An evaluation of a frontline led quality improvement initiative
Bibliographic record
Abstract
Purpose The Edmonton Zone, one of five Zones in Alberta Health Services (the health system in the province of Alberta, Canada), established a quality management framework (QMF) as a means to improve the delivery of high quality health care in the spring of 2014. The purpose of this research study was to understand the factors that facilitated or hindered the implementation of a quality improvement (QI) initiative for hand hygiene led by a newly formed frontline unit quality council (UQC), a part of the QMF, based out of the pediatric intensive care unit (PICU) at the Stollery Children's Hospital in the Edmonton Zone. This research will provide an understanding of the newly established QMF in the Edmonton Zone and the factors needed to foster the ongoing development of frontline UQC that do improvement work as part of their daily routine. Design/methodology/approach Using a qualitative case study research design data were collected using semi-structured open-ended interviews with six key stakeholders (one registered nurse, one physician, one patient case manager, medical director for QI, clinical QI consultant and director of clinical QI) involved in UQC at the PICU. Findings Individual, unit and organizational level factors were identified as influencing the function of the UQC. Leadership and work culture were the key facilitating factors to success and lack of QI training and personnel/dedicated time were perceived barriers to completing the QI initiative. Originality/value The findings from this research illustrate that frontline UQC are able to impact positive sustained change early in their establishment as part of a larger QMF. It is important, however, for the system to foster ongoing development of capacity and capability of these frontline UQC to ensure sustained success of the larger systems change.
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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 | 0.043 | 0.036 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.005 | 0.003 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.003 | 0.005 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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".