ACGME Requirements for Geriatrics Medicine Curricula in Medical Specialties: Progress Made and Progress Needed
Bibliographic record
Abstract
In the recent past, most physician visits by older adults were with a primary care physician, with less than 40% of ambulatory visits to other specialists. Since 1991, that trend has reversed. In 2001, 53% of ambulatory visits by patients aged 65 years or older were to nonprimary care specialists. Demographic trends and an expanding geriatrics medicine knowledge base require that every physician develop skills specific to the care of older adults. There are concerns that physicians-in-training are not learning adequate specific geriatrics medicine content to prepare them for the rapidly expanding numbers of older adults who will be seeking medical care. Training standards to prepare residents and fellows for practicing medicine are established by experts in the various medical specialties serving on individual residency review committees (RRCs) of the Accreditation Council for Graduate Medical Education. In 2002 (with a follow-up in 2003), the Association of Directors of Geriatric Academic Programs' team at the University of Cincinnati School of Medicine's Institute for Health Policy and Health Services Research reviewed all 91 nonpediatric specialties' RRC program requirements to identify the specific curriculum requirements related to geriatrics medicine training. As of 2003, 27 of the 91 RRC-accredited specialties have specific geriatrics training requirements; the other 70% of these specialties did not specifically mention geriatrics training. Even among the specialties with specific geriatrics training requirements, curriculum expectations are modest. The geriatrics-specific descriptions within the program requirements of the 27 specialties are presented in this article. The authors encourage the RRCs for all nonpediatric specialties to update their program requirements to ensure that future physicians graduating from their graduate medical education programs are adequately prepared to care for older adults.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.006 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.003 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; both teacher heads agree on what is shown here.
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".