Short-notice (48 hours) ACCREDITATION trial in Australia: stakeholder perception of assessment thoroughness, resource requirements and workforce engagement
Bibliographic record
Abstract
BACKGROUND: External, independent accreditation assessments of healthcare organisations are necessary to ensure the nationally legislated minimum standards of quality and safety (QS) are met. The predetermined scheduling of the assessments continues to be criticised due to the high level of organisational emphasis on preparing for accreditation. OBJECTIVES: To determine the stakeholder perception of assessment thoroughness, staff resource requirements and workforce engagement changes if only 48 hours' notice is given to an organisation prior to an accreditation assessment, compared with the standard-notice accreditation process. METHODS: Logan and Beaudesert Hospitals in Brisbane, Australia, trialled the 'Short-Notice Survey Accreditation Assessment Process' (SNAAP) between August 2017 and December 2018. The organisation was given just 48 hours' notice prior to an accreditation assessment. Staff perception of the standard-notice accreditation process and short-notice process was assessed using a 5-point Likert scale repeated measures questionnaire (pretrial, 6 and 12 months after SNAAP launch). RESULTS: There was a statistically significant stakeholder opinion that SNAAP more effectively identified the true strengths and achievements of the organisation's QS compared with 'standard-notice' survey (p=0.033). There was a significantly lower overall perceived proportion of staff resources required for SNAAP preparation in contrast to 'standard-notice' process (Baseline Av=21.38% vs Follow-up 1 and 2 Av=9.75%-6.25%, p=0.021). The questionnaire results reflected that SNAAP increased staff engagement in QS activities (Av=3.75 and 3.69, 95% CI=3.45-4.05 and 3.45-3.94). CONCLUSIONS: With sufficient cultural and operational preparation to move to SNAAP, hospitals can potentially use SNAAP as a truer validation of QS standards, require less staffing resources to prepare for accreditation assessments and improve staff engagement in QS assurance and improvement.
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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 | 0.030 | 0.001 |
| 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 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".