Developing and evaluating new models of care in hematology.
Bibliographic record
Abstract
53 Background: The duration of care for patients with hematological malignancies (HM) from diagnosis to discharge can often be five years or longer, during which patients frequently visit their hematologist but may not maintain contact with their primary care physician (PCP). This can result in gaps in the care of non cancer health problems. A number of studies in solid tumors have highlighted the benefits of maintaining contact with the PCP however there has been little published on survivorship care in HM. Objective. Develop and evaluate models of care in hematology that facilitate transition to the PCP where appropriate. Methods: This study used a stepwise approach to inform the development and evaluation of care models. Models were developed using: a literature review; expert opinion; input from patient and PCP focus groups. The survivorship model (SM) was evaluated in a longitudinal, cohort of patients using validated patient surveys: Coordination of Cancer Care Questionnaire; Edmonton Symptom Assessment Scale; EQ5D-QoL. Results: Focus groups were conducted with 26 participants. Patients indicated they would be willing to engage with their PCP if primary care were more confident in their cancer care abilities, and if communication improved between specialty and PCP. PCPs felt care plans should be clear, concise and within their scope. Three new models of care were developed based on level of care need (survivorship, shared, engagement). The SM has been tested with 50 patients who have completed treatment and follow up. Survey results indicated the majority of SM patients: continued to feel well; reported high functioning; had seen their PCP since discharge; were satisfied with the coordination of their care. Fifteen PCPs responded to a follow up survey. PCPs were: satisfied with the SM care plan and aware of the repatriation process to specialty care, if needed. Conclusions: Patient involvement in model design was instrumental in the success of the project. PCPs reported that the tools developed in this pilot enhanced the care experience and provider collaboration. These findings warrant further testing of care models in a comparative study with this complex cancer population.
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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 | 0.004 |
| 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 | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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".