Designing a model for security requirements of electronic health records in Iran
Bibliographic record
Abstract
Background: Flourishing capacity of information technologies for collecting, storage and transmission unheard of amount of information creates a great deal of concerns for patients. Patients are worried over the access of numerous people to their electronic health records. Objective: To determine the security requirements of electronic health records for Iran. Methods: This descriptive study was carried out in 2007. Security requirements of electronic health records gathered from comparative study performed in Australia, Canada and England countries followed by designing the initial model. The final model was prepared through gathering the information by questionnaire and the use of Delphi Technique. The values under 50 percent were eliminated from the model and those equal or higher than 75 percent added to the model. Findings: The proposed model for Iran includes the requirements for organizing information, information classification, human resources, communication and operation management, and access control security. Conclusion: A comprehensive model of electronic health records security requirements was designed for Iran. The approval of this model by authorities for protecting the electronic health information security is recommended.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 |
| 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 | 0.000 |
| 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".