Developing a Frailty Care Pathway for Older Adults in Long-Term Care: A Modified Delphi Process
Bibliographic record
Abstract
OBJECTIVE: We developed a clinical care pathway for the detection and management of frailty for older adults living in long-term care (LTC) homes. METHODS: We utilized a modified Delphi with residents of LTC homes experiencing frailty, their caregivers, and care providers. The pathway was created using existing literature and input from key LTC experts. FINDINGS: Fifty-two panelists completed round one of the Delphi, and 55.8% of these respondents completed round two. Both rounds had high agreement and ratings. We added six new statements following analysis of round two, and 15 statements were modified/updated to reflect panelist feedback. The final pathway included 28 statements and promotes a resident-centered approach that highlights caregiver involvement and inter-professional teamwork to identify and manage frailty, as well as initiate palliative care earlier. CONCLUSION: Implementing this pathway will allow health care providers to adopt screening measures and adapt care to a resident's frailty severity.
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 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 | 0.140 | 0.092 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.004 | 0.002 |
| Science and technology studies | 0.007 | 0.004 |
| Scholarly communication | 0.003 | 0.004 |
| Open science | 0.003 | 0.013 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".