The Evaluation of a Fall Management Program in a Nursing Home Population
Bibliographic record
Abstract
PURPOSE OF THE STUDY: This study evaluates a nursing home Fall Management program to see if residents' mobility increased and injurious falls decreased. DESIGN AND METHODS: Administrative health care use and fall occurrence report data were analyzed from 2 rural health regions in Manitoba, Canada, from June 1, 2003 to March 31, 2008. A quasiexperimental, pre-post, comparison group design was used to compare rates of three outcomes, falls, injurious falls, and falls resulting in hospitalization, by RHA (program vs nonprogram nursing homes) and period (preprogram vs postprogram). Data collectors entered occurrence report information into spreadsheets. This was supplemented with administrative health care use data. RESULTS: The program appears to have benefitted residents-falls trended upward, injurious falls remained stable, and hospitalized falls decreased significantly (0.036-0.021 per person-year [ppy]; p = .043). Compared with nonprogram residents in the postperiod, both groups had the same fall rate, but program residents had significantly fewer injurious falls (0.596-0.746 ppy; p = .02) and hospitalized falls (0.02-0.041 ppy; p = .023). IMPLICATIONS: These results are among a small body of literature showing that Fall Management was associated with improved outcomes in program nursing homes from pre- to postperiod and compared with nonprogram nursing homes. This research provides some support for the benefits of being proactive and implementing injury prevention strategies universally and pre-emptively before a resident falls, helping to minimize injuries while keeping residents mobile and active. Larger scale research is needed to identify the true effectiveness of the Fall Management program and generalizability of results.
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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 | 0.002 | 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".