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Supporting Learner Transition to Residency: Match Day Resources

Written by Admin | Mar 16, 2025 11:29:30 PM

Match Day – the day that marks both a thrilling and nerve-wracking milestone for medical learners. It represents the culmination of years of hard work, sacrifices, and unwavering dedication. For most, it’s the defining moment when they finally find out where they’ll continue their training post-graduation. But for others, it can be a period of uncertainty.

In a recent community virtual discussion held among Elentra member institutions, we delved into a variety of topics related to Match Day, including comparisons between the United States and Canadian versions of the process, how the pandemic universally impacted approaches to the process, and how artificial intelligence is shaping it today.

 

Similarities and Differences Between the US and Canada

The Match process can seem complex, but at its core, it's about aligning medical learners with residency programs. Both the US and Canada follow a structured process, but with key differences in how unmatched learners are handled.

In the US, learners who don't match with a program can enter the Supplemental Offer and Acceptance Program (SOAP). This is a critical opportunity for unmatched learners to find available positions in residency programs, though the process is fast-paced and can be stressful. On the other hand, Canada follows a similar concept through running a second iteration of the initial Match Day process, giving unmatched learners another shot at securing a spot in residency. However, the second iteration in Canada differs in terms of timing and how programs and learners interact during the process.

 

The Impact of COVID-19 on the Interview Process

One of the most significant shifts in the medical Match process occurred during the COVID-19 pandemic. The traditional in-person interviews were replaced with virtual formats, a change that had lasting effects on how candidates and programs interacted. In our community discussion, we explored how this new interview format affected learners, programs, and faculty alike and whether some of these changes may be permanent in the future.

For many learners, virtual interviews have leveled the playing field, reducing the barriers of travel costs and time constraints. However, it also posed challenges in making a genuine connection with the program’s faculty, fellow applicants, and the institution’s culture. This shift led to a reevaluation of how interviews can be conducted to ensure both sides—learners and programs—can make well-informed decisions.

 

How Artificial Intelligence (AI) is Transforming the Match Process

With advancements in technology, the Match process is evolving. One of the most exciting areas we discussed during the webinar was the potential role of artificial intelligence (AI) in improving the overall process for both residency programs and learners.

For residency programs, AI can help analyze large data sets to streamline decision-making processes, such as selecting candidates based on criteria that align with the program’s objectives. Additionally, AI tools can assist with scheduling interviews, making it easier for both programs and candidates to manage their time effectively.

But AI’s role doesn’t stop there. Medical learners can benefit from AI-driven tools when it comes to crafting personal statements, helping them tailor their applications to highlight their strengths in the most compelling way. Faculty, too, can leverage AI when writing letters of recommendation for learners, ensuring that these letters are thorough, clear, and aligned with the program’s expectations.

However, while AI offers significant benefits, there are also challenges to consider. One concern is the potential for bias in the algorithms. AI systems are trained on existing data, which may inadvertently perpetuate biases present in that data. If the historical data used to train AI systems reflects past biases in the match, the algorithm may unintentionally replicate these biases in its recommendations. This raises concerns about fairness and equity, particularly when it comes to underrepresented groups in medicine.

 

Creative Ways to Celebrate Learners 

During our virtual community event, we discussed how different schools celebrate Match Day, and one school shared an interesting tradition. They explained that each learner brings $5 to the stage, contributing to a pot. The last learner to have their match announced is then given the entire pot as a reward. In addition, the school adds a bit of fun to the process with walk-on music for each learner as they make their way to the stage to hear their match. It’s a creative way to build excitement and add some lightheartedness to what is often a nerve-wracking day for learners.

 

Match Day Resources 

Elentra is pleased to share the following Match Day resource list which, though originally created for the use of Elentra member institutions to deepen their understanding of the Match process and its various components, may be helpful to any individuals or teams who are seeking greater understanding of the Match Day process, related practices, and example guides publicly-available from numerous institutions. Mirroring the highlights of our community discussion, these resources cover both the US and Canadian systems, the impact of COVID-19 on the interview process, and the role of AI in shaping the future of residency applications.

If you are interested in learning more about Elentra or becoming part of our community, please get in touch or sign up to receive notifications of public webinars we offer in the future.

 

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Learner-specific Resources 

Resource

Description

Overview of AAMC ERAS

Association of American Medical Colleges. (n.d.). ERAS for Institutions: Medical Schools.

Retrieved from www.aamc.org
/services/eras-for-institutions   

This section of the AAMC's ERAS website provides medical schools with resources to assist students with residency applications, including guides on the Supplemental Offer and Acceptance Program (SOAP).

ERAS Resources

Association of American Medical Colleges. (n.d.). ERAS® Resources for Medical Schools.

Retrieved from www.aamc.org
/services/eras-for-institutions/medical-schools/resources   

This resource provides medical schools with guides, checklists, and schedules to assist students in preparing for the National Resident Matching Program (NRMP) Main Residency Match, including information on the Supplemental Offer and Acceptance Program (SOAP).

Overview of the National Residency Matching Program (NRMP)

National Residency Matching Program. (n.d.). Medical Schools.

Retrieved from www.nrmp.org /medical-schools/

This page provides essential information for medical schools, including how they can participate in the residency matching process and resources available for students applying for residency programs.

Supporting Medical Students for Match Day

Association of American Medical Colleges. (n.d.). Transition to Residency Resources for Students.

Retrieved from www.aamc.org /about-us/mission-areas/medical-education/transition-residency/transition-residency-resources-students

This resource provides comprehensive materials to help medical students transition into residency, including ERAS guidance, interview preparation, and organizational checklists.

Your Path to Medical Residency

Saba University School of Medicine. (2025). Plan Your Path to Medical Residency: Guide for Students.

Retrieved from www.saba.edu/ blog/plan-your-path-to-medical -residency-guide-for-students

This guide offers insights into the residency application process, including steps to prepare for residency placements, tips for USMLE success, and strategies for securing competitive residencies.

Getting Into a Residency Program

American Academy of Family Physicians. (n.d.). The Match: Getting Into a Residency Program.

Retrieved from www.aafp.org /students-residents/medical-students /become-a-resident/match.html

This guide, "Strolling Through the Match," offers detailed information on the residency match process, including guidance on application preparation, interview strategies, and insights into matching with family medicine residency programs.

Strolling Through the Match

Citation: American Academy of Family Physicians. (n.d.). Strolling Through the Match.

Retrieved from www.aafp.org/students-residents/medical-students/become-a-resident/match/strolling-through-the-match.html

This annual guide by the AAFP offers a detailed overview of the residency match process, including application timelines, interview strategies, and ranking tips for students and advisors.

Tips for Unmatched Learners

American Medical Association. (n.d.). What If You Don’t Match? 4 Things You Should Do.

Retrieved from www.ama-assn.org/ medical-students/preparing-residency/what-if-you-don-t-match-4-things-you-should-do

This article offers practical advice for medical students who do not match into a residency program, outlining four key steps they can take to navigate the situation and improve their chances in subsequent match cycles.

Faculty Development Resources

Resource

Description

Toolkit for Reentering the Residency Application Process

American Association of Colleges of Osteopathic Medicine. (2024). Toolkit to Support Students Reentering the Residency Application Process.

Retrieved from www.aacom.org/docs/default-source/residency-gme/toolkit-for-support-student-re-entering-residency_final.pdf

This toolkit offers guidance for faculty and advisors assisting osteopathic medical students who are reentering the residency application process, providing strategies to support their success.

A Faculty Member’s Guide to Supporting Students Through the National Residency Match

University of British Columbia. (2024). A Faculty Member's Guide to Supporting Students Through the National Residency Match.

This guide provides faculty members with strategies and advice for supporting medical students through the complex process of the National Residency Match, focusing on mentoring and helping students prepare for match day.

Supporting Medical Learners

Dalhousie University. (2023). Supporting Medical Learners: CaRMS Match Day.



This document offers guidance to faculty members on how to effectively support medical learners during the CaRMS Match Day, addressing the emotional and logistical challenges students face during this high-stakes time.

Match Day Process Resources

Resource

Description

How the NRMP Matching Algorithm Works

National Residency Matching Program. (n.d.). How  the Matching Algorithm Works.

Retrieved from www.nrmp.org /intro-to-the-match/how-matching- algorithm-works/

This page provides an overview of the NRMP’s matching algorithm, explaining how it pairs medical school graduates with residency programs based on mutual preferences and program rankings.

Residency Match Applicant Journey

YouTube. (2023). 2023 Main Residency Match Applicant Journey.

Retrieved from www.youtube.com /watch?list=PLr0LH_NifZSoJXb6 WviDphNHwBi-1V1nL&v=2tSaV5WtXlQ

This video provides insights and guidance for medical students preparing for the NRMP  Match Day, featuring tips on managing the process and expectations around the match results

How the CaRMS Match Algorithm Works

YouTube. (2023). How the Match Algorithm works.

Retrieved from www.youtube.com/watch?v=28CvXJ_DcGo

This video explains how the Canadian Resident Matching Service (CaRMS) Match Algorithm works, providing a detailed breakdown of how residency matches are made for Canadian medical students, and helping applicants better understand the process behind the allocation of residency positions.

Virtual Interviewing Resources

Resource

Description

Virtual Residency Interviews During the COVID-19 Pandemic

Lee E, Terhaar S, Shakhtour L, Gerhard E, Patella M, Singh R, Zapanta PE. Virtual Residency Interviews during the COVID-19 Pandemic: The Applicant's Perspective. South Med J. 2022 Sep;115(9):698-706. doi: 10.14423-SMJ.0000000000001442.
PMID: 36055658; PMCID: PMC9426311.

Retrieved from https://pmc.ncbi.nlm.nih.gov
/articles/PMC9426311/
 

This article examines how virtual residency interviews during the COVID-19 pandemic affected applicants, highlighting both the benefits, like cost savings, and challenges, such as limited interactions and difficulty assessing program culture.

Benefits and Downsides of Virtual Residency Interviews

American Association of Medical Colleges. (2021, November 30). Do the benefits of virtual residency interviews outweigh the downsides?

Retrieved from www.aamc.org/news/ do-benefits-virtual-residency-interviews-outweigh-downsides 

This article evaluates the pros and cons of virtual residency interviews, discussing their accessibility and financial benefits, alongside challenges like evaluating program fit and culture remotely.

Match Day + Artificial Intelligence Resources

Resource

Description

AI Revolutionizing the Match Day Process

American College of Surgeons. (2025, February). How can AI revolutionize the Match Day process? Bulletin of the American College of Surgeons.

Retrieved from www.facs.org/for-medical-professionals/news-publications/news-and-articles/bulletin/2025/ february-2025-volume-110-issue-2/how-can-ai-revolutionize-the-match-day-process/

This article explores the potential of artificial intelligence (AI) to transform the residency match process, discussing how AI could streamline administrative tasks, improve decision-making, and reduce biases in applicant selection, ultimately enhancing the efficiency and fairness of Match Day.

How to Tell if ChatGPT Wrote Content

Harding, X. Did ChatGPT write this? Here’s how to tell. Mozilla. Published April 14, 2023. Accessed April 23, 2023.

Retrieved from https://foundation.mozilla.org
/en/blog/
how-to-tell-chat-gpt-generated-text/

This article provides guidance on how to identify whether text has been generated by ChatGPT, offering practical tips and tools for distinguishing between human-written and AI-generated content. It discusses the challenges and importance of recognizing AI-authored material in the context of academic integrity and online content creation.

Applications of AI in Graduate Medical Education

Mangold S, Ream M. Artificial Intelligence in Graduate Medical Education Applications. J Grad Med Educ. 2024 Apr;16(2):115-118. doi: 10.4300/JGME-D-23-00510.1. Epub 2024 Apr 15. PMID: 38993314; PMCID: PMC11234320.

Retrieved from
https://pmc.ncbi.nlm.nih.gov/articles/
PMC11234320/
 

This article examines how AI can enhance the residency application process by improving efficiency, reducing bias, and aiding in applicant evaluation while also addressing ethical concerns and challenges.