Early integration of palliative care in a long-term care home: A telemedicine feasibility pilot study
Bibliographic record
Abstract
OBJECTIVE: Palliative care plays an essential role in enhancing the quality of life and quality of death for residents in long-term care homes (LTCHs). Access to palliative care specialists is one barrier to providing palliative care to LTCHs. This project focused on palliative telemedicine, specifically evaluating whether integration of early palliative care specialist consultation into an LTCH would be feasible through the implementation of videoconferencing during routine interdisciplinary care conferences. METHOD: This was a mixed-methods evaluation of a pilot program implementation over 6 months, to integrate early palliative care into an LTCH. There were two pilot communities with a total of 61 residents. Resident demographics were collected by a chart review, and palliative telemedicine feasibility was evaluated using staff and family member surveys. RESULTS: For the 61 residents, the average age of the residents was 87 years, with 61% being female and 69% having dementia as the primary diagnosis. The mean CHESS (Change in Health, End-Stage Disease, Signs, and Symptoms) and ADL (Activities of Daily Living) scores were 0.8 and 4.0, respectively, with 54% having a Palliative Performance Scale score of 40. Seventeen clinical staff surveys on palliative teleconferences were completed with the majority rating their experience as high. Ten out of the 20 family members completed the palliative teleconference surveys, and the majority were generally satisfied with the experience and were willing to use it again. Clinical staff confidence in delivering palliative care through telemedicine significantly increased (P = 0.0021). SIGNIFICANCE OF RESULTS: The results support the feasibility of videoconferencing as a means of palliative care provision. Despite technical issues, most clinical staff and families were satisfied with the videoconference and were willing to use it again. Early integration of palliative care specialist services into an LTCH through videoconferencing also led to improved self-rated confidence in the palliative approach to care by clinical staff.
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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 | 0.010 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".