Is the introduction of an accreditation program likely to generate organization‐wide quality, change and learning?
Bibliographic record
Abstract
OBJECTIVE: This research assesses whether integration of Accreditation Canada's program brings about change and organizational learning. METHODS: Two health organizations, the Health Authority of Anguilla and the Ca' Foncella Opetale di Treviso, are studied on three levels: (1) members; (2) accreditation teams; and (3) organization. The methods used to collect data consisted of individual questionnaires administered to team members, semi-formal interviews with team leaders and quality coordinators, a documentation review and periodic assessments of compliance with the standards. RESULTS: The findings indicate that the organizations made strategic, organizational and relational changes. They improved their systems and management practices as well as their internal and external communications. There was also useful learning by individuals, teams and the organizations. Individual learning involved quality practice, client-focused approach, risk management, ethics, participatory management and assessment of services. The "self-assessment" and "make improvements and follow up on recommendations" stages of the accreditation cycle contributed the most to change and organizational learning. The interdisciplinary accreditation teams were the preferred vehicle for achieving these changes and this learning. CONCLUSIONS: The Health Authority of Anguilla and Ca' Foncella Opetale di Treviso have gradually improved their level of compliance with the standards in all quality dimensions. However, improvement in the overall compliance level was below the program's minimum requirements to obtain accreditation status without major restrictions. The scope of the changes and learning achieved raises the issue of the capacity of organizations to formalize this new knowledge throughout the organization. Copyright © 2015 John Wiley & Sons, Ltd.
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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 | 0.028 | 0.114 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 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".