Reflections on benefits and challenges of longitudinal organisational network analysis as a tool for health systems research and practice

As health systems practitioners and researchers increasingly turn towards systems thinking approaches and work on building interorganisational networks, they have demonstrated increasing interest in network analysis for investigating relationships and interactions between system actors, both at the individual and organisational levels. Despite the potential of network-based approaches to improve health system efficiency, effectiveness and responsiveness, both the theoretical and practical guidance on designing and evaluating network-building strategies is underdeveloped within the field. While there are multiple tools and resources to help users collect, manage and analyse network data, there is much less guidance on the practical applications of this information. One apparent gap is the limited application of longitudinal organisational network analysis, in which data are collected from the same organisational actors repeatedly over multiple time points. This yields insights into the dynamic nature of networks, including how the network structure and interactions change over time. Given that networks are rarely static, the addition of the time dimension has the potential to substantially enhance the analytical value of network analysis and contribute to more nuanced guidance for interested practitioners and policymakers. In this article, the authors draw on their experiences in conducting longitudinal network analysis of interorganisational relationships in the USA and India to comment on the opportunities and challenges of the methodology within the field of health systems research. We also provide suggestions as to how some of these challenges may be addressed or mitigated.

Automated summary

Health systems practitioners and researchers are increasingly interested in network analysis, especially longitudinal organizational network analysis, to improve system efficiency and provide nuanced guidance. While there are abundant tools for analyzing network data, practical guidance on applying this information is lacking.