Medication-related quality of care in residential aged care: an Australian experience
Bibliographic record
Abstract
OBJECTIVE: To describe medication-related quality of care (MRQOC) for Australian aged care residents. DESIGN: Retrospective cohort using an administrative healthcare claims database. SETTING: Australian residential aged care. PARTICIPANTS: A total of 17 672 aged care residents who were alive at 1 January 2013 and had been a permanent resident for at least 3 months. MAIN OUTCOME MEASURES: Overall, 23 evidence-based MRQOC indicators which assessed the use of appropriate medications in chronic disease, exposure to high-risk medications and access to collaborative health services. RESULTS: Key findings included underuse of recommended cardiovascular medications, such as the use of statins in cardiovascular disease (56.1%). Overuse of high-risk medications was detected for medications associated with falls (73.5%), medications with moderate to strong anticholinergic properties (46.1%), benzodiazepines (41.4%) and antipsychotics (33.2%). Collaborative health services such as medication reviews were underutilised (42.6%). CONCLUSION: MRQOC activities in this population should be targeted at monitoring and reducing exposure to antipsychotics and benzodiazepines, improving the use of preventative medications for cardiovascular disease and improving access to collaborative health services. Similarity of suboptimal MRQOC between Australia and other countries (UK, USA, Canada and Belgium) presents an opportunity for an internationally collaborative approach to improving care for aged care residents.
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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 | 0.003 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.002 |
| 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 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".