A Long-Term Care—Comprehensive Geriatric Assessment (LTC-CGA) Tool: Improving Care for Frail Older Adults?
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
BACKGROUND: Most older adults living in long-term care facilities (LTCF) are frail and have complex care needs. Holistic understanding of residents' health status is key to providing good care. Comprehensive Geriatric Assessment (CGA) is a valid assessment method which aims to embrace complexity. Here we aimed to study a CGA that has been modified for use in long-term care (the LTC-CGA) and to investigate its acceptability and usefulness to stakeholders and users. METHODS: This mixed methods study, conducted in 10 LTCFs in Halifax, Nova Scotia, reviewed 598 resident charts from pre- and post-implementation of the LTC-CGA. Qualitative methods explored stakeholder perspectives (physicians, nurses, paramedics, administrators, residents and families) though focus groups. RESULTS: The LTC-CGA was present in 78% of LTCF charts in the post -implementation, period though it did not appear in acute care charts of transferred residents, despite the intention that it accompany residents between care sites. Some items had suboptimal completion rates (e.g., Advance Directives at 56.4%), though these were located in other sections of the LTCF chart (98.2%). Nevertheless, qualitative findings suggest the LTC-CGA describes a clinical baseline health status which enabled timely and informed clinical decision-making. CONCLUSIONS: The LTC-CGA is a useful resource whose full capacity may not yet have been realized.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| 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 it