94DEVELOPING INTERNATIONAL STANDARDS FOR THE CARE OF OLDER PEOPLE IN THE EMERGENCY DEPARTMENT
Bibliographic record
Abstract
Introduction: Emergency departments (ED) across Canada acknowledge the need to transform in order to provide high quality care for the increasing proportion of older patients presenting for treatment. Older people are more complex than younger ED users. They have a disproportionately high use of EDs, increased rates of hospitalization, and are more likely to suffer adverse events. The objective of this initiative was to develop minimum standards for the care of older people in the emergency department. Methods: We created a panel of international leaders in geriatrics and emergency medicine to develop a policy framework on minimum standards for care of older people in the ED. We conducted a literature review of international guidelines, frameworks, recommendations, and best practices for the acute care of older people and developed a draft standards document. This preliminary document was circulated to interdisciplinary members of the International Federation of Emergency Medicine (IFEM) geriatric emergency medicine (GEM) group. Following review, the standards were presented to the IFEM clinical practice group. At each step, verbal, written and online feedback were gathered and integrated into the final minimum standards document. Results: Following the developmental process, a series of eight minimum standard statements were created and accepted by IFEM. These standards utilise the IFEM Framework for Quality and Safety in the ED, and are centred on the recognition that older people are a core population of emergency health service users whose care needs are different from those of children and younger adults. They cover key areas, including the overall approach to older patients, the physical environment and equipment, personnel and training, policies and protocols, and strategies for navigating the health-care continuum. Conclusions: These standards aim to improve the evaluation, management and integration of care of older people in the ED in an effort to improve outcomes. The minimum standards represent a first step on which future activities can be built, including the development of specific indicators for each of the minimum standards. The standards are designed to apply across the spectrum of EDs worldwide, and it is hoped that they will act as a catalyst to change.
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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 | 0.158 | 0.228 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.009 | 0.007 |
| Science and technology studies | 0.004 | 0.006 |
| Scholarly communication | 0.010 | 0.007 |
| Open science | 0.007 | 0.007 |
| Research integrity | 0.006 | 0.009 |
| Insufficient payload (model declined to judge) | 0.003 | 0.003 |
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".