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Record Number of Anesthesiology Positions Filled in 2024 Match Year

2024· article· en· W4400983071 on OpenAlexaboutno aff
Jennifer Rock-Klotz, Thomas R. Miller

Bibliographic record

VenueASA Monitor · 2024
Typearticle
Languageen
FieldMedicine
TopicCardiac, Anesthesia and Surgical Outcomes
Canadian institutionsnot available
Fundersnot available
KeywordsAnesthesiologyMedicineAnesthesia

Abstract

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ASA's Center for Anesthesia Workforce Studies (CAWS) reports trends in anesthesiology resident matches based on the National Resident Matching Program (NRMP) Results and Data report published in May or June each year (asamonitor.pub/2Sm1t96). This report summarizes data on candidates who filled residency positions between 2005 and 2024. Resident match data prior to 2005 are available in the August 2018 ASA Monitor (ASA Monitor 2018;82:42-6). Match results signaled strong demand for anesthesiology residency programs. Key metrics include growth in the number of applicants and positions, increase in the percentages of positions filled, and almost 50% of applicants not matched. Overall, 4,533 candidates applied for 2,146 anesthesiology positions and filled all but two positions.a The total number of anesthesiology positions increased 13% between 2020 and 2024. Table 1 summarizes the total number of applicants and the type of candidates who matched into anesthesiology programs between 2015 and 2024 (e.g., U.S. allopathic seniors, osteopathic students or graduates, and international).a In 2024, 2,144 candidates matched, a 14% increase over 2020; it was the greatest number of matched candidates into the specialty in at least 50 years. The percentage of anesthesiology matches by U.S. allopathic seniors and osteopathic students or graduates ranges from 80%-85% between 2020 and 2024. For all other specialties, in aggregate, the percentage of matches by U.S. allopathic seniors and osteopathic students or graduates varied between 72%-75% between 2020 and 2024. From 2015 to 2017 the number of international medical graduates (IMGs) matched into anesthesiology increased substantially. In 2021, IMGs significantly decreased by 20% compared to 2020, and remained relatively flat, with a small increase in 2024 of 10%. In 2024, 9% of IMGs matched, compared to 11% in 2020.There have been only three years since 2005 where the number of candidates matched did not increase; the last time was in 2016. Between 2016 and 2024, the number increased by 34% (Figure 1), and is comparable to the number of matches increased in orthopedic surgery and general surgery programs in the same period, of 28% and 38%, respectively (not shown). In 2024, the number of anesthesiology applicants increased by 22% compared to 2020 (Figure 2). The number of anesthesiology programs more than doubled in the last two decades, with a reported 72 programs in 2005 and 178 programs in 2024 (data not shown).Since 2005, anesthesiology residency programs have filled more than 93% of positions each year. The anesthesiology position fill rate was greater than 99% from 2020 through 2024 match years (Figure 3). The anesthesiology position fill rate in 2024 was comparable to several specialties, including orthopedic surgery, diagnostic radiology, general surgery, neurology, obstetrics-gynecology, and psychiatry (Figure 4). Of those shown in the figure, family medicine had the lowest percentage of residency positions filled (88%).Trends in Ranking Applicants to PGY-1 Programs In 2024, all but one position was filled across PGY-1 anesthesiology programs, with 1,705 candidates matched. The number of PGY-1 anesthesiology positions increased 24% between 2020 and 2024 (not shown). When evaluating the percentage of non-matched candidates to PGY-1 programs with more than 200 ranking applicants in the 2024 match year, anesthesiology positioned 13th out of 26 total programs with 45% non-matched in PGY-1 programs (sorted in descending order). Emergency medicine had the lowest percentage of non-matched and (preliminary) obstetrics and gynecology had the highest, 19% versus 95%, respectively (not shown). Trends in anesthesiology resident match results are useful for indicating an increase to the supply pipeline and may represent a lagging indicator of demand for the specialty. Based on estimates by CAWS of CMS and other datasets, the supply increases have been enough to counter attrition (i.e., those that leave or retire), between 2018 and 2023, such that the supply of anesthesiologists has continued to increase. This report shows that the overall total number of matched candidates continues to grow; however, the percentage of matched U.S. allopathic seniors and osteopathic students or graduates has decreased by 3 percentage points in 2024 compared to 2023.The number of anesthesiology residency positions has almost doubled since 2005. The position fill rate in the last decade ranged between 94% and greater than 99% – reflecting a consistently strong preference for the specialty. a Historically, CAWS has included applicant counts based on NRMP reporting, however, further investigation by CAWS indicates that NRMP applicant counts do not capture the unique number of residency program applicants due to two mechanisms: First, only applicants (i.e., active applicants) that submit a certified rank order list of programs are represented, and second, applicants can match into a preliminary postgraduate year 1 (PGY-1) and advanced postgraduate year 2 / clinical anesthesia year 1 (PGY-2 / CA-1) in tandem (asamonitor.pub/3qTIhR2), which attributes to some double counting of applicants. To ensure that unique applicant counts are presented, this and future reports will include data based on supplemental information provided by the Association of American Medical Colleges (AAMC) Electronic Residency Application Service® (ERAS®) (asamonitor.pub/4bQkunJ).EXHIBIT Definitions of Applicant and Position Types Applicant Types 5th Pathway (Graduate of Fifth Pathway Program) – Graduate of a U.S. Fifth Pathway program. Canadian (Student/Graduate of Canadian Medical School) – Senior student or graduate of a Canadian school of medicine accredited by the Committee on Accreditation of Canadian Medical Schools (CACMS). Non-U.S. IMG (Non-U.S. Citizen Student/Graduate of International Medical School) – Non-U.S. citizen who attended an international medical school. Osteopathic Senior – Senior student of a medical school accredited by the Commission on Osteopathic College Accreditation (COCA). U.S. Grad (Previous Graduate of U.S. Allopathic or Osteopathic Medical School) –Either a graduate of a U.S. allopathic school of medicine accredited by the LCME with a graduation date before July 1 in the year before the Match (the medical school does not sponsor previous U.S. graduates), or a graduate of a medical school accredited by COCA. U.S. IMG (U.S. Citizen Student/Graduate of International Medical School) – U.S. citizen who attended an international medical school. U.S. Senior (Senior student of U.S. Allopathic Medical School) – Fourth-year medical student in a U.S. allopathic school of medicine accredited by the Liaison Committee on Medical Education (LCME) with a graduation date after July 1 in the year before the Match. U.S. seniors are sponsored by their medical schools. Program Types PGY-1 – Post-graduate year one programs. PGY-2/CA-1 – Post-graduate year two and/or clinical anesthesia year one programs. Physician (R) – Programs reserved for physicians who have had prior graduate medical education. Reserved programs offer PGY-2 positions that begin in the year of the Match and thus are not available to senior medical students. Jennifer A. Rock-Klotz, MBA, ASA Analytics and Research Services ManagerThomas R. Miller, PhD, MBA, ASA Director of Analytics and Research Services ASA Director of the Center for Anesthesia Workforce Studies

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How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.010
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.035
Threshold uncertainty score0.115

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.010
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0040.004
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0350.022

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 head0.012
GPT teacher head0.306
Teacher spread0.294 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreOther

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

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Citations2
Published2024
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