Driving quality in delirium care through a patient-centered monitoring system in palliative care: Protocol for the two-staged exploratory sequential mixed methods MODEL-PC study
Bibliographic record
Abstract
Introduction Delirium is a serious acute neurocognitive condition that is common in palliative care units and yet under-addressed. To improve delirium care in this setting, we will develop and pilot a monitoring system that integrates the Delirium Clinical Care Standard, Palliative Care Outcomes Collaboration (PCOC) methods, and perspectives of patients, carers and staff. Methods This paper reports the protocol for a two-stage, exploratory, sequential mixed-methods implementation study. Stage 1 data collection includes Delirium Standard-aligned process mapping and clinical audits, and Critical Incident Technique interviews with patients, carers and staff with a recent experience of delirium. We will present integrated stage 1 findings to stakeholders then collaboratively develop a delirium monitoring system that aligns with the Delirium Standard and PCOC methods. In stage 2, we will pilot the new system and repeat stage 1 data collection and analyses, adding PCOC and adverse event measures. Implementation principles and strategies such as audit and feedback and education will be applied. We developed simplified participants information sheets and consent forms for interview and process mapping participants, who will provide written informed consent; and waiver of consent to collect clinical audit, PCOC and adverse event data from patients’ medical records is approved. At study end, we will report implementation, effectiveness and safety outcomes, including systemic utility of the delirium monitoring system for wider testing and use to meet the Delirium Standard in palliative care units. Quantitative data analyses will include descriptive and inferential statistics and qualitative analyses will incorporate thematic content analysis aligned to the Critical Incident Technique. Mixed methods data integration will be at the end of each stage. Discussion This protocol paper describes the mixed methods, systems integration, and innovative measures and study processes of the MODEL-PC study. We also share data collection tools and a simplified information sheet and consent form for 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 | 0.064 | 0.082 |
| Meta-epidemiology (narrow) | 0.004 | 0.003 |
| Meta-epidemiology (broad) | 0.004 | 0.007 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.004 | 0.003 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.005 | 0.004 |
| Research integrity | 0.004 | 0.006 |
| Insufficient payload (model declined to judge) | 0.058 | 0.010 |
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".