Interpretive Diagnostic Error Reduction in Surgical Pathology and Cytology: Guideline From the College of American Pathologists Pathology and Laboratory Quality Center and the Association of Directors of Anatomic and Surgical Pathology
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
CONTEXT: Additional reviews of diagnostic surgical and cytology cases have been shown to detect diagnostic discrepancies. OBJECTIVE: To develop, through a systematic review of the literature, recommendations for the review of pathology cases to detect or prevent interpretive diagnostic errors. DESIGN: The College of American Pathologists Pathology and Laboratory Quality Center in association with the Association of Directors of Anatomic and Surgical Pathology convened an expert panel to develop an evidence-based guideline to help define the role of case reviews in surgical pathology and cytology. A literature search was conducted to gather data on the review of cases in surgical pathology and cytology. RESULTS: The panel drafted 5 recommendations, with strong agreement from open comment period participants ranging from 87% to 93%. The recommendations are: (1) anatomic pathologists should develop procedures for the review of selected pathology cases to detect disagreements and potential interpretive errors; (2) anatomic pathologists should perform case reviews in a timely manner to avoid having a negative impact on patient care; (3) anatomic pathologists should have documented case review procedures that are relevant to their practice setting; (4) anatomic pathologists should continuously monitor and document the results of case reviews; and (5) if pathology case reviews show poor agreement within a defined case type, anatomic pathologists should take steps to improve agreement. CONCLUSIONS: Evidence exists that case reviews detect errors; therefore, the expert panel recommends that anatomic pathologists develop procedures for the review of pathology cases to detect disagreements and potential interpretive errors, in order to improve the quality of patient care.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.007 | 0.022 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.013 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 it