faced by student-led groups is recruiting and transitioning leadership between successive class years, which results in continuity gaps in provided activities from year to year. This lack of continuity may be addressed by medical school administrations taking more responsibility for their student-led groups and by introducing a structure that supports interdisciplinary collaboration. In fact, our analysis shows a significant correlation between interdisciplinary collaborations within students’ home institutions and turnout rates for student-led activities (P=.001). Students may find it easier to pursue projects and consider the future integration of innovation into their medical careers when they are able to collaborate with colleagues who have complementary skill sets, such as engineering and business skill sets [42-44]. This further reinforces the importance of administrative initiative in supporting students’ interests and activities.

Future Directions: Challenges and Propositions

Geographical Barriers to External Support

Our review identifies several challenges in the implementation of I&T-focused initiatives in US allopathic medical schools. Our geographical analysis correlates the density of available programs with their proximity to biotechnology hubs, suggesting that regional economic factors and the availability of external support may be associated with students’ and faculties’ exposure to I&T outcomes, further encouraging interest and investment [45]. However, areas with a low biotechnology entrepreneurship presence may produce fewer physicians who are equipped to take advantage of new clinical developments, leading to disparities in future care delivery and suggesting the importance of developing I&T initiatives in these areas. When considering efforts for introducing technological concepts into medical education, McCoy et al [46] suggest distinguishing between information that physicians must know for daily practice and information that they should know for innovation advancement; the curricular components of such efforts should target the former, and robust extracurricular programs should target the latter. Given the geographic distribution of programs across the country, well-equipped and well-resourced institutions may act as examples for supporting and modeling curriculum development and developing best practices.

Needs Assessment for Curricular Development

This review identifies great variation in the types of opportunities being offered to students. Hence, gaining a better understanding of the efficacy and drawbacks of each approach is important to achieving improved outcomes, as previously proposed by Chan and Zary [47] in their review of implementing artificial intelligence in medical education. Echelard et al [48] have also proposed the implementation of new courses and rotations, mentorships, and expert invitations to medical schools. Rigorous assessments of program outcomes, such as students’ familiarity with medical technology concepts or the potential rise in student- and physician-driven inventions and start-ups from proactive institutions, may be valuable downstream end points. Analyses of what practicing physician innovators identify as their needs may result in the creation of a more balanced basis for, as well as increased student interest in, defining competencies in formal curricula. In the interim, offering track programs or ancillary degrees and certificates may help with the transition to the eventual curricular reform [49]. Bringing new technologies into everyday classrooms and clinical settings can help students familiarize themselves with novel operating skills and can foster the appreciation for innovative design and problem solving [50,51].

Future studies may benefit from using Association of American Medical Colleges data from the Curriculum Reports and FACTS data sets. The former may provide insight into which schools are currently pursuing curriculum changes, which competency criteria are receiving greater prioritization in these changes, and what types of instructional methods are being applied to implement these changes. FACTS data may provide insight into the backgrounds of medical school applicants and matriculants, which may help to determine whether increasing proportions of students with engineering or business backgrounds are associated with the rapid increase in the student-led initiatives reported in our study.

Limitations

This study exhibits several limitations. First, it relied on publicly available information. Due to possible delays between the creation of initiatives and formal publicity on the web, as well as the inherent private nature of certain types of initiatives, our study may have missed more recent efforts. This may have resulted in an underestimation of recently founded programs, especially those from schools with less frequent website updates. However, one benefit of our approach is that we were able to provide a more accurate representation of how prospective trainees and collaborators are able to discover programs, as they are generally limited to publicly available information. Future studies can deliver surveys to individual medical schools to obtain a more accurate count of the number of I&T programs that each school offers. Additionally, the development of a centralized database of opportunities and joint conferences may facilitate greater discoverability within the medical education community.

A second limitation was the challenge of surveying student organizations through publicly available contact information. In some cases, publicly available contact information was unavailable or outdated, resulting in only 33 of the 46 identified programs being sent surveys and contributing to our survey response rate. As in all survey studies, limitations in the generalizability and inflexibility of multiple-choice responses apply to our study. Our survey may be biased toward more active student organizations who provide contact information publicly and routinely respond to inquiries. Inactive student organizations may have low levels of student engagement and few organized activities; therefore, these organizations may be underrepresented in our results. Future studies may mitigate this problem by engaging medical school activity coordinators, who may provide more recent contact information and status information on club inactivity.

Conclusions

New technologies and innovations are transforming medicine and clinical care. Efforts in exposing students to technology and innovation in medical school will prepare students for the changing landscape of medical practice. Our review of existing opportunities indicates both the growing interest in introducing trainees to medical I&T and the current challenges in integrating formalized curricular changes. Immediate and tangible future directions include increasing the visibility of current and future opportunities, achieving greater collaboration among schools, and establishing a national competency curriculum as well as a centralized platform that interested students and educators can use to share experiences.

Acknowledgments

The authors thank Boston Medical Center for helping to support this study.

Conflicts of Interest

None declared.

Multimedia Appendix 1

Student organization survey items and responses.

DOCX File , 18 KB

Multimedia Appendix 2

Word cloud generated from student organizations' mission statements.

PNG File , 170 KB

  1. Phillips AB, Merrill JA. Innovative use of the integrative review to evaluate evidence of technology transformation in healthcare. J Biomed Inform 2015 Dec;58:114-121 [FREE Full text] [CrossRef] [Medline]
  2. Morilla MDR, Sans M, Casasa A, Giménez N. Implementing technology in healthcare: insights from physicians. BMC Med Inform Decis Mak 2017 Jun 27;17(1):92 [FREE Full text] [CrossRef] [Medline]
  3. Thimbleby H. Technology and the future of healthcare. J Public Health Res 2013 Dec 01;2(3):e28 [FREE Full text] [CrossRef] [Medline]
  4. Erickson BJ, Korfiatis P, Akkus Z, Kline TL. Machine learning for medical imaging. Radiographics 2017;37(2):505-515 [FREE Full text] [CrossRef] [Medline]
  5. Feußner H, Ostler D, Wilhelm D. [Robotics and augmented reality : Current state of development and future perspectives]. Chirurg 2018 Oct;89(10):760-768. [CrossRef] [Medline]
  6. Berger MF, Mardis ER. The emerging clinical relevance of genomics in cancer medicine. Nat Rev Clin Oncol 2018 Jun;15(6):353-365 [FREE Full text] [CrossRef] [Medline]
  7. Mann DM, Chen J, Chunara R, Testa PA, Nov O. COVID-19 transforms health care through telemedicine: Evidence from the field. J Am Med Inform Assoc 2020 Jul 01;27(7):1132-1135 [FREE Full text] [CrossRef] [Medline]
  8. Ahuja V, Nair LV. Artificial intelligence and technology in COVID Era: A narrative review. J Anaesthesiol Clin Pharmacol 2021;37(1):28-34 [FREE Full text] [CrossRef] [Medline]
  9. Tilahun B, Gashu KD, Mekonnen ZA, Endehabtu BF, Angaw DA. Mapping the role of digital health technologies in prevention and control of COVID-19 pandemic: Review of the literature. Yearb Med Inform 2021 Aug;30(1):26-37 [FREE Full text] [CrossRef] [Medline]
  10. Medina M, Babiuch C, Card M, Gavrilescu R, Zafirau W, Boose E, et al. Home monitoring for COVID-19. Cleve Clin J Med. Epub ahead of print 2020 Jun 11 [FREE Full text] [CrossRef] [Medline]
  11. Luks AM, Swenson ER. Pulse oximetry for monitoring patients with COVID-19 at home. Potential pitfalls and practical guidance. Ann Am Thorac Soc 2020 Sep;17(9):1040-1046 [FREE Full text] [CrossRef] [Medline]
  12. Peacock S, Reddy A, Leveille SG, Walker J, Payne TH, Oster NV, et al. Patient portals and personal health information online: perception, access, and use by US adults. J Am Med Inform Assoc 2017 Apr 01;24(e1):e173-e177 [FREE Full text] [CrossRef] [Medline]
  13. Obermeyer Z, Emanuel EJ. Predicting the future - Big data, machine learning, and clinical medicine. N Engl J Med 2016 Sep 29;375(13):1216-1219 [FREE Full text] [CrossRef] [Medline]
  14. Law M, Veinot P, Campbell J, Craig M, Mylopoulos M. Computing for medicine: Can we prepare medical students for the future? Acad Med 2019 Mar;94(3):353-357 [FREE Full text] [CrossRef] [Medline]
  15. Charow R, Jeyakumar T, Younus S, Dolatabadi E, Salhia M, Al-Mouaswas D, et al. Artificial intelligence education programs for health care professionals: Scoping review. JMIR Med Educ 2021 Dec 13;7(4):e31043 [FREE Full text] [CrossRef] [Medline]
  16. Paranjape K, Schinkel M, Panday RN, Car J, Nanayakkara P. Introducing artificial intelligence training in medical education. JMIR Med Educ 2019 Dec 03;5(2):e16048 [FREE Full text] [CrossRef] [Medline]
  17. Petty E, Golden RN. Embracing innovation in medical education. WMJ 2017 Aug;116(3):179-180 [FREE Full text] [Medline]
  18. Sandars J, Murdoch-Eaton D. Appreciative inquiry in medical education. Med Teach 2017 Feb;39(2):123-127. [CrossRef] [Medline]
  19. Brown JF, Nelson JL. Integration of information literacy into a revised medical school curriculum. Med Ref Serv Q 2003;22(3):63-74. [CrossRef] [Medline]
  20. Silverman H, Cohen T, Fridsma D. The evolution of a novel biomedical informatics curriculum for medical students. Acad Med 2012 Jan;87(1):84-90. [CrossRef] [Medline]
  21. Sapci AH, Sapci HA. Artificial intelligence education and tools for medical and health informatics students: Systematic review. JMIR Med Educ 2020 Jun 30;6(1):e19285 [FREE Full text] [CrossRef] [Medline]
  22. Car LT, Kyaw BM, Panday RSN, van der Kleij R, Chavannes N, Majeed A, et al. Digital health training programs for medical students: Scoping review. JMIR Med Educ 2021 Jul 21;7(3):e28275 [FREE Full text] [CrossRef] [Medline]
  23. Critical data. MIT Critical Data. 2019.   URL: https://criticaldata.mit.edu/ [accessed 2020-09-15]
  24. Niccum BA, Sarker A, Wolf SJ, Trowbridge MJ. Innovation and entrepreneurship programs in US medical education: a landscape review and thematic analysis. Med Educ Online 2017;22(1):1360722 [FREE Full text] [CrossRef] [Medline]
  25. Carney PA, Palmer RT, Miller MF, Thayer EK, Estroff SE, Litzelman DK, et al. Tools to assess behavioral and social science competencies in medical education: A systematic review. Acad Med 2016 May;91(5):730-742 [FREE Full text] [CrossRef] [Medline]
  26. Koo K, Martin AN. Reimagining the behavioral and social sciences in medical education. Acad Med 2012 Sep;87(9):1151; author reply 1151-1151; author reply 1152. [CrossRef] [Medline]
  27. Rangel JC, Cartmill C, Kuper A, Martimianakis MA, Whitehead CR. Setting the standard: Medical education's first 50 years. Med Educ 2016 Jan;50(1):24-35. [CrossRef] [Medline]
  28. Accredited MD programs in the United States. Liaison Committee on Medical Education.   URL: https://lcme.org/directory/accredited-u-s-programs/ [accessed 2020-12-14]
  29. Leskin P. These are the 10 most innovative states in the U.S. Business Insider. 2019 Mar 21.   URL: https://www.businessinsider.com/most-innovative-states-in-united-states-dc-2019-3 [accessed 2020-12-14]
  30. ENMED – Engineering and medicine. Texas A&M University College of Engineering.   URL: https://enmed.tamu.edu/ [accessed 2022-01-01]
  31. 2021 FACTS: Applicants and matriculants data. Association of American Medical Colleges.   URL: https:/​/www.​aamc.org/​data-reports/​students-residents/​interactive-data/​2020-facts-applicants-and-matriculants-data [accessed 2020-12-15]
  32. Muoio D. Stanford Medicine: Physicians, medical students are interested in digital health, data-driven care. MobiHealthNews. 2020 Jan 16.   URL: https:/​/www.​mobihealthnews.com/​news/​stanford-medicine-physicians-medical-students-are-interested-digital-health-data-driven-care [accessed 2022-01-01]
  33. Briscoe GW, Arcand LGF, Lin T, Johnson J, Rai A, Kollins K. Students' and residents' perceptions regarding technology in medical training. Acad Psychiatry 2006;30(6):470-479. [CrossRef] [Medline]
  34. Avidan A, Weissman C, Zisk-Rony RY. Interest in technology among medical students early in their clinical experience. Int J Med Inform 2021 Sep;153:104512. [CrossRef] [Medline]
  35. MacNevin W, Poon E, Skinner TA. Technology readiness of medical students and the association of technology readiness with specialty interest. Can Med Educ J 2021 Apr 30;12(2):e31-e41 [FREE Full text] [CrossRef] [Medline]
  36. Edirippulige S, Gong S, Hathurusinghe M, Jhetam S, Kirk J, Lao H, et al. Medical students' perceptions and expectations regarding digital health education and training: A qualitative study. J Telemed Telecare. Epub ahead of print 2020 Jun 22. [CrossRef] [Medline]
  37. Wartman SA. The empirical challenge of 21st-century medical education. Acad Med 2019 Oct;94(10):1412-1415. [CrossRef] [Medline]
  38. Panchal A, Keim S, Ewy G, Kern K, Hughes KE, Beskind D. Development of a medical student cardiopulmonary resuscitation elective to promote education and community outreach. Cureus 2019 Apr 20;11(4):e4507 [FREE Full text] [CrossRef] [Medline]
  39. Boss A, Taylor SR, Coleman MD. Perceived benefit of a student-led journal club presentation in a pharmacotherapy module. Curr Pharm Teach Learn 2018 Aug;10(8):1132-1137. [CrossRef] [Medline]
  40. Khodabocus R, Tran K, Broom T, Razaq A. Breakfast club: a simple, reproducible, student education initiative. Med Educ 2015 Nov;49(11):1143-1144. [CrossRef] [Medline]
  41. Sayma M, Saleh D, Saleh K, Gaukroger A, Howard T, Hesford C, et al. Can medical students lead effective quality improvement initiatives? A systematic review. Am J Med Qual 2019;34(2):189-199. [CrossRef] [Medline]
  42. Han ER, Yeo S, Kim MJ, Lee YH, Park KH, Roh H. Medical education trends for future physicians in the era of advanced technology and artificial intelligence: an integrative review. BMC Med Educ 2019 Dec 11;19(1):460 [FREE Full text] [CrossRef] [Medline]
  43. Aboab J, Celi LA, Charlton P, Feng M, Ghassemi M, Marshall DC, et al. A "datathon" model to support cross-disciplinary collaboration. Sci Transl Med 2016 Apr 06;8(333):333ps8 [FREE Full text] [CrossRef] [Medline]
  44. Prober CG, Khan S. Medical education reimagined: a call to action. Acad Med 2013 Oct;88(10):1407-1410. [CrossRef] [Medline]
  45. Philippidis A. Top 10 U.S. biopharma clusters. Genetic Engineering & Biotechnology News. 2018 Sep 23.   URL: https://www.genengnews.com/a-lists/top-10-u-s-biopharma-clusters-6/ [accessed 2021-01-11]
  46. McCoy LG, Nagaraj S, Morgado F, Harish V, Das S, Celi LA. What do medical students actually need to know about artificial intelligence? NPJ Digit Med 2020 Jun 19;3:86 [FREE Full text] [CrossRef] [Medline]
  47. Chan KS, Zary N. Applications and challenges of implementing artificial intelligence in medical education: Integrative review. JMIR Med Educ 2019 Jun 15;5(1):e13930 [FREE Full text] [CrossRef] [Medline]
  48. Echelard JF, Méthot F, Nguyen HA, Pomey MP. Medical student training in eHealth: Scoping review. JMIR Med Educ 2020 Sep 11;6(2):e20027 [FREE Full text] [CrossRef] [Medline]
  49. Aungst TD, Patel R. Integrating digital health into the curriculum-Considerations on the current landscape and future developments. J Med Educ Curric Dev 2020 Jan 20;7:2382120519901275 [FREE Full text] [CrossRef] [Medline]
  50. Vassar L. How to equip new doctors for the digital health frontier. American Medical Association. 2015 Jun 18.   URL: https:/​/www.​ama-assn.org/​education/​accelerating-change-medical-education/​how-equip-new-doctors-digital-health-frontier [accessed 2022-01-01]
  51. How to prepare the future generation of physicians. The Medical Futurist. 2018 Jul 24.   URL: https://medicalfuturist.com/how-to-prepare-the-future-generation-of-physicians/ [accessed 2022-01-05]


I&T: innovation and technology


Edited by T Leung; submitted 18.07.21; peer-reviewed by JA Sánchez-Margallo, S Pesälä; comments to author 19.10.21; revised version received 14.01.22; accepted 22.02.22; published 31.03.22

Copyright

©Judy Jiaqi Wang, Rishabh K Singh, Heather Hough Miselis, Stephanie Nicole Stapleton. Originally published in JMIR Medical Education (https://mededu.jmir.org), 31.03.2022.

This is an open-access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work, first published in JMIR Medical Education, is properly cited. The complete bibliographic information, a link to the original publication on https://mededu.jmir.org/, as well as this copyright and license information must be included.