A Student-Led Clinical Informatics Enrichment Course for Medical Students

Introduction

Clinical informatics leverages data to integrate analytics and clinical decision-making with aims to improve the quality, safety, and cost effectiveness of care delivery.[1] Numerous examples of clinical decision support systems (CDSS) have been shown to aid clinicians in diagnosis, outcome prediction, and disease management. Examples include but are not limited to infectious disease diagnosis,[2] thrombosis prophylaxis,[3] perioperative pediatric management,[4] and neurosurgical outcome prediction.[5] Such systems have been shown to benefit patient safety by reducing the incidence of adverse events such as medication errors,[6] [7] [8] care quality by ensuring adherence to established treatment guidelines, and cost reduction[9] by automating processes and decreasing resource waste.[10] [11]

Clinical informatics is a formally recognized medical subspecialty[12] [13] with a multitude of applications and career opportunities as information technology becomes more intertwined with modern practices of medicine.[14] [15] Significant strides have been taken to integrate core clinical informatics competencies into medical education,[16] [17] [18] as studies have shown medical students desire both broad training in informatics and opportunities for career exploration.[19] [20] Examples include lecture-based online electives,[21] credit-based introductory medical informatics courses,[22] one-on-one faculty mentorship programs,[23] and isolated problem-based learning exercises.[24] While these examples demonstrate a growing emphasis on informatics education, they are limited with respect to number of participants and cohesive, clinically applicable skill-building that go beyond basic acquaintance of core concepts. To address this need, more integrated and contemporary informatics training seminars have recently emerged at institutions around the United States (i.e., New York University Langone Health,[25] University of California at San Francisco,[26] Oregon Health & Science University,[27] and Duke[28]). In this spirit, the authors—four second and third year medical students—designed and delivered a 12-week informatics enrichment elective for first and second year medical students at our institution. Our goal was to introduce clinically relevant informatics concepts and foster development of technical skills, so that participants could apply informatics into research projects and during their time on the wards. We welcome medical students with similar goals to reach out for additional information.

Protection of Human and Animal Subjects

The University of Texas Southwestern Medical Center Institutional Review Board determined this project to be exempt from further review as this activity did not meet the definition of research.

Publikationsverlauf

Eingereicht: 03. Januar 2022

Angenommen: 21. Januar 2022

Artikel online veröffentlicht:
02. März 2022

• References

• 1 Kim GR, Lehmann CU. In search of dialogue and discourse in applied clinical informatics. Appl Clin Inform 2009; 0 (01) 1-7
• 2 Peiffer-Smadja N, Rawson TM, Ahmad R. et al. Machine learning for clinical decision support in infectious diseases: a narrative review of current applications. Clin Microbiol Infect 2020; 26 (05) 584-595
• 3 Lau BD, Haider AH, Streiff MB. et al. Eliminating health care disparities with mandatory clinical decision support: the venous thromboembolism (VTE) example. Med Care 2015; 53 (01) 18-24
• 4 Wang E, Brenn BR, Matava CT. State of the art in clinical decision support applications in pediatric perioperative medicine. Curr Opin Anaesthesiol 2020; 33 (03) 388-394
• 5 Buchlak QD, Esmaili N, Leveque JC. et al. Machine learning applications to clinical decision support in neurosurgery: an artificial intelligence augmented systematic review. Neurosurg Rev 2020; 43 (05) 1235-1253
• 6 Miller MR, Clark JS, Lehmann CU. Computer based medication error reporting: insights and implications. Qual Saf Health Care 2006; 15 (03) 208-213
• 7 Kim GR, Chen AR, Arceci RJ. et al. Error reduction in pediatric chemotherapy: computerized order entry and failure modes and effects analysis. Arch Pediatr Adolesc Med 2006; 160 (05) 495-498
• 8 Lehmann CU, Conner KG, Cox JM. Preventing provider errors: online total parenteral nutrition calculator. Pediatrics 2004; 113 (04) 748-753
• 9 Stenner SP, Chakravarthy R, Johnson KB. et al. ePrescribing: reducing costs through in-class therapeutic interchange. Appl Clin Inform 2016; 7 (04) 1168-1181
• 10 Sick AC, Lehmann CU, Tamma PD, Lee CK, Agwu AL. Sustained savings from a longitudinal cost analysis of an internet-based preapproval antimicrobial stewardship program. Infect Control Hosp Epidemiol 2013; 34 (06) 573-580
• 11 Sutton RT, Pincock D, Baumgart DC, Sadowski DC, Fedorak RN, Kroeker KI. An overview of clinical decision support systems: benefits, risks, and strategies for success. NPJ Digit Med 2020; 3: 17
• 12 Detmer DE, Shortliffe EH. Clinical informatics: prospects for a new medical subspecialty. JAMA 2014; 311 (20) 2067-2068
• 13 Lehmann CU, Gundlapalli AV, Williamson JJ. et al. Five years of clinical informatics board certification for physicians in the United States of America. Yearb Med Inform 2018; 27 (01) 237-242
• 14 Ohno-Machado L. Careers in informatics: a diversity of options with an abundance of jobs. J Am Med Inform Assoc 2012; 19 (06) 919
• 15 Kannry J, Sengstack P, Thyvalikakath TP. et al. The Chief Clinical Informatics Officer (CCIO): AMIA task force report on CCIO knowledge, education, and skillset requirements. Appl Clin Inform 2016; 7 (01) 143-176
• 16 Hersh WR, Gorman PN, Biagioli FE, Mohan V, Gold JA, Mejicano GC. Beyond information retrieval and electronic health record use: competencies in clinical informatics for medical education. Adv Med Educ Pract 2014; 5: 205-212
• 17 Kaufman DM, Jennett PA. Preparing our future physicians: integrating medical informatics into the undergraduate medical education curriculum. Stud Health Technol Inform 1997; 39: 543-546
• 18 Otto A, Kushniruk A. Incorporation of medical informatics and information technology as core components of undergraduate medical education - time for change!. Stud Health Technol Inform 2009; 143: 62-67
• 19 Briscoe GW, Fore Arcand LG, Lin T, Johnson J, Rai A, Kollins K. Students' and residents' perceptions regarding technology in medical training. Acad Psychiatry 2006; 30 (06) 470-479
• 20 Beaudoin DE, Richardson SJ, Sheng X, Mitchell JA. Medical students' perspectives on biomedical informatics learning objectives. Int J Med Educ 2013; 4: 1-8
• 21 Burnette MH, De Groote SL, Dorsch JL. Medical informatics in the curriculum: development and delivery of an online elective. J Med Libr Assoc 2012; 100 (01) 61-63
• 22 Feldman SS, Hersh W. Evaluating the AMIA-OHSU 10 × 10 program to train healthcare professionals in medical informatics. AMIA Annu Symp Proc 2008; 2008: 182-186
• 23 Green EP, Borkan JM, Pross SH. et al. Encouraging scholarship: medical school programs to promote student inquiry beyond the traditional medical curriculum. Acad Med 2010; 85 (03) 409-418
• 24 Burgun A, Darmoni S, Duff FL, Wéber J. Problem-based learning in medical informatics for undergraduate medical students: an experiment in two medical schools. Int J Med Inform 2006; 75 (05) 396-402
• 25 Health NL. Introduction to clinical informatics elective. Accessed December 26, 2021 at: https://med.nyu.edu/education/md-degree/registration-student-records/elective-catalog/interdepartmental/introduction-to-clinical-informatics
• 26 Clinical informatics and data science pathway. Accessed December 26, 2021 at: https://meded.ucsf.edu/residents-clinical-fellows/gme-educational-professional-development-opportunities/gme-pathways/clinical-informatics-and-data-science-pathway#Curriculum-Overview
• 27 Hersh W. Clinical informatics medical student elective. Accessed December 26, 2021 at: https://dmice.ohsu.edu/hersh/minf705B709A.html
• 28 Informatics DCfH. Informatics elective for medical students. Accessed December 26, 2021 at: https://dukeinformatics.org/education/health-informatics-programs-available-at-duke/informatics-for-medical-students/
• 29 Smith SR, Bakshi R. Promoting resident involvement in quality improvement initiatives through faculty involvement and curriculum. J Grad Med Educ 2015; 7 (01) 119-120
• 30 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; 3: 86
• 31 Williams MS, Taylor CO, Walton NA. et al. Genomic information for clinicians in the electronic health record: lessons learned from the clinical genome resource project and the electronic medical records and genomics network. Front Genet 2019; 10: 1059
• 32 Valerius J, Mohan V, Doctor D, Hersh W. Collaboration leads to enhanced curriculum. Appl Clin Inform 2015; 6 (01) 200-209
• 33 Zackoff MW, Real FJ, Abramson EL, Li ST, Klein MD, Gusic ME. Enhancing educational scholarship through conceptual frameworks: a challenge and roadmap for medical educators. Acad Pediatr 2019; 19 (02) 135-141
• 34 Bleackley J, Kim SYR. The merit and agony of retrospective chart reviews: a medical student's perspective. BC Med J 2013; 55 (08) 374-375
• 35 Worster A, Haines T. Advanced statistics: understanding medical record review (MRR) studies. Acad Emerg Med 2004; 11 (02) 187-192
• 36 Benè KL, Bergus G. When learners become teachers: a review of peer teaching in medical student education. Fam Med 2014; 46 (10) 783-787
• 37 Yu TC, Wilson NC, Singh PP, Lemanu DP, Hawken SJ, Hill AG. Medical students-as-teachers: a systematic review of peer-assisted teaching during medical school. Adv Med Educ Pract 2011; 2: 157-172
• 38 Ten Cate O, Durning S. Peer teaching in medical education: twelve reasons to move from theory to practice. Med Teach 2007; 29 (06) 591-599
• 39 Omar F, Zaheer M, Ahmed M. Effectiveness of peer teaching in medical education: medical student's perspective. Adv Med Educ Pract 2018; 9: 199-201
• 40 Nelson AJ, Nelson SV, Linn AM, Raw LE, Kildea HB, Tonkin AL. Tomorrow's educators … today? Implementing near-peer teaching for medical students. Med Teach 2013; 35 (02) 156-159