From what works to what matters: Whole person cancer care and the integrative oncology leadership collaborative (IOLC).
Bibliographic record
Abstract
e13567 Background: In 2021-2022, a two-year integrative oncology leadership collaborative ( IOLC ) was established with a goal to routinize whole person care. Thirteen cancer organizations met virtually 1-2x/month, including community, federal and academic centers. The IOLC defined whole person cancer care, adapted & tested open-source patient intake/PROs, education, and workflow resources from primary care, anchored in “what matters” for patients in oncology, and implemented practice change in their settings. Methods: Based on concepts and tools used in whole person primary care , and, with iterative discussion, the IOLC defined minimal required elements for whole person cancer care. Patient advocates, oncology social workers, physicians & nurses came together to draw from efforts that alleviate suffering in palliative, integrative, supportive, and other forms of (mostly) unreimbursed care. Six cancer survivor-advocate members vetted patient-facing resources. Subject matter experts reviewed topics important for clinical initiatives (e.g. group visit models , patient education resources ), shared best practices and solidified commitments to provide whole person care. To assess outcomes, a post-participation survey was fielded. Results: Minimal required elements (MREs) of whole person care were defined as: 1) inclusion of patient & caregiver voice in programming/care plans, 2) explicitly anchoring to “what matters” to the patient in shared decision making and goals of care (using PROs), and 3) supporting safe choices in complementary & integrative modalities. Challenges faced across organizations were: 1) leadership involvement, 2) patient understanding/engagement, 3) resource availability (time/financial), and 4) team alignment. Adaptation of primary care tools to oncology was successful; 15 “pocket guides” gained 2049 page views in 20 mos (top 3: cannabis 18%, nutrition 13%, patient advocacy 10%) and the American Cancer Society adopted the IOLC resources for distribution in 2024. Multi-institutional success occurred via publications and projects such as retooled nurse navigation, survivorship & wellness programs . Survey response rate was 54% (7 of 13 clinical sites). 89% increased whole person health services following IOLC participation (44% moderately or significantly). 100% reported use of the resources in patient care (55% often, 45% periodically). Conclusions: A definition of whole person cancer care, derived from broad consensus, identified MREs that allowed startup success across practice settings. An inclusive community of professionals & patients furthered whole person care with national impact, partnerships and culture change based on what matters to patients.
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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 | 0.014 | 0.042 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.004 | 0.005 |
| Open science | 0.001 | 0.009 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.016 | 0.001 |
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".