Academic Medicine, the flagship journal of Association of American Medical Colleges (AAMC) recently published an article advocating for a lottery-based residency match system to replace the current match system that, in the authors’ words, emphasize “a narrow set of comparative achievements—standardized test performance, publication counts, and honor society memberships.”
The article, written by several authors including the Associate Dean for Admissions at Stanford University School of Medicine, starts out with the premise that this more merit-oriented approach is actually harmful to medical education.
Instead, the authors argue that residency programs should adopt a “modified lottery” system in which applicants who are deemed “qualified” by their medical schools are assigned, through an algorithm, to interview with certain residency programs.
The crux of the argument is as follows:
“We argue that the current residency selection process must be upended to achieve several important aims: facilitating the implementation of [competency-based medical education], promoting a growth mindset among students, eliminating the use of metrics that foster harmful bias, ensuring optimal preparation for patient care, and improving equality within the selection process.”
Notice the sections on “bias” and “equality.”
And here’s the kicker: the authors argue that this process should include diversity objectives so that residency programs can achieve their DEI goals.
“Inclusion of diversity-related programmatic outcomes in the modified lottery process could help align applicants and programs with similar interests in caring for diverse patient populations, advancing health equity, or promoting inclusive practices,” the authors write.
To be clear, it is not the lottery itself that is the issue. Indeed, Do No Harm’s founder Dr. Stanley Goldfarb explained in National Review how, in the context of medical school admissions, instituting a lottery system past a certain threshold of academic achievement would prevent racial preferences in admissions while ensuring that medical schools preserve merit.
Each medical school should announce a minimum MCAT score and undergraduate GPA necessary for admission, then institute a lottery system for applicants who clear those bars. This approach would not only end racial discrimination overnight — it would also strongly incentivize medical schools to admit the best-qualified students.
Instead, it is the article’s premise that more merit-oriented methods of selection should be devalued, and that the lottery process should be used to achieve DEI goals, that is disturbing. It’s a system in which “good enough” replaces “the best” for selecting into the most competitive training programs.
The authors give the game away elsewhere in the paper, arguing that more achievement-oriented metrics of residency selection “confer demonstrable bias (e.g. racial, ethnic, gender, and/or socioeconomic), potentially limiting the entrance of applicants with identities considered underrepresented in medicine into residency positions.”
How, exactly, merit-based metrics of selection confer bias while consideration of diversity objectives does not is anyone’s guess.
Additionally, the article is remarkably light on details as to what counts as a qualified applicant, instead calling for widespread adoption of a standardized “programmatic assessment.”
“In order for a modified lottery for interviews to be successful, this would require UME institutions to agree upon a set of outcomes to determine qualification and develop rigorous programmatic assessment to ensure those outcomes are met,” the authors write.
But apparently the “standardized test performance, publication counts, and honor society memberships” are excluded from the qualification discussion? This doesn’t make much sense.
In short, the article’s proposal would indeed upend residency selection, but make it much less fair. Objective measures of academic excellence would be devalued, and non-academic considerations would be promoted.
We shouldn’t gamble on the future of medicine like this.
