A case study on the assessment of sustaining evidence-based practice changes and outcomes using the Nursing Quality Indicators for Reporting and Evaluation® (NQuIRE®) data system
Bibliographic record
Abstract
Background In 2003, the Registered Nurses’ Association of Ontario (RNAO) established the Best Practice Spotlight Organization ® (BPSO ® ) designation, a pivotal knowledge translation strategy. This initiative aimed to support the Best Practice Guidelines (BPGs) implementation, enable rapid learning and sustainability of evidence-based practice changes. Evaluating the sustainability of evidence-based practice changes is crucial for fidelity of the BPG implementation. Despite existing strategies to acknowledge sustained improvements in practices, there are currently no clear criteria or guidelines available for evaluating sustainability. This article introduces a systematic approach to evaluate the sustainability of BPG implementation outcomes. Methods A mixed methods approach is used to develop criteria to evaluate the sustainability of practice changes and outcomes associated with BPG implementation. This process aims to guide future data reporting frequencies by BPSOs. This approach includes collecting and analyzing qualitative and quantitative data from BPSOs; conducting an environmental scan to determine any existing methods to assess sustainability; and facilitating internal and external expert discussions to provide feedback on the proposed criteria. Results A numerical measure is developed to estimate the number of observations or data submission months required for achieving data saturation and stability or sample size adequacy. A case study is conducted to illustrate the application of the proposed method based on data collected during the implementation of the Assessment and Management of Pain (2013) BPG at an acute care hospital in Ontario, Canada illustrates sustainability of the following practice change and related outcome: consistent pain assessments by healthcare providers and improved patient satisfaction with pain management. Conclusions Monitoring sustainability is a crucial step in BPG implementation. Optimized reporting informs resource allocation and changes to implementation activities. The case study underscores the benefits of using control charts for evaluating practice sustainability and facilitating meaningful data collection by BPSOs for quality improvement.
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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 | 0.058 | 0.077 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.005 | 0.005 |
| Science and technology studies | 0.011 | 0.005 |
| Scholarly communication | 0.005 | 0.005 |
| Open science | 0.004 | 0.007 |
| Research integrity | 0.006 | 0.004 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".