Study protocol: optimization of complex palliative care at home via telemedicine. A cluster randomized controlled trial
Bibliographic record
Abstract
BACKGROUND: Due to the growing number of elderly with advanced chronic conditions, healthcare services will come under increasing pressure. Teleconsultation is an innovative approach to deliver quality of care for palliative patients at home. Quantitative studies assessing the effect of teleconsultation on clinical outcomes are scarce. The aim of this present study is to investigate the effectiveness of teleconsultation in complex palliative homecare. METHODS/DESIGN: During a 2-year recruitment period, GPs are invited to participate in this cluster randomized controlled trial. When a GP refers an eligible patient for the study, the GP is randomized to the intervention group or the control group. Patients in the intervention group have a weekly teleconsultation with a nurse practitioner and/or a physician of the palliative consultation team. The nurse practitioner, in cooperation with the palliative care specialist of the palliative consultation team, advises the GP on treatment policy of the patient. The primary outcome of patient symptom burden is assessed at baseline and weekly using the Edmonton Symptom Assessment Scale (ESAS) and at baseline and every four weeks using the Hospital Anxiety and Depression Scale (HADS). Secondary outcomes are self-perceived burden from informal care (EDIZ), patient experienced continuity of medical care (NCQ), patient and caregiver satisfaction with the teleconsultation (PSQ), the experienced problems and needs in palliative care (PNPC-sv) and the number of hospital admissions. DISCUSSION: This is one of the first randomized controlled trials in palliative telecare. Our data will verify whether telemedicine positively affects palliative homecare. TRIAL REGISTRATION: The Netherlands National Trial Register NTR2817.
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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 | 0.016 |
| Meta-epidemiology (narrow) | 0.005 | 0.002 |
| Meta-epidemiology (broad) | 0.010 | 0.004 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.003 | 0.001 |
| Research integrity | 0.006 | 0.004 |
| Insufficient payload (model declined to judge) | 0.060 | 0.007 |
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".