Reducing harm from falls.
Bibliographic record
Abstract
Serious adverse event reporting from district health boards (DHBs) brought in-hospital falls to the attention of the Health Quality & Safety Commission (the Commission) when it was incepted in 2010. In 2012, responding to the large numbers reported, the Commission began planning for a three-year programme to reduce harm from falls, initially to run 2013-2015. In this article we discuss the serious consequences of falls, and the challenges and practical considerations involved in reducing the risk of falling and the rate of falls. We explore the Commission's choice of an adaptive approach in its programme, and show how a targeted measurement framework and national action has led to a nationwide statistically significant reduction in fractured neck of femur (hip fracture) and associated costs resulting from in-hospital falls, from a median of 12 per 100,000 admissions to eight per 100,000 admissions, sustained as at June 2016 for six quarters. This reduction reflects nationwide implementation of two key care processes: 1.) the percentage of patients 75 and over provided with an assessment of their risk of falling upon admission to hospital has risen from 77% in the first quarter of 2013 to 91% nationally in June 2016, 2.) the percentage of those with identified risk who were provided with an individualised care plan that addressed those risks has risen from 77% of older patients in the first quarter of 2013 to 95% nationally in June 2016. (These results are also reflected in a 14% decrease to 30 June 2016 in numbers of falls reported by DHBs as serious adverse events). Finally, we give a call to arms to the disparate health practitioners and services across all settings for individualised responses to prevent falls one patient at a time, and for leadership responses that promote an integrated approach to falls in older people.
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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 | 0.000 | 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".