Management of Fall-Related Injuries in the Elderly: A Retrospective Chart Review of Patients Presenting to the Emergency Department of a Community-Based Teaching Hospital
Bibliographic record
Abstract
PURPOSE: To identify current practice for elderly individuals who have sustained a fall-related injury and subsequently presented to the emergency department (ED) of a community-based hospital in Toronto, Ontario. METHODS: A retrospective longitudinal chart review was conducted for 300 persons, 65 years of age and older, who presented to the ED of a community-based teaching hospital with a fall from June 2004 through May 2005. Data were collected using a tool created by the investigators (based on information gathered through a literature review) to capture information related to risk factors for falling. RESULTS: Our study sample was demographically similar to elderly individuals in other fall-related studies. Most patients discharged directly from the ED did not receive multidisciplinary care. In the ED, all patients saw a nurse or physician, while only 1.3% (n = 4) saw a physical therapist, 3.0% (n = 9) saw an occupational therapist, and 5.3% (n = 16) saw a social worker. At discharge, 62% (n = 152) had no documented referral for follow-up care. Abilities related to falls in elderly individuals were not consistently assessed in the ED. Frequency of assessment for these abilities was as follows: (1) gait, 10.2%; (2) balance, 4.1%; (3) lower-extremity range of motion, 4.9%; (4) lower-extremity strength, 2.0%; (5) cognition, 26.1%; (6) vision, 2.0%; (7) ability to perform activities of daily living, 7.3%. In the 6 months following the index fall, 8.3% of patients returned to the ED of the same hospital because of a subsequent fall. CONCLUSIONS: In the ED, fall-related risk factors were not consistently assessed or documented, and few patients received multidisciplinary management. Since elderly individuals who fall commonly present to the ED, the implementation of evidence-based strategies aimed at preventing repeat falls should be considered.
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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 | 0.001 | 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 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".