The Ontario psychosocial oncology framework: a quality improvement tool
Bibliographic record
Abstract
OBJECTIVE: To overview the newly developed Psychosocial Health Care for Cancer Patients and Their Families: A Framework to Guide Practice in Ontario and Guideline Recommendations in the context of Canadian psychosocial oncology care and propose strategies for guideline uptake and implementation. METHOD: Recommendations from the 2008 Institute of Medicine standard Cancer Care for the Whole Patient: Meeting Psychosocial Health Needs were adapted into the Ontario Psychosocial Oncology (PSO) Framework. Existing practice guidelines developed by the Canadian Partnership against Cancer and Cancer Care Ontario and standards developed by the Canadian Association of Psychosocial Oncology are supporting resources for adopting a quality improvement (QI) approach to the implementation of the framework in Ontario. RESULTS: The developed PSO Framework, including 31 specific actionable recommendations, is intended to improve the quality of comprehensive cancer care at both the provider and system levels. Important QI change management processes are described as Educate - raising awareness among medical teams of the significance of psychosocial needs of patients, Evidence - developing a research evidence base for patient care benefits from psychosocial interventions, and Electronics - using technology to collect patient reported outcomes of both physical and emotional symptoms. CONCLUSIONS: The Ontario PSO Framework is unique and valuable in providing actionable recommendations that can be implemented through QI processes. Overall, the result will be improved psychosocial health care for the cancer population.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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 teacher head, 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".