The role of comprehensive international electronic medical file in improving the quality of medical services and achieving the satisfaction of stakeholders: An exploratory study in Jeddah, Saudi Arabia
Bibliographic record
Abstract
Objective: The current study investigates the possible impact of creating a comprehensive international electronic medical file that is part of a database which can be used in various areas to achieve the highest levels of satisfaction for patients and official bodies and enhance the quality of medical services at hospitals as well. One of the key purposes of this e-file is achieving the readiness and confidentiality of data so that it can be shared among hospitals whether inside the Kingdom of Saudi Arabia or even abroad. In addition, the medical e-file may contribute to reducing the costs of treatment, monitoring the performance of doctors and minimising medical errors. Moreover, the e-file may be used for even other purposes such as security or financial reasons.Methods: The study employed the quantitative research design where 171 questionnaires were distributed to patients, managers and staff in 19 small private hospitals in Jeddah city. The questionnaire 44 questions were designed after conducting a small pilot study on 15 participants. The response rate was about 82.5% in terms of the study questionnaire as only 141 questionnaires were collected. 84 male and 57 female participants took part in the study.Results: The study shows that there is a statistically significant correlation between the use of the international electronic medical file and the enhancement of the quality level of services provided at hospitals, the electronic rehabilitation, training, integrity and awareness of medical staff, and the productivity of hospital workers in line with the Kingdom’s 2030 vision. Moreover, there is a statistically significant correlation between the use of the comprehensive international electronic medical file and raising the level of patient satisfaction by working to protect their medical and financial information and speeding up the process of providing it whenever needed, whether inside the KSA or abroad, as well as reducing the costs of treatment locally and internationally and raising the rates of patient awareness of their medical rights. The results also reveal that using the comprehensive international electronic medical file helps to link patients’ data to all concerned authorities, which leads to enabling them to monitor the performance of hospitals and their staff, monitor the performance of doctors, reduce medical errors, and follow up on patients’ cases and rights to the fullest extent.Conclusions: The study recommends the necessity of selecting and training medical personnel in a professional manner, including those working in the field of the database, and the necessity of maintaining the confidentiality of personal information.
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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 | 0.004 | 0.001 |
| 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".