Policy options to address the effectiveness of health service management graduates in solving Iranian health system challenges: a mixed scoping review and policy Delphi approach
Bibliographic record
Abstract
Background: Iran's healthcare system is grappling with multifaceted challenges, including financial constraints, staffing shortages, infrastructural deficiencies, legal hurdles, and cross-sectoral coordination issues. The integration of health service management graduates into the healthcare workforce is vital to tackle these obstacles effectively. However, the lack of skilled managers can exacerbate problems, leading to inflated costs, and wasted resources. This study aims to propose policy options to improve the effectiveness of healthcare management graduates in exposure to the challenges of Iran's health system. Methods: The study used a mixed-methods design that combined a scoping review and interviews with academics specializing in healthcare management and hospital management, as well as key informants of the Ministry of Health and Medical Education (MoHME), the vice chancellor and deans of faculties of management and paramedicine (December 1, 2022 to February 30, 2023), and a policy Delphi technique (April 1, 2023 to Jun 30, 2023). In the scoping review, we searched PubMed, Web of Science Platform, MEDLINE, Scopus, Google Scholar/Academia, and ERIC for articles published from the inception of each database until August 10, 2022, with an update on October 6, 2022. The search terms included "health services," "healthcare organizations," "healthcare management," "health management education," "Iran," "challenges," "issues," "policy," "interventions," "policy options," "solutions," "policy-making," "effectiveness," "efficacy," and similar terms. We incorporated scholarly articles that presented instances or resolutions demonstrating the impact of health service management graduates in addressing the issues encountered by Iran's healthcare system. Non-English research papers, except Persian, were excluded due to translation resource limitations. Articles from peer-reviewed journals were included based on their publication type, while conference abstracts, book reviews, commentaries, and editorial pieces were considered for review. In the present study, the first step of the modified Delphi methodology involved conducting interviews and qualitative content analysis. Then, through two rounds of online surveys, the policy Delphi technique engaged experts and stakeholders in reviewing and prioritising policy options. Findings: In the scoping review, our initial search of the main databases retrieved 553 articles, with an additional 14 articles from gray literature and 5 studies from local databases, totaling 572 references. 426 studies remained after removing duplicates and reviewing them. We excluded 339 studies that did not align with our study's objectives, leaving us with 87 articles. We had access to the full text of 63 of these studies and ultimately selected 31 for review and thematic analysis. The study involved 21 participants, with a 100% response rate in the interview phase. In the Delphi phase, 64 experts were invited, with 41 participating in Round 1 (64% response rate) and 32 in Round 2 (78% response rate). The scoping review identified eleven policy options, followed by designing an interview guide and presenting nine more options based on expert insights from the interviews. We evaluated twenty policy options using a 5-point Likert scale and modified Delphi methodology to assess their effectiveness, feasibility, relevance, and acceptance cost. The study produced four policy options that were culturally and ethically appropriate, as well as compatible with the context and target population. These options were: 1) training and capacity building based on Iran's health system model; 2) development of the framework of Entrustable Professional Activities (EPAs) for healthcare management graduates; 3) determining the career pathways of healthcare management graduates and reviewing the job categories approved by the Ministry of Health and Medical Education (MoHME); and 4) providing effective collaboration between healthcare management graduates and professionals, policymakers, and stakeholders for integrated health system improvement. Interpretation: The study provides evidence-based recommendations for improving the education, training, and professional deployment of healthcare management graduates in Iran. Funding: This work was supported by the National Agency for Strategic Research in Medical Education (NASR) (Grant Number 4020159).
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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 | 0.035 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| 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".