Developing National Functional Accreditation Model for Primary Healthcares with Emphasis on Family Practice in Iran
Bibliographic record
Abstract
BACKGROUND: Accreditation is an approach toward quality improvement which has been increasingly implemented in healthcare. This study aimed at developing a national functional accreditation model for primary healthcare with emphasis on family practice in Iran. METHODS: This mixed-method study utilizes a set of research methods purposefully. Initially, the reference models were used for benchmarking accreditation standards through a systematic review. Then, the primary accreditation standards were developed and then they were assessed and approved by the experts of the field via Delphi technique. In the following and after developing essential parts of the standards, the necessary changes in developed model were done according to the pilot test results. RESULTS: The results of systematic review suggested the superiority of accreditation models of the United States, Australia, Canada, and the United Kingdom globally; and the models of Jordan, Saudi Arabia, Lebanon, and Egypt in Eastern-Mediterranean region. Then, the primary standards including 39 functional standards with 231 measures were developed according to the benchmarked models, and were approved by the experts in Delphi-based study. In pilot test step, the compliance rate of developed standards by primary healthcare centers was calculated 61.61% and 26.37% for self-evaluation and external evaluation phases, respectively. CONCLUSION: Regarding the comprehensiveness of developed accreditation model due to its focus on all functional dimensions and the consensus over the developed standards by the experts, it can be an underlying ground for the establishment and evaluation of functional improvement programs in Iranian primary healthcare system.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".