Reflections on benefits and challenges of longitudinal organisational network analysis as a tool for health systems research and practice
Bibliographic Data
| ID | 21880818 |
|---|---|
| Authors | Douglas Glandon (0000-0003-2305-7424, Johns Hopkins University, corresponding author), Ligia Paina (0000-0002-8403-7825, Johns Hopkins University), Connie Hoe (0000-0001-8008-4010, Johns Hopkins University) |
| Year | 2021 |
| Volume | 6 |
| Issue | 8 |
| Pages | e005849 |
| Publication date | 2021-08-01 |
| Open Access | Yes |
| Type | ARTICLE |
| Venue | BMJ Global Health (JOURNAL) |
| Journal identifiers | ISSN: 2059-7908 • E-ISSN: 2059-7908 |
| Publisher | BMJ (PUBLISHER • GB) |
| DOI | 10.1136/bmjgh-2021-005849 |
| PMID | 34385160 |
| OpenAlex | W3191730589 |
| Language | EN |
| Citations received | 4 |
| References cited | 28 |
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
Business · Data science · Knowledge management · Management science · Network analysis · Organizational network analysis · Process management · Social network analysis · Community Health and Development · Computer Science · Engineering · Health disparities and outcomes · Mental Health and Patient Involvement
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| Citations per year | 1.33 |
|---|---|
| Citation span | 2023 - 2024 (2) |
| Highly cited | No |