SIMPLE procedures: Survey of Internal Medicine Providers' Limitations and Experiences with procedures and medical procedure services
Bibliographic record
Abstract
BACKGROUND: In response to a decline in bedside procedures performed by hospitalists, some hospital medicine groups have created medical procedure services (MPSs) concentrating procedures under the expertise of trained hospitalist-proceduralists. OBJECTIVES: To characterize the structure, breadth, and heterogeneity of academic medical center MPSs, as well as compare the procedural landscape for groups with and without an MPS. METHODS: The Survey of Internal Medicine Providers' Limitations and Experiences with Procedures and MPSs, is a cross-sectional study, conducted in the United States and Canada through a web-based survey administered from October 2022 to March 2023. We used convenience and snowball sampling to identify eligible study participants. The survey explored presence of MPS, procedure volumes, patient safety, and educational practices. For MPSs, we explored onboarding, staffing, skill maintenancy, funding, and barriers to growth. RESULTS: Forty institutions (response rate 97.5%), represented by members of the Procedural Research and Innovation for Medical Educators (PRIME) consortium participated in the survey. MPSs were found in 75% of the surveyed institutions. Most MPSs (97%) involved trainees and were staffed by internists (100%) who often had additional clinical duties (70%). The majority (83%) of MPSs used checklists and procedural safety guidelines, but only 53% had a standardized process for tracking complications. There was significant variability in determining procedural competency and supervising trainees. Groups with an MPS reported higher procedure volume compared to those without. CONCLUSIONS: MPSs were highly prevalent among the participating institutions, offered a broad array of bedside procedures, and often included trainees. There was a high variability in funding models, procedure volumes, patient safety practices, and skill maintenance requirements.
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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 | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".