The evaluation of a Fall Management Program in a personal care home (PCH) population
Bibliographic record
Abstract
Injurious falls are a common problem among older institutionalized adults, having serious physical, psychological and/or financial consequences for the fallers, their families, and personal care home (PCH) staff (Tideiksaar, 2002). North Eastman Health Association (NEHA) introduced a Fall Management Program into its five PCHs in 2005 in an effort to keep residents active and mobile, while minimizing injuries if they fell. The purpose of this research was to evaluate the Fall Management Program to determine if its goals of increased resident mobility and injury minimization were being met. A quasi-experimental, pre-post, comparison group design triangulating different data sources was used to evaluate the effectiveness of the program. Fall Occurrence Report data were collected from all five NEHA PCHs, and from seven similar PCHs in the Interlake Regional Health Authority (IRHA) that did not have a fall program in place. Administrative data from the Manitoba Centre for Health Policy (MCHP) were also used to provide information about some explanatory variables. Comparisons were made between regional health authorities (RHAs) and over time, from the pre- to post- period. Results indicate that NEHA’s Fall Management Program had some benefits for residents – there was a trend towards an increase in mobility (i.e., a non-significant upward trend in falls) while overall injuries remained stable, and falls resulting in hospitalization decreased significantly. NEHA residents appear to have been protected from an increase in injuries despite an upward trend in falls. Moreover, NEHA’s residents had significantly better outcomes compared to similar residents in the non-program PCHs in IRHA. By the post-period, both RHAs had the same rate of falls, but NEHA had significantly fewer injurious falls and falls resulting in hospitalization than IRHA. This suggests that the non-program PCHs had more difficulty preventing resident injuries than the program PCHs in NEHA.
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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 | 0.008 | 0.012 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".