Survey of Communicable Diseases Surveillance System in Hospitals of Iran: A Qualitative Approach
Bibliographic record
Abstract
BACKGROUND: Communicable Disease Surveillance and reporting is one of the key elements to combat against diseases and their control. Fast and timely recognition of communicable diseases can be helpful in controlling of epidemics. One of the main sources of management of communicable diseases reporting is hospitals that collect communicable diseases' reports and send them to health authorities. One of the focal problems and challenges in this regard is incomplete and imprecise reports from hospitals. In this study, while examining the implementation processes of the communicable diseases surveillance in hospitals, non-medical people who were related to the program have been studied by a qualitative approach. METHODS: This study was conducted using qualitative content analysis method. Participants in the study included 36 informants, managers, experts associated with health and surveillance of communicable diseases that were selected using targeted sampling and with diverse backgrounds and work experience (different experiences in primary health surveillance and treatment, Ministry levels, university staff and operations (hospitals and health centers) and sampling was continued until arrive to data saturation. RESULTS: Interviews were analyzed after the elimination of duplicate codes and integration of them. Finally, 73 codes were acquired and categorized in 6 major themes and 21 levels. The main themes included: policy making and planning, development of resources, organizing, collaboration and participation, surveillance process, and monitoring and evaluation of the surveillance system. In point of interviewees, attention to these themes is necessary to develop effective and efficient surveillance system for communicable diseases. CONCLUSION: Surveillance system in hospitals is important in developing proper macro - policies in health sector, adoption of health related decisions and preventive plans appropriate to the existing situation. Compilation, changing, improving, monitoring and continuous updating of surveillance systems can play a significant role in its efficiency and effectiveness. In the meantime, policy makers' and senior managers' support in development and implementation of communicable disease surveillance' plans and their reporting plays a key and core role.
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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 | 0.015 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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".