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Record W3144166270 · doi:10.7759/cureus.14301

The Effect of Single Accreditation on Medical Student Match Rates in Surgical Specialties

2021· article· en· W3144166270 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueCureus · 2021
Typearticle
Languageen
FieldSocial Sciences
TopicDiversity and Career in Medicine
Canadian institutionsHeritage College
Fundersnot available
KeywordsAccreditationMedicineOtorhinolaryngologyOrthopedic surgeryGraduate medical educationFamily medicineMedical educationSurgery

Abstract

fetched live from OpenAlex

Introduction The year 2020 marked the first year in which a match under single accreditation took place. Both osteopathic (DO) and allopathic (MD) students would participate in the first match cycle without a dedicated DO match system. Our primary objective was to investigate how single accreditation has impacted the DO applicants attempting to match into surgical specialties. Our secondary objective was to investigate the impact of single accreditation at the program director (PD) level and whether or not this process would see a change in DO PD distribution in previously American Osteopathic Association (AOA)-approved programs. Method Information on number of applicants and post-match positions was gathered from AOA and National Residency Match Program (NRMP) websites. Credentials of PDs were obtained from the Accreditation Council on Graduate Medical Education website. Based on the available data, the following surgical specialties were compared for the years 2020, 2018, and 2016: General Surgery, Neurological Surgery (NSGY), Orthopedic Surgery, Otolaryngology/ENT (ENT), Plastic Surgery, and Thoracic Surgery. Data from 2016 were not included in the results as the AOA match results analysis was insufficient and unable to be directly compared to the NRMP data. Results of matched DO and MD applicants were compared using bivariate analysis. A p-value of <0.05 was considered significant. Results From the year 2018 to 2020, the DO applicants saw a decrease of 3% in the total number of matched postgraduate year 1 spots in surgical specialties. NRMP results from 2020 saw that 51.7% of DO applicants matched and 67.7% (p < 0.001) of MD applicants matched for the specialties examined. Percent of matched:applied for DO applicants was lower than MD applicants in the fields of NSGY (p < 0.001), ENT (p < 0.001), Plastic Surgery (p < 0.001), General Surgery (p < 0.001), and Thoracic Surgery (p = 0.011). After evaluating 60 former AOA General Surgery programs, 56% were found to have MD as PD. Another 26 former AOA surgical programs were investigated, and 58% were found to have MD PD. Conclusion Single accreditation has impacted the match process now that a large number of both MD and DO applicants are using the NRMP match system for postgraduate placement. Based on the available data, our results indicate that in the examined surgical specialties, there is a statistically significant difference in the number of MD and DO residents.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.487
Threshold uncertainty score0.433

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.023
GPT teacher head0.357
Teacher spread0.334 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it