The need to reorganize health research systems in pandemic crisis: A prospective study

Pandemics pose significant challenges to global health systems. The COVID-19 pandemic starkly revealed the critical need for robust and adaptable health research systems. Countries worldwide recognize that leveraging research findings is essential for growth, development, and problem-solving across social, health, and economic sectors. Sustainable development hinges on investment in and application of research. Health research is particularly vital, as its outcomes directly impact public health; neglecting it jeopardizes lives. While many countries have established health research systems, inconsistencies, lack of coordination, inadequate funding, and insufficient skilled personnel often hinder their effectiveness. This research addresses the urgent need to review and improve health research systems, particularly in light of the COVID-19 crisis. In Iran, the pandemic prompted an immediate call for system reform, leading to efforts by university administrators and professors to design a more effective model. This study aims to develop an integrated model for Iranian health research systems using quantitative and qualitative methods, given the similar organizational structures of medical universities across the country, making the results generalizable nationwide.

The literature extensively documents the impact of pandemics on health systems and the critical role of research in responding to crises. Studies highlight the need for coordinated research efforts and efficient resource allocation to tackle public health emergencies. Existing literature also underscores the challenges faced by many health research systems, including inconsistencies, lack of coordination, inadequate funding, and human resource limitations. Several studies emphasize the importance of robust management and leadership in strengthening health research systems. The review also identifies a gap in research on integrated health research system models for pandemic response, motivating this study to design and propose such a framework. The literature underlines the importance of effective knowledge management and science production as key outputs of any functional health research system.

This study employed a descriptive and analytical design, incorporating expert opinions to identify components influencing health research systems. Thirty key experts, selected through purposive sampling (heads and deputies of medical science universities, deans and faculty deputies, and professors of health services management and health information management), participated in semi-structured interviews. The selection process continued until theoretical saturation was reached. The Clarke and Braun six-step method guided the process approach and content analysis of data: familiarity with the data, creating initial codes, searching for themes, forming subthemes, defining and naming the main themes, and preparing the final list. Components were identified at three levels: conceptual, structural, and basic. However, only the first and second levels were used for model development, while third-level components were reserved for operational planning. Two independent experts reviewed the final list to ensure validity. Mic Mac analysis determined the position, influence, effectiveness, and stability of the components within the system. The components were arranged in an n × n matrix, and experts scored their effectiveness or influence on a scale of 0-3. Four different Mic Mac matrices were created; their outputs were analyzed using Mic Mac graphs and maps, including a Matrix of Direct Influences (MDI).

The study identified seventeen influential structural components within the health research system. These components fell into several categories: Enhancers (Leadership and management, Human resources, Information systems and databases, Financing, Research process); Primary outputs (Knowledge management and science production, Efficiency, Quality, Sustainability, Innovation, Satisfaction, Decision making); and Final outputs (Responsiveness to community needs, Health promotion, Culturalization, Equity, Effectiveness). While third-level (basic) components were excluded from modeling, their frequencies were recorded for further information. Mic Mac analysis revealed the leadership and management components to have the most direct and indirect influence. Health promotion showed the highest dependence among components. Input components included management and leadership, systems and databases, financing, human resources, and the research process. Innovation, sustainability, and culturalization were classified as independent components. Knowledge management and science production acted as linkage components, while other components functioned as outputs. The system stability was assessed using Mic Mac direct and indirect influence maps, showing strong relationships between components in the direct mode. A conceptual model was developed integrating these components. The model illustrates inputs (human resources, financing, information systems, research process), regulators (research process, sustainability), linkage components (knowledge management, science production), and outputs (health promotion, effectiveness, responsiveness to community needs).

The findings highlight the critical role of management and leadership in driving effective health research systems. The model reveals that focusing on inputs like human resources and robust information systems is crucial. The strong dependence on health promotion emphasizes the importance of community engagement. The placement of sustainability and innovation as independent components underscores the need for a supportive environment to foster these aspects. The key outputs, knowledge management and science production, demonstrate that these systems should prioritize translating research into tangible improvements in health outcomes. The model's design allows for a comprehensive understanding of the relationships and interdependencies between different components within the health research system. The integrated model offers a valuable tool for policymakers and administrators to strategically allocate resources and strengthen the research system's resilience during and after a pandemic.

This study provides a comprehensive, integrated model for health research systems, particularly relevant during pandemic crises. The Mic Mac analysis identifies key influential and dependent components, emphasizing the crucial role of management and leadership, and the importance of investing in human resources and information systems. The model underscores the need for strategic resource allocation to support sustainability and innovation within the research system. Future research could explore the model's application in diverse contexts and further refine its components based on real-world implementation data.

The study's generalizability is limited to the context of Iranian medical universities, as the sample focused on this specific setting. The reliance on expert opinions may introduce subjectivity; however, the use of multiple experts and the attainment of theoretical saturation mitigated this limitation. Future studies could expand the sample to include broader perspectives from various stakeholders within the health research ecosystem. Furthermore, longitudinal studies are needed to assess the model's effectiveness over time and in different crisis situations.