Fall prevention strategy in an emergency department
Bibliographic record
Abstract
Purpose The purpose of this paper is to document the need for implementing a fall prevention strategy in an emergency department (ED). The paper also spells out the research process that led to approving an assessment tool for use in hospital outpatient services. Design/methodology/approach The fall risk assessment tool was based on the Morse Fall Scale. Gender mix and age above 65 and 80 years were assessed on six risk assessment variables using χ 2 analyses. A logistic regression analysis and model were used to test predictor strength and relationships among variables. Findings In total, 5,371 (56.5 percent) geriatric outpatients were deemed to be at fall risk during the study. Women have a higher falls incidence in young and old age categories. Being on medications for patients above 80 years exposed both genders to equal fall risks. Regression analysis explained 73-98 percent of the variance in the six-variable tool. Originality/value Canadian quality and safe healthcare accreditation standards require that hospital staff develop and adhere to fall prevention policies. Anticipated physiological falls can be prevented by healthcare interventions, particularly with older people known to bear higher risk factors. An aging population is increasing healthcare volumes and medical challenges. Precautionary measures for patients with a vulnerable cognitive and physical status are essential for quality care.
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How this classification was reachedexpand
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 | 0.003 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".