Improving Rates of Germline <i>BRCA</i> Mutation Testing for Patients With Ovarian Cancer in Vancouver Island, British Columbia, Canada
Bibliographic record
Abstract
PURPOSE Despite more than a decade of endorsement from multiple international cancer authorities advocating all women with ovarian cancer be offered germline breast cancer ( BRCA) gene testing, British Columbia Cancer Victoria was not meeting this target. A quality improvement project was undertaken with the aim of increasing completed BRCA testing rates for all eligible patients seen at British Columbia Cancer Victoria to > 90% by 1 year from April 2016. METHODS A current state analysis was completed, and multiple change ideas were developed, including education of medical oncologists, referral process update, initiating a group consenting seminar, and engagement of a nurse practitioner to lead the seminar. We used a retrospective chart audit from December 2014 to February 2018. On April 15, 2016, we initiated our Plan, Do, Study, Act (PDSA) cycles and completed them on February 28, 2018. We evaluated sustainability through an additional retrospective chart audit from January 2021 to August 2021. RESULTS Patients with completed germline BRCA genetic testing climbed from an average of 58%-89% per month. Before our project, patients waited on average 243 days (± 214) for their genetic test results. After implementation, patients received results within 118 days (± 98). This was sustained with an average of 83% of patients per month having completed germline BRCA testing almost 3 years after project completion. CONCLUSION Our quality improvement initiative resulted in a sustained increase in germline BRCA test completion for eligible patients with ovarian cancer.
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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 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".