Coordination of Radiologic and Clinical Care Reduces the Wait Time to Breast Cancer Diagnosis
Bibliographic record
Abstract
Background: In 2009, a Rapid Access Breast Clinic (RABC) was opened at our urban hospital. Compared with the traditional system (TS), the navigated care through the clinic was associated with a significantly shorter time to surgical consultation. Since 2009, many radiology facilities have introduced facilitated-care pathways for patients with breast pathology. Our objective was to determine if that change in diagnostic imaging pathways had eliminated the advantage in time to care previously shown for the RABC. Methods: All patients seen in the RABC and the office-based TS in November–December 2012 were included in the analysis. A retrospective chart review tabulated demographic, surgeon, pathology, and radiologic data, including time intervals to care for all patients. The results were compared with data from 2009. Results: In 2012, time from presentation to surgical consultation was less for the RABC group than for the TS group (36 days vs. 73 days, p < 0.001) for both malignant (31 days vs. 55 days, p = 0.008) and benign diagnoses (43 days vs. 79 days, p < 0.001). Comparing the 2012 results with results from 2009, a decline in mean wait time was observed for the TS group (86 days vs. 73 days, p = 0.02). Compared with patients having investigations in the TS, RABC patients with cancer were more likely to undergo surgery within 60 days of presentation (33% vs. 15%, p = 0.04). Conclusions: The coordination of radiology and clinical care reduces wait times for diagnosis and surgery in breast cancer. To achieve recommended targets, we recommend implementation of more systematic coordination of care for a breast cancer diagnosis and of navigation to surgeons for patients needing surgical care.
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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 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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 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".