The Association of Resident Communication Abilities and Antibiotic Use in Long‐Term Care
Bibliographic record
Abstract
OBJECTIVES: To determine whether decreased communication ability among long-term care residents is associated with increased antibiotic exposure. DESIGN: Retrospective cohort study. SETTING: All long-term care homes in Ontario, Canada. PARTICIPANTS: All adults aged 66 years or older residing in long-term care and undergoing a full assessment between January 1 and December 31, 2016 (N = 87,947). MEASUREMENTS: Data were obtained from linkable, population-wide administrative data sets. Residents were identified, and characteristics were abstracted from the Resident Assessment Instrument Minimum Dataset version 2.0. The primary predictors of interest were residents' ability to make themselves understood and ability to understand others. The primary outcome was antibiotic days of treatment per 1000 resident days in the 90 days following assessment (obtained from the Ontario Drug Benefits Database). RESULTS: Those who were sometimes/rarely/never able to make themselves understood received 50.7 antibiotic days per 1000 person-days of follow-up, compared to 62.1 received by those who were able to make themselves understood. Those who were sometimes/rarely/never able to understand others received 50.0 antibiotic days per 1000 person-days of follow-up, compared to 61.4 by those who were able to understand others. Multivariable Poisson regression, accounting for resident characteristics, confirmed that compared to those with highest levels of communication ability, those who could sometimes/rarely/never make themselves understood had significantly fewer days on antibiotics (rate ratio [RR] = 0.76; confidence interval [95% CI] = 0.73-0.79) as did those who could sometimes/rarely/never understand others (RR = 0.76; 95% CI = 0.74-0.79). CONCLUSION: Poor resident communication ability is not a driver of antibiotic overuse in long-term care. In fact, lower ability to understand others and/or be understood by others is associated with less antibiotic exposure. Further work is needed to optimize antibiotic use in long-term care residents across the entire spectrum of communication skills.
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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 | 0.001 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".