Analysis of the suitability of 'video-visits' for palliative home care: implications for practice
Bibliographic record
Abstract
We conducted a retrospective chart review to estimate the extent to which palliative home care visits could be carried out using videophones and to explore factors that might inform the eligibility criteria for video-visits. Four hundred palliative home care health records of deceased clients from 2002 were randomly selected from the Health Records Office in one Canadian health region. One visit was randomly selected from each of these health records. Three hundred and fifty-four visits were coded, and based on professional nursing judgment, the coder estimated whether video-visits could have been carried out. Approximately 43% of the visits were considered appropriate for video-visits. The results suggest that four factors may inform eligibility and decisions about a client's suitability for video-visits: diagnosis (cancer versus non-cancer), low Edmonton Symptom Assessment System (ESAS) score, no care-giver present, number and types of interventions required. Patients with a cancer diagnosis were more likely to be suitable for video-visits, which suggests that disease trajectory, rather than diagnosis of 'palliative', may be more influential in determining the care required and appropriateness of videophone use.
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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 | 0.035 | 0.177 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.004 | 0.005 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".