Background: Accountability for maternal, newborn and child health (MNCH) is a collaborative endeavour and documenting collaboration dynamics may be key to understanding variations in the performance of MNCH services. This study explored the dynamics of collaboration among frontline health professionals participating in two MNCH coordination structures in a rural South African district. It examined the role and position of actors, the nature of their relationships, and the overall structure of the collaborative network in two sub-districts. Methods: Cross-sectional survey using a social network analysis (SNA) methodology of 42 district and sub district actors involved in MNCH coordination structures. Different domains of collaboration (eg, communication, professional support, innovation) were surveyed at key interfaces (district-sub-district, across service delivery levels, and within teams). Results: The overall network structure reflected a predominantly hierarchical mode of clustering of organisational relationships around hospitals and their referring primary healthcare (PHC) facilities. Clusters were linked through (and dependent on) a combination of district MNCH programme and line managers, identified as central connectors or boundary spanners. Overall network density remained low suggesting potential for strengthening collaborative relationships. Within cluster collaborative patterns (inter-professional and across levels) varied, highlighting the significance of small units in district functioning. Conclusion: SNA provides a mechanism to uncover the nature of relationships and key actors in collaborative dynamics which could point to system strengths and weaknesses. It offers insights on the level of fragmentation within and across small units, and the need to strengthen cohesion and improve collaborative relationships, and ultimately, the delivery of health services.
|Journal||International Journal of Health Policy and Management|
|Number of pages||11|
|Publication status||Published - 2021|
- District Health System
- Social Network Analysis
- Quality Improvement