Transition care clinic: Evidence-based survivorship care.
Bibliographic record
Abstract
141 Background: The Odette Cancer Centre (OCC) is the sixth largest comprehensive cancer centre in North America. In 2012/2013 fiscal year it is projected there will be 19,633 new cases and 82,293 follow-up visits, of which 16% of new and 24% of follow-ups will be for gastrointestinal (GI) and hematology disease sites. Current specialty cancer clinics are not well equipped to provide evidence-based survivorship care. Methods: The Transition Care Clinic (TCC) was developed for colorectal cancer and lymphoma patients transitioning from acute care at OCC back to their primary care provider (PCP) for follow-up, assessment, and surveillance after completion of active treatment. Patients are seen by a family medicine physician and advanced practice nurse and receive comprehensive survivorship care, individualized treatment summaries, and post-treatment care plans. An accompanying web resource continues to connect patients to OCC after discharge and provides survivorship specific information. Results: An eight month pilot resulted in 66 visits and 28 discharges, of which 53% of visits and 93% of discharges were for GI patients and 47% and 7% respectively for hematology. The 28 discharges resulted in resource utilization savings of 122 OCC clinic visits and 118 hospital CT scans. Symptom screening results across the domains of anxiety, depression, pain, and tiredness were on par with other cancer patients, dispelling concern that these patients experience different/more symptoms after treatment and during transition. Finally, patient feedback indicated that those that found it difficult to attend OCC appointments appreciated knowing guidelines were available and were comfortable with PCP follow-up, while others whose PCP missed initial presenting symptoms preferred cancer centre “specialists” and were not comfortable. Conclusions: There is need for inter-disciplinary development of survivorship and transition programs with buy-in from disease sites, multimodality consensus, revision of eligibility criteria for lymphoma, and efficiencies to complete comprehensive treatment summaries. Short and long-term outcomes to be measured include recurrences and secondary cancers, adherence to guidelines, patient quality of life, and satisfaction.
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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 | 0.003 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.035 | 0.007 |
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".