Hematology/Oncology Fellowship Programs' Participation in the Quality Oncology Practice Initiative
Bibliographic record
Abstract
PURPOSE: In the first decade of this millennium, ASCO pioneered a quality measurement tool, the Quality Oncology Practice Initiative (QOPI). Despite an Accreditation Council for Graduate Medical Education (ACGME) requirement since 2012 for oncology fellows to participate in quality improvement (QI) projects, the uptake of QOPI remains modest. METHODS: This study examined reasons for low QOPI participation by surveying participating and nonparticipating HemOnc Fellowship Programs. The survey elicited views toward QI and QOPI as well as ideas about making the program more helpful. RESULTS: Among 69 fellowship programs, only 39% (n = 27) participated in QOPI. Other findings were that (1) the majority of programs considered their fellows' QI projects beneficial but were not fulfilling the ACGME standard for all fellows' QI participation; (2) nonparticipating programs were unfamiliar with but interested in QOPI; (3) participating programs tended to view QI as easier to conduct and more beneficial than nonparticipating programs; and (4) programs that withdrew from QOPI and participating programs alike were dissatisfied with the educational benefit and data abstraction burden for fellows. CONCLUSION: Academic oncology programs generally valued QI but many have not fully engaged in it. Fellows in programs participating in QOPI may have had less difficulty conducting QI and their projects may have been more beneficial than that of nonparticipating programs. However, perceived lack of educational benefits for fellows and the burden of manual data abstraction from the electronic medical record are impediments to satisfaction with the program. Higher faculty involvement and longitudinal reports for each fellow may significantly increase participation.
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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 | 0.014 | 0.016 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.004 |
| Insufficient payload (model declined to judge) | 0.001 | 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; a candidate call from one teacher head, not a consensus.
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".