Succession Planning in the Iranian Health System: A Case Study of the Ministry of Health and Medical Education
Bibliographic record
Abstract
BACKGROUND: Succession planning promotes the culture of private ownership, staff loyalty to the organization and develops organizational commitment, and increases organizational stability. The study was conducted to examine the status of succession planning in the Iranian health system in order to highlight the key concepts, provide new insight, and attract the attention of senior managers of the Ministry of Health and Medical Education to the importance of succession planning in achieving organizational goals. METHODS: In a qualitative study with a framework analysis approach, semi-structured interviews were conducted with a sample selected using purposive and snowball sampling procedure. The MAXQDA-10 was used to apply the codes and manage the data. The codes were extracted using inductive and deductive methods. RESULTS: Fourteen themes and six main subthemes were identified, including planning, organizational culture, system approach, competency model, career path, and senior managers. Our findings indicate a lack of succession planning in the Iranian health system. CONCLUSION: lack of succession planning could lead to inefficiency and ineffectiveness in health services provision. Implementation of succession planning could maximize human resources utilization.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.004 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.009 | 0.003 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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 source (direct Gemma or distilled Codex), 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".