25CONJ • 18/1/08 RCSIO • 18/1/08
Bibliographic record
Abstract
Care maps for patient care have been around for many years. Key stakeholders at our institution developed and implemented a care map for patients undergoing surgery for colorectal cancer. The purpose of this descriptive, qualitative pilot study was twofold. First was to understand the lived experience of patients being cared for under a newly-implemented care map utilizing patient diaries and interviews. The second goal was to describe the experiences of surgical oncology nurses caring for these patients using a focus group technique. The results of our small study indicated that patients appreciated having a document that outlines daily activities and goals, and were anxious to get home, but were disappointed in the discharge planning process. Nurses were positive about the care map overall, but felt they could have contributed more in the development and planning stages of the care map. Overall, the implementation of our patient-centred care map was a success. Publicly-funded health care systems, such as those in Canada, face increasing pressures to simultaneously harness the soaring costs associated with providing care to those who need it and providing that care in a timely manner. Since the new millennium, a key area of focus in Ontario has been reducing surgical “wait times ” in various populations, including those patients with cancer. Recent literature in the colorectal surgery population has suggested a median length of stay (LOS) of two days can be achieved (Basse, Hjort Jakobsen, Billesbolle,
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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 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.002 |
| Scholarly communication | 0.004 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.008 | 0.006 |
| Insufficient payload (model declined to judge) | 0.270 | 0.081 |
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".