Champions for improved adherence to guidelines in long-term care homes: a systematic review
Bibliographic record
Abstract
BACKGROUND: The champion model is increasingly being adopted to improve uptake of guideline-based care in long-term care (LTC). Studies suggest that an on-site champion may improve the quality of care residents' health outcomes. This review assessed the effectiveness of the champion on staff adherence to guidelines and subsequent resident outcomes in LTC homes. METHOD: This was a systematic review and meta-analyses of randomised controlled trials. Eligible studies included residents aged 65 or over and nursing staff in LTC homes where there was a stand-alone or multi-component intervention that used a champion to improve staff adherence to guidelines and resident outcomes. The measured outcomes included staff adherence to guidelines, resident health outcomes, quality of life, adverse events, satisfaction with care, or resource use. Study quality was assessed with the Cochrane Risk of Bias tool; evidence certainty was assessed using the GRADE approach. RESULTS: After screening 4367 citations, we identified 12 articles that included the results of 1 RCT and 11 cluster-RCTs. All included papers evaluated the effects of a champion as part of a multicomponent intervention. We found low certainty evidence that champions as part of multicomponent interventions may improve staff adherence to guidelines. Effect sizes varied in magnitude across studies including unadjusted risk differences (RD) of 4.1% [95% CI: - 3%, 9%] to 44.8% [95% CI: 32%, 61%] for improving pressure ulcer prevention in a bed and a chair, respectively, RD of 44% [95% CI: 17%, 71%] for improving depression identification and RD of 21% [95% CI: 12%, 30%] for improving function-focused care to residents. CONCLUSION: Champions may improve staff adherence to evidence-based guidelines in LTC homes. However, methodological issues and poor reporting creates uncertainty around these findings. It is premature to recommend the widespread use of champions to improve uptake of guideline-based care in LTC without further study of the champion role and its impact on cost. TRIAL REGISTRATION: PROSPERO CRD42019145579 . Registered on 20 August 2019.
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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 | 0.012 | 0.053 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.008 | 0.010 |
| Bibliometrics | 0.005 | 0.006 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".