Surgical Pathology Extradepartmental Consultation Practices
Bibliographic record
Abstract
OBJECTIVES: To document the practice parameters and case characteristics associated with personal (expert) consultations. We also examine the value, level of participant (customer) satisfaction, turnaround time, and rate of personal consultations. DESIGN: We asked participants in the College of American Pathologists' Q-Probes program to document cases sent for consultation during 4 months or up to 20 cases. They documented patient and specimen characteristics, the turnaround times, and the participants' levels of satisfaction with the consultation experience. PARTICIPANTS: One hundred eighty laboratories/surgical pathology practices. One hundred seventy-two (95.6%) were from the United States; the remainder were located in Canada and Australia. MAIN OUTCOME MEASURES: Rate and turnaround time of consultations and participant level of satisfaction. RESULTS: A total of 2746 consultation cases were examined for an aggregate consultation rate of 0.5% (median, 0.7%). Institutions with a higher occupied bed size and a greater number of surgical pathology cases both had lower consultation rates (P < or =.05). The median turnaround time (defined as the interval from the date on which the case was sent to the date on which the diagnosis was received) was 6 days. Twenty-nine percent and 68% of cases had a turnaround time within 3 and 7 days, respectively. Fifty-two percent of cases were sent to nationally known experts, and 32% were sent to local experts. Skin (18.0%), hematolymphoid (11.6%), and breast (9.6%) specimens were most commonly sent for consultation. In 70.5% of cases, the consultant confirmed the referring pathologist's original diagnosis, but in 15.9% of cases, the consultant also added significant information. Satisfaction rates were higher with faster turnaround times and verbal reporting. Satisfaction rates were lower for cases in which the patient or the clinician requested the consultation and in which the consultant's diagnosis was ambiguous. CONCLUSIONS: This study establishes a multi-institutional consultation rate of 0.5%, defines the nature of surgical pathology consultations, and demonstrates that satisfaction with consultations is associated with a faster turnaround time and receipt of additional, clinically meaningful information.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.014 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.016 | 0.002 |
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 source (direct Gemma or distilled Codex), 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".