An innovative approach to post-treatment cancer care: The After Cancer Treatment Transition Clinic (ACTT).
Bibliographic record
Abstract
e19522 Background: Improvements in early detection and cancer therapy have led to better survival rates. Integration of cancer survivorship initiatives as part of cancer care is gaining momentum. However, post cancer treatment follow up care may not be best met in acute cancer clinics. Visits to a large urban cancer centre in Canada have increased by 30% in the past 5 years. These increased volumes have lead to prolongation of patient wait times and increased stress for health care providers. This cancer centre is undergoing a transformative change that focuses on improving the patient cancer care experience. Methods: The development of the ACTT clinic has been a partnered initiative between two academic healthcare centres: an urban cancer centre and a community ambulatory hospital with a focus in chronic disease management. It is being managed by an advanced practice nurse and a GP Oncologist. The ACTT clinic delivers high quality, safe specialized physician and advanced nursing patient care, with engagement of patients/families, oncologists and primary care. The target population is patients who have completed cancer therapy, are well and are at moderate to low risk for cancer recurrence. The initial phase of the project involved transitioning patients with Testes, Melanoma, Breast and Colorectal cancers. Each cancer site group identifies the appropriate processes for clinic functioning at the ACTT, and if required, for appropriate linkages back to acute cancer care and primary care. Results: Over 1,000 patients have been transitioned to ACTT since April 2010 with 10-20 additional patients referred weekly. Essential components of the model include: standard surveillance protocols for recurrence or secondary cancers, management of long term and late effects of cancer treatment, monitoring for distress and health promotion. Standard reporting includes patient assessment and a defined plan of care communicated to their oncologist and primary care. Patient experience evaluation of the program is ongoing. Conclusions: The ACTT clinic initiative has been successful in developing a novel clinic model and has successfully transitioned over 1,000 patients from an acute care cancer clinic.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.083 | 0.008 |
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".