The Effects of Quality Assurance System Implementation on Work Well-Being and Patient Safety: Protocol for a Mixed Methods Study
Bibliographic record
Abstract
BACKGROUND: Systematic monitoring of work atmosphere and patient safety incidents is a necessary part of a quality assurance system, particularly an accredited system like the Joint Commission International (JCI). How the implementation of quality assurance systems affects well-being at work and patient safety is unclear. Evidence shows that accreditation improves workplace atmosphere and well-being. Thus, the assumption that an increase in employees' well-being at work improves patient safety is reasonable. OBJECTIVE: This study aims to describe the protocol for monitoring the effects of implementing the quality assurance system of JCI at Orton Orthopedic Hospital on employees' well-being (primary outcome) and patient safety (secondary outcome). METHODS: Quantitative (questionnaires and register data) and qualitative (semistructured interviews) methods will be used. In addition, quantitative data will be collected from register data. Both quantitative and register data will be analyzed. Register data analysis will be performed using generalized linear models with an appropriate distribution and link function. The study timeline covers the time before, during, and after the start of the accreditation process. The collected data will be used to compare job satisfaction, as a part of the well-being questionnaire, and the development of patient safety during the accreditation process. RESULTS: The results of the quality assurance system implementation illuminate its possible effects on the patient's safety and job satisfaction. The repeatability and internal consistency reliability of the well-being questionnaire will be reported. Data collection will begin in May, 2024. It will be followed by data analysis and the results are expected to be published by 2025. CONCLUSIONS: The planned study will contribute to the evaluation of the effects of JCI accreditation in terms of well-being at work and patient safety. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): PRR1-10.2196/45200.
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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 | 0.094 | 0.089 |
| Meta-epidemiology (narrow) | 0.005 | 0.003 |
| Meta-epidemiology (broad) | 0.007 | 0.005 |
| Bibliometrics | 0.004 | 0.005 |
| Science and technology studies | 0.005 | 0.003 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.004 | 0.003 |
| Research integrity | 0.008 | 0.007 |
| Insufficient payload (model declined to judge) | 0.043 | 0.010 |
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".