The prevalence of suboptimal prescribing of medication in First Nations older adults in the Torres Strait
Bibliographic record
Abstract
OBJECTIVES: This study assessed the prevalence of suboptimal prescribing of medicines in First Nations older adults in the Torres Strait. Types of suboptimal prescribing included polypharmacy, over-prescribing, under-prescribing and anticholinergic burden. It also assessed any significant associations between suboptimal prescribing and common age-related problems such as falls, reduced function and cognition. METHOD: Cross-sectional study (2015-2018) on 18 island and five mainland communities in the Torres Strait and Northern Peninsula Area of Far North Queensland, Australia. Community-dwelling residents aged 45 years and older who identified as Torres Strait Islander and/or Aboriginal with complete medication histories were recruited in this study. Validated prescribing tools were used to identify suboptimal prescribing practises. RESULTS: There were 254 participants with complete medication histories. The mean age was 65.7 (SD ± 10.9, range 45-93), with 65% female. Suboptimal prescribing in this study was 74%. Of these, 49% of participants had polypharmacy, 44% were over-prescribed, and 36% were under-prescribed. Anticholinergic burden was identified in 26% of participants. Polypharmacy was more prevalent in participants who were dependent on instrumental activities of daily living (iADLs). CONCLUSIONS: The results demonstrate the importance of general practitioners, health-care workers or pharmacists, to monitor medication prescribing in this population. Frequent review of medications to reduce suboptimal prescribing practices within these communities may help to reduce adverse outcomes because of prescribing practices.
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.
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 | 0.002 | 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".