Cross-sectoral video consultation in cancer care: GPs’ evaluation of a randomised controlled trial
Bibliographic record
Abstract
BACKGROUND: Shared care models present an opportunity for patients to receive the benefits of specialist care combined with the continuity of care provided by a GP. AIM: To test the effects on GP-perceived involvement in cancer care and their satisfaction with this cross-sectoral information after bringing the patient, GP, and oncologist together in a shared video consultation. DESIGN & SETTING: GPs from the Region of Southern Denmark evaluated a randomised controlled trial testing shared video consultations. METHOD: This study describes secondary outcomes based on a 4 months' follow-up survey from GPs participating in The Partnership Project (PSP). Patient perception of coordination of care at 7 months' follow-up was the primary outcome of the PSP. A tripartite video consultation was conducted during cancer treatment to share tasks and roles between health professionals with the patient. RESULTS: The study included 281 patients, and 105 unique GPs returned 124 questionnaires. Video consultations were accomplished in 68% of scheduled cases. The study found an increased odds ratio (OR) of 3.03 for GP satisfaction with the distribution of tasks and roles, and they experienced more involvement in the cancer patients' trajectory. The study found an increased OR of 6.95 for the GP perception of more direct contact and dialogue with the Department of Oncology. There was a decreased OR of 0.88 for the GP to be engaged in handling anxiety and psychological concerns. CONCLUSION: The study showed that involving the GP in one shared consultation increased the odds of the GP being satisfied with the distribution of tasks and roles, and feeling more involved in the cancer patient's trajectory. However, recruitment and response rates from GPs were limiting factors.
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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 | 0.012 | 0.028 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.006 | 0.004 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.005 | 0.003 |
| Insufficient payload (model declined to judge) | 0.008 | 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".