MEASURING THE IMPACT OF THE GEM NURSING ROLE IN THE EMERGENCY DEPARTMENT SETTING
Bibliographic record
Abstract
With older adults increasingly becoming significant users of emergency department services, the creation of a Geriatric Emergency Management (GEM) Nursing Role has been one response to improve the overall delivery of care to older adults 65+ at higher risk of admission. In 2009, Mount Sinai Hospital established such a role and subsequently expanded it to a 7-day a week service with additional nurses. During the 2014/15 fiscal year we evaluated the impact of the care our GEM Nurses provided on ED Visitors 75+ whom they saw versus those who they didn’t. In 2014/15 they saw a total of 1024 patients, 783 who were 75+. Patients seen were more likely to arrive by ambulance and be more medically complex. Through proactive screening and engagement with appropriate community supports, GEM nurses contributed to a total of 17 avoidable hospital admissions, 195 avoidable hospital days that led to $189,000 saved for the hospital alone in a 12 month period.
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 | 0.015 | 0.036 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.002 |
| 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".