Perceptions, Attitudes, and Barriers towards the Use of Central Board for Accreditation of Healthcare Institutions (CBAHI) Standards among Saudi Healthcare Providers
Bibliographic record
Abstract
BACKGROUND: Quality improvement is a strategic priority for all healthcare systems. However, the engagement of healthcare providers in pursuing accreditation plays a critical role in integrating standards into routine practice. Therefore, the current study assessed the perceptions, attitudes, and barriers towards using the Central Board for Accreditation of Healthcare Institutions (CBAHI) standards among Saudi healthcare providers. METHOD: This cross-sectional study was conducted in 2023 among a representative sample (364) of Saudi healthcare providers (both genders, aged 20-60) working at twenty governmental CBAHI-accredited hospitals in Saudi Arabia. The study participants were selected using a cluster random sampling method. Data regarding the perceptions, attitudes, and barriers toward using CBAHI standards among Saudi healthcare providers were evaluated using a validated questionnaire. Additional information regarding demographic-socioeconomic variables was obtained with an interview-based questionnaire. Statistical analysis was performed using SPSS version 28. RESULTS: -value < 0.05). The means of overall item agreement percentage of the participating healthcare providers for perceptions and attitudes towards using CBAHI standards and attitudes towards using CBAHI standards as a tool for quality improvement were 80.1%, 76.4%, and 72.0%, respectively. The highest item agreement percentage of the participating healthcare providers regarding the barriers that inhibit the hospital from obtaining the full benefit from the CBAHI accreditation was for the inexpedient IT tools (59.6%). CONCLUSION: The current study's results demonstrated accepted perceptions and attitudes toward using CBAHI standards among Saudi healthcare providers. In addition, the identified barriers should be alleviated to improve the quality, effectiveness, and efficiency of the hospitals in Saudi Arabia. The findings also help clarify the accreditation operating process, which may be helpful to policymakers and stakeholders in making informed decisions on integrating accreditation standards.
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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 | 0.003 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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".