Incidence of adverse incidents in residential aged care
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Objective Adverse incident research within residential aged care facilities (RACFs) is increasing and there is growing awareness of safety and quality issues. However, large-scale evidence identifying specific areas of need and at-risk residents is lacking. This study used routinely collected incident management system data to quantify the types and rates of adverse incidents experienced by residents of RACFs. Methods A concurrent mixed-methods design was used to examine 3 years of incident management report data from 72 RACFs in New South Wales and the Australian Capital Territory. Qualitative thematic analysis of free-text incident descriptions was undertaken to group adverse incidents into categories. The rates and types of adverse incidents based on these categories were calculated and then compared using incidence rate ratios (IRRs). Results Deidentified records of 11 987 permanent residents (aged ≥65 years; mean (±s.d.) age 84 ± 8 years) from the facilities were included. Of the 60 268 adverse incidents, falls were the most common event (36%), followed by behaviour-related events (33%), other impacts and injuries (22%) and medication errors (9%). The number of adverse incidents per resident ranged from 0 (42%) to 171, with a median of 2. Women (IRR 0.804; P P Conclusion This study demonstrates that data already collected within electronic management systems can provide crucial baseline information about the risk levels that adverse incidents pose to older Australians living in RACFs. What is known about the topic? To date, research into aged care adverse incidents has typically focused on single incident types in small studies involving mitigation strategies. Little has been published quantifying the multiple adverse incidents experienced by residents of aged care facilities or reporting organisation-wide rates of adverse incidents. What does this paper add? This paper adds to the growing breadth of Australian aged care research by providing baseline information on the rates and types of adverse incidents in RACFs across a large and representative provider. What are the implications for practitioners? This research demonstrates that the wealth of data captured by aged care facilities' incident management information systems can be used to provide insight into areas of commonly occurring adverse incidents. Better use of this information could greatly enhance strategic planning of quality improvement activities and the care provided to residents.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 it