Chart based data as a resource for tracking and improving a <scp>person‐centred</scp> palliative approach in long‐term care
Bibliographic record
Abstract
AIMS AND OBJECTIVES: To enhance the practice of a person-centred palliative approach in long-term care. BACKGROUND: Implementing a person-centred palliative approach in long-term care entails placing residents at the centre of care planning that attends to the 'whole' person, rather than prioritising biomedical needs. DESIGN: We conducted a four-stage directed content analysis of long-term care progress notes to meet our study aims and applied the EQUATOR guidelines for qualitative research publication (COREQ). METHODS: We qualitatively analysed 78 resident charts across three long-term care homes in southern Ontario to capture the extent to which person-centred care was absent, initiated or implemented in different types of documented care interactions. RESULTS: Most residents had interactions related to daily care activities (65/78, 83%), social concerns (65/78, 83%) and treatment decisions (53/78, 68%). By contrast, interactions around pain and discomfort (34/78, 44%) and spirituality (27/78, 35%) were documented for less than half of the residents. Almost all (92%) residents had at least one progress note where staff initiated person-centred care by documenting their preference for a certain type of care, but only a third had at least one progress note that suggested their preference was implemented (35%). CONCLUSIONS: While person-centred care is often initiated by nurses and other allied health professionals, changes to care plans to address resident preferences are implemented less often. Nurses and other allied health professionals should be encouraged to elicit care preferences crucial for holistic care planning and equipped with the skills and support to enact collaborative care planning. RELEVANCE TO CLINICAL PRACTICE: Collaborative care planning appears relatively absent in charted progress notes, constraining the full implementation of a person-centred palliative approach to care. PATIENT OR PUBLIC CONTRIBUTION: An advisory group consisting of long-term care resident and staff representatives informed the overall study design and dissemination of the results.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 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".