Constraints to applying systems thinking concepts in health systems: A regional perspective from surveying stakeholders in Eastern Mediterranean countries
Bibliographic record
Abstract
BACKGROUND: Systems Thinking (ST) has recently been promoted as an important approach to health systems strengthening. However, ST is not common practice, particularly in Low- and Middle-Income Countries (LMICs). This paper seeks to explore the barriers that may hinder its application in the Eastern Mediterranean Region (EMR) and possible strategies to mitigate them. METHODS: A survey consisting of open-ended questions was conducted with a purposive sample of health policy-makers such as senior officials from the Ministry of Health (MoH), researchers, and other stakeholders such as civil society groups and professional associations from ten countries in the region. A total of 62 respondents participated in the study. Thematic analysis was conducted. RESULTS: There was strong recognition of the relevance and usefulness of ST to health systems policy-making and research, although misconceptions about what ST means were also identified. Experience with applying ST was very limited. Approaches to designing health policies in the EMR were perceived as reactive and fragmented (66%). Commonly perceived constraints to application of ST were: a perceived notion of its costliness combined with lack of the necessary funding to operationalize it (53%), competing political interests and lack of government accountability (50%), lack of awareness about relevance and value (47%), limited capacity to apply it (45%), and difficulty in coordinating and managing stakeholders (39%). CONCLUSION: While several strategies have been proposed to mitigate most of these constraints, they emphasized the importance of political endorsement and adoption of ST at the leadership level, together with building the necessary capacity to apply it and apply the learning in research and practice.
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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 | 0.005 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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".