Modeling help chains in health services as social networks: moving from linearity to complexity

Help Chain (HC) is a problem-solving practice underpinned by lean manufacturing principles and also adopted for health services, which have different complexity characteristics in relation to manufacturing. This study is based on the premise that Social Network Analysis (SNA) might be an effective analytical approach to account for the complexity of HCs in healthcare. Hence, two research questions are addressed: how to model and interpret HCs in health services as a social network and how SNA can either challenge or add to the lean assumptions of HC design. The use of SNA to model HCs was tested in a maternity hospital, where HCs related to five problems were analyzed, concerning the supply of instruments from the centre of sterilised materials to the surgical and obstetrics units. We analyzed the HCs of single problems and then combined the five problem-solving networks to produce a multilayered network that accounted for their interactions. The patterns of social interactions varied according to the problem and three dimensions of actors' performance (i.e. availability, reliability, and agility). SNA unveiled the complexity of HCs and provided guidance for revising the lean assumptions in their design, matching the realities of health services.