Abstracts from the 35th Annual Scientific Meeting of the Canadian Geriatrics Society, Montreal, April 2015
Bibliographic record
Abstract
Optimizing heath care services for seniors in emergency departments (ED) is a core component of the "Senior Friendly Hospital Approach" being implemented in Quebec.We measured the availability of geriatric expertise in Quebec EDs and its relationship with ED characteristics such as university affiliation, number of stretchers, and geographical location.We surveyed (2013-2014) head nurses and head physicians at 116 adult, non-psychiatric Quebec EDs.We defined high level of availability in the three following components of geriatric expertise: 1) geriatric care coordinatioN = a designated clinician coordinating the care of older adults available every day; 2) multidisciplinarity = 4 or 5 different nonmedical professionals, i.e., specialized nurse, social worker, occupational therapist, physiotherapist, and pharmacist, available almost always/often (nursereported); and 3) geriatric consultation = a specialist or a general practitioner specialized in geriatrics available almost always/often (physician-reported).We performed descriptive analyses and Fisher's exact test.Among participating EDs (N = 83), 73 (88%) nurses and 67 (81%) physicians participated in the survey.18% of EDs had high level of geriatric care coordination, 41% provided high level of multidisciplinarity, and 33% received high level of geriatric consultation.We found that EDs that had greater number of stretchers were more likely to have high level of geriatric care coordination (p < .05)and consultation (p < .001).EDs in metropolitan areas were also more likely to receive high level of geriatric consultation (p < .01).High level of multidisciplinarity was not associated with any ED characteristics.2/5 of Quebec EDs provide high level of multidisciplinarity varying in their characteristics, whereas smaller and non-metropolitan EDs lack geriatric care coordination and consultation.There is a need for reorganisation and finding innovative ways to use existing human resources in Quebec EDs.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.002 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.268 | 0.063 |
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".