The Case for Transparency in the Ophthalmology Residency Match
Authors: Daniel L. Liebman, Grayson W. Armstrong, Ankoor S. Shah, Alice C. Lorch, Joan W. Miller, James Chodosh
Journal: Ophthalmology (2020)

Each fall, hundreds of medical students and residency program faculty begin the process of pairing prospective ophthalmologists with the training programs best suited to guide their professional growth. “The Match” represents an enormous investment of time and resources for all involved; those who undertake it share a mutual, deep-seated goal to build the next generation of competent and caring ophthalmologists. For graduating medical students who have chosen ophthalmology as their professional path, the choice of where to train is their most consequential career decision to date. Cognizant that residency programs vary widely in their relative strengths and educational experiences, applicants must weigh a range of factors as they formulate their rank lists. Common considerations include program size, geographic location, balance of clinical and research training, training site characteristics, alumni placement, subspecialty exposure, and surgical case load and mix, as well as personal factors such as perceived cultural “fit.”1Venincasa M.J. Cai L.Z. Gedde S.J. et al.Current applicant perceptions of the ophthalmology residency match.JAMA Ophthalmol. 2020; 138: 460-466Crossref PubMed Scopus (7) Google Scholar Unfortunately, in seeking to evaluate and differentiate programs, many applicants encounter a match process that can be deeply opaque. Residency websites and interview day presentations offer a smattering of statistics and program highlights, but the depth and type of available data are inconsistent from program to program. Consequently, most applicants must use alternative sources of information such as internet chatrooms, residency blogs, and alumni, despite the resulting information often being outdated, biased, impossible to verify, or a combination thereof. The information vacuum also has led to the widespread use of rankings calculated by third parties, such as Doximity’s Residency Navigator and Ophthalmology Times’ Best Programs Survey. Unfortunately, the data underlying these calculations are not necessarily reliable and can be weighted heavily by reputation and other nebulous considerations.2Lorch A.C. Miller J.W. Kloek C.E. Accuracy in residency program rankings on social media.J Grad Med Educ. 2019; 11: 127-128Crossref PubMed Scopus (2) Google Scholar In the end, most applicants turn to faculty mentors for help regarding where to apply, interview, and rank. Mentors strive to offer accurate and impartial advice to their mentees, but they, too, rely predominantly on either second-hand knowledge based on interactions with other programs’ faculty or first-hand recollections that may be outdated. Plainly stated, our current matching system pushes applicants to make critical decisions based primarily on word of mouth, hearsay, and chance encounters. It is no small irony that after 4 years of medical school training steeped in the principles of evidence-based medicine and data-driven decision making, prospective ophthalmologists must make their biggest decision yet without the benefit of objective data. This is certainly not a problem unique to ophthalmology; the issue of data paucity in the residency matching process has been noted across medicine writ large.3Gruppuso P.A. Adashi E.Y. Residency placement fever: is it time for a reevaluation?.Acad Med. 2017; 92: 923-926Crossref PubMed Scopus (22) Google Scholar Fortunately, our specialty has a well-established reputation as a leader in the application of data-driven insights to drive improvements, from establishing and capitalizing on one of the nation’s first and largest clinical disease registries to our boundary-expanding work in artificial intelligence and machine learning.4American Academy of OphthalmologyIRIS® Registry.https://www.aao.org/iris-registryGoogle Scholar,5Ting D.S.W. Pasquale L.R. Peng L. et al.Artificial intelligence and deep learning in ophthalmology.Br J Ophthalmol. 2019; 103: 167-175Crossref PubMed Scopus (263) Google Scholar Especially now, as the coronavirus disease 2019 pandemic introduces further uncertainty into the residency application and interview process, we believe the time is ripe for ophthalmology to apply this same data-driven spirit to the process by which we prepare the next generation of ophthalmologists. An ideal match process would feature informed decision making for all participants. The match algorithm is well equipped to harmonize applicants’ and programs’ rank lists; the key is to ensure that these rank lists accurately reflect participants’ best self-determined interests. Programs have access to detailed qualitative and quantitative profiles of each applicant with which to formulate their rank lists; we envision a future where applicants’ lists are similarly well informed. Be it through programs’ websites or through central clearinghouses, prospective trainees should have the means to compare and contrast data across residencies easily on the topics that matter most to their professional goals. For some, this may mean granular data on patient populations and subspecialty surgical exposures. For others, this may mean markers of resident success such as board pass rates, fellowship matches, or recent alumni job placements. For the academically inclined, this may mean grant funding and faculty research output. Gender balance, minority representation, and other metrics of diversity are likely to be of interest as well. Regardless of data category, the common thread is a movement toward standardization and transparency for all programs. It is important to note that such a transition would not likely impose additional burdens on residency programs and staff; programs already generate a wide range of data provided to an array of accrediting, licensing, and affiliate organizations. These include the American Board of Ophthalmology, the Accreditation Council for Graduate Medical Education, the San Francisco MATCH system, the Association of University Professors of Ophthalmology, and the American Academy of Ophthalmology. Such reporting includes details on residents’ clinical activities, surgical volumes, performance on standardized testing, fellowship match results after residency, and specialty board pass rates. Beyond this, most programs collect additional internal data far in excess of reporting requirements, tracking residents’ clinical performance, departmental research funding and productivity, and job placement after residency. Thus, making such data available to applicants is not a matter of feasibility, but simply of collective willingness. We argue that data transparency is a worthwhile pursuit in its own right and that a general culture of openness and transparency would benefit all, including those who have made it their life’s work to educate the next generation of physicians. Indeed, research in education repeatedly has shown that data transparency improves outcomes for both the educated and the educators.6Winkelmes M.-A. Transparency in teaching: faculty share data and improve students’ learning.Liberal Education. 2013; 99: 48-55Google Scholar That said, we recognize that there exists something of a reverse prisoner’s dilemma when it comes to the practical aspects of voluntarily releasing one’s own data. Given that inevitably there will be data elements for all programs that are less than flattering in some respect, institutional politics make it difficult to be the first to engage. This tendency has been recognized by the federal government in its own ongoing efforts to promote transparency in the public education sphere, with legislation such as the Every Student Succeeds Act of 2015 sidestepping such reticence by making reporting of metrics both standardized and mandatory.7United States Department of EducationEvery Student Succeeds Act (ESSA).https://www.ed.gov/essaGoogle Scholar Thus, to mitigate pressure on any given program, the most likely path forward will entail accrediting and oversight organizations promulgating data for all programs simultaneously.8Gawande A. The health-care bell curve: what happens when patients find out how good their doctors really are? The New Yorker.https://www.newyorker.com/magazine/2004/12/06/the-bell-curveDate accessed: December 6, 2019Google Scholar Encouragingly, several of these organizations already have demonstrated interest and ability in public reporting. Most notably, starting in the 2020 application cycle, the Association of University Professors of Ophthalmology and the San Francisco MATCH system will provide data on certain basic elements for all residency programs, derived from a survey of all United States ophthalmology residencies. These data will be available to all applicants and will include details on class size, internship type, inclusion of a Veterans Affairs facility, number of faculty and fellows by specialty, surgical volumes for cataract and selected other procedures, and percentages of recent graduates pursuing fellowship or private practice. We recognize that these data alone will not solve the issue of transparency; many additional professional and personal factors play into applicants’ decisions beyond what fits on an Excel (Microsoft) spreadsheet. Further, we acknowledge that data sharing can carry risks of compromising individual residents’ privacy if not carried out properly and the possibility of applicants overemphasizing particular data points if not accompanied by appropriate context. Nevertheless, it is our hope that these initial efforts will lay the groundwork for thoughtful further data transparency initiatives, both by overarching entities and residencies themselves.8Gawande A. The health-care bell curve: what happens when patients find out how good their doctors really are? The New Yorker.https://www.newyorker.com/magazine/2004/12/06/the-bell-curveDate accessed: December 6, 2019Google Scholar Data transparency in health care remains a hot-button issue on many fronts, from clinical outcomes to hospital costs. We believe that within the realm of residency education, too, an important role for data transparency exists. Applicants entrusting their professional futures to a program deserve a robust array of data points by which to make their decision. Likewise, educators seeking to honor that trust deserve applicants who have made a conscientious and fully informed decision in committing to their programs’ educational and clinical responsibilities. We envision a transparent matching process that enhances program–trainee fit, laying the groundwork to prepare the next generation of ophthalmologists optimally and furthering our profession’s ultimate mission to treat and prevent blindness and ophthalmic disease.