Journal of Health and Biomedical Informatics
Volume 13, Issue 1 (6-2026)
jhbmi 2026, 13(1): 41-52 |
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Farboud M, Hessam S, Vahdat S, Tofighi S. Analysis of Barriers and Facilitators of Predictive Models for Metabolic Syndrome Prevention in Iran: A Qualitative Thematic SWOT. jhbmi 2026; 13 (1) :41-52
URL: http://jhbmi.ir/article-1-983-en.html
URL: http://jhbmi.ir/article-1-983-en.html
Associate Professor, Ph.D. in Health Service Administration, Department of Health Service Administration, ST.C., Islamic Azad University, Tehran, Iran
Abstract: (13 Views)
Introduction: As one of the most common metabolic disorders in Iran, metabolic syndrome imposes a heavy financial and therapeutic burden on the healthcare system and insurance organizations. Although AI-based predictive models can serve as valuable tools for early prevention, their success depends on their implementability within the real-world operational environment of the healthcare system. This study aims to examine the perspectives of healthcare experts regarding the facilitators and barriers associated with implementing these models for the prevention of metabolic syndrome in Iran.
Method: This study employed a qualitative approach and a descriptive-analytical method, utilizing Braun and Clarke’s (2006) six-phase thematic analysis. The research design followed a hybrid inductive-deductive method. Purposive sampling was conducted until theoretical saturation was reached, ultimately involving 15 experts: six clinicians, five managers and policymakers, and four health information technology specialists. Data were collected through in-depth, semi-structured interviews and analyzed using manual coding. Additionally, the SWOT analysis framework served as a deductive guide for organizing and analyzing the themes.
Results: The analysis led to the identification of 20 main themes, which were organized into four categories: strengths (8 themes), weaknesses (5 themes), opportunities (3 themes), and threats (4 themes). Strengths mainly included managerial flexibility, employee empowerment, and action-based learning. Weaknesses included dependence on traditional training and lack of continuous feedback, opportunities included technological advances and policy support, and threats included high workload and policy instability. Four implementation strategies (SO), WO, ST, WT) were extracted, with the combined SO and WT strategies being the most emphasized.
Conclusion: The success of predictive models requires a focus on integrated strategies at the organization level and macro-policy making. The findings of this study can also contribute to evidence-based policy making in the Iranian Health Insurance Organization as well as national prevention programs.
Method: This study employed a qualitative approach and a descriptive-analytical method, utilizing Braun and Clarke’s (2006) six-phase thematic analysis. The research design followed a hybrid inductive-deductive method. Purposive sampling was conducted until theoretical saturation was reached, ultimately involving 15 experts: six clinicians, five managers and policymakers, and four health information technology specialists. Data were collected through in-depth, semi-structured interviews and analyzed using manual coding. Additionally, the SWOT analysis framework served as a deductive guide for organizing and analyzing the themes.
Results: The analysis led to the identification of 20 main themes, which were organized into four categories: strengths (8 themes), weaknesses (5 themes), opportunities (3 themes), and threats (4 themes). Strengths mainly included managerial flexibility, employee empowerment, and action-based learning. Weaknesses included dependence on traditional training and lack of continuous feedback, opportunities included technological advances and policy support, and threats included high workload and policy instability. Four implementation strategies (SO), WO, ST, WT) were extracted, with the combined SO and WT strategies being the most emphasized.
Conclusion: The success of predictive models requires a focus on integrated strategies at the organization level and macro-policy making. The findings of this study can also contribute to evidence-based policy making in the Iranian Health Insurance Organization as well as national prevention programs.
Keywords: Statistical Models, Qualitative Research, Strategic Planning, Health Services Accessibility, Barriers to Care
Type of Study: Original Article |
Subject:
Health Information Management
Received: 2026/03/25 | Accepted: 2026/05/24
Received: 2026/03/25 | Accepted: 2026/05/24
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