Ultrasound-Guided Transrectal Prostate Biopsy: An Evidence-Based Process Report for an Acute Care Community Hospital
Bibliographic record
Abstract
Background and Purpose: Clearly designed processes improve patient care and department efficiency. A formative process evaluation is used to strengthen a service, improve outcomes, or increase program efficiency. A community hospital in Southern Ontario completed such an evaluation of its ultrasound-guided prostate biopsy service. During a prostate biopsy, tissue samples for cancer diagnosis are obtained. The Canadian Cancer Society estimated that 22,300 men would be diagnosed with prostate cancer and approximately 4,300 would die in 2007. Timely access to diagnostic and treatment services is critical for the reduction of prostate cancer mortality and morbidity. An evaluation of the ultrasound-guided prostate biopsy service was undertaken to identify possible strategies to reduce wait times from 6 months to 6 weeks and identify service improvements. Hospitals are accountable for the efficient and effective use of resources. This evaluation was designed to provide evidence-based data to identify ways to improve resource use. Methods: A literature review, stakeholder interviews, and comparator hospital survey were conducted to identify stakeholder needs and to determine industry standards and opportunities for service improvement and access. Results: The results suggest a need for revisions of the booking process, patient information service, and pain management strategies, as well as staff realignment, policy and procedure updates, and a process to evaluate outcomes. Conclusion: This process evaluation successfully identified service improvements that may reduce the wait time from 6 months to 6 weeks.Therapeutic Uses of Ultrasound-Guided Microbubbles: A Review of Current Research
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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 | 0.096 | 0.126 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.008 | 0.006 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.006 | 0.003 |
| Open science | 0.003 | 0.004 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.001 | 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".