Hospital Infection Control accreditation standards: A Comparative Review
Bibliographic record
Abstract
Introduction: Nosocomial infection (NI) is an infection occurring in a patient after 48 hours of hospitalization or up to 72 hours after discharge from the hospital, which was not present or incubating at the time of admission. Hospital accreditation standards have a significant impact on the prevention and control of NI. Nevertheless, Iran’s hospital accreditation standards face challenges. The aim of this study was to compare the accreditation standards of NI prevention and control in Iran and leading countries. Material and Methods: This research was conducted using the comparative review method in 2020. Hospital infection prevention and control (IPC) standards of Iran Hospital Accreditation Program was compared with those of international accreditation programs in the United States, Canada and Australia. Thematic analysis method was used to analyze the qualitative data. Results: Iran and the United States had the highest share of nosocomial IPC standards. The Iranian Hospital IPC standards approximately comply with 62.1%, 46.6% and 49.9% of Hospital IPC standards of the United States, Canada and Australia, respectively. A hospital infection management system including constructs of NI leadership and management, NI planning, NI education, employee management, patient management, resource management, process management and outcomes is necessary for IPC. Iran Hospital Accreditation Program places great emphasis on process and resource management and less importance to leadership and management, planning, employee management, patient management and outcomes. Conclusion: The Iranian Hospital Accreditation Program is progressing. However, its IPC standards need to be reviewed and updated. Using a systems approach including structures, processes and results in the development of hospital accreditation standards, leads to the optimal use of hospital resources and achieving better results.
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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 | 0.005 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.007 | 0.002 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.003 |
| Insufficient payload (model declined to judge) | 0.037 | 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".