Report of a pilot study of quality improvement in nursing homes led by healthcare aides
Bibliographic record
Abstract
Objective: Healthcare aides (unregulated care providers), who deliver the majority of direct care in Canadian nursing homes, have high levels of emotional exhaustion and cynicism. However, they also have remarkably high levels of job efficacy. Strategies to empower this workforce may reduce cynicism and draw on their high levels of job efficacy. The primary objective of this study was to act as proof-of-principle to determine whether quality improvement teams led by healthcare aides could be established in nursing homes and function on a daily basis. Methods: This study was a pilot test of a complex intervention using a mixed methods approach. We used a combination of education, networking and coaching to engage staff teams in quality improvement in 1 of 3 areas (pain control, skin care or behaviour management). We measured healthcare aides’ quality of work life, informal communication and research (best practice) use before and after the intervention. To understand the effect of quality of care at the bedside we used risk-adjusted quality indicators derived from Resident Assessment Instrument - Minimum Data Set 2.0 data. Results: A total of 10 teams participated in the intervention. At least 70% of the teams succeeded in learning and applying the improvement model and methods for local measurement. For 50% of the teams, data showed measurable improvement in the clinical areas. There were no significant differences between pre and post measures of survey variables. Conclusions: We have demonstrated the ability of healthcare aides to engage in quality improvement initiatives at the bedside in a collaborative environment and advance our results as an important contribution to person-centered healthcare.
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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 | 0.004 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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) | 0.000 | 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".