The Value of Systems and Complexity Thinking to Enable Change in Adaptive Healthcare Organisations, Supported by Informatics

Background. This paper provides an overview of complex adaptive systems (CAS) theories and value in enabling change in an adaptive organisation. A CAS approach is interpreted here as a framework that assists thinking about the nature of quality improvement programmes with a focus on the people involved. Objective. To identify key elements and characteristics of complex adaptive systems, drawing on examples from primary care informatics and clinical governance programmes. Method. The research strategy is built on longitudinal case studies of the implementation of clinical governance arrangements in two United Kingdom (UK) Primary Care Organisations (PCOs) and includes a literature review to develop theoretical models relevant to the governance of quality improvement. Results. The findings show that CAS theories are a valuable tool to help make sense of natural phenomena, which include human responses to problem solving. Approaches incorporate professional self-regulation that builds on the skills and strengths of the clinicians. There is considerable variation in the way in which consultation data is captured, recorded and organised, which includes free text, coded data and structured data collected using templates. An emphasis on incentivised information sharing led to local consensus on standard coding policies and models of data recording before any national contractual requirement. Informatics is acknowledged as a mechanism to link electronic health record outputs, quality improvement and resources. Investment in informatics, education and training is identified as development priorities in order to embed clinical governance principles in practice. Conclusions. This study suggests that a CAS approach is useful in describing evolutionary change processes in semi-autonomous, networked PCOs. The adoption of new forms of governance does not necessarily neutralise previous models, but adds further dimensions to them. For instance, clinical governance models have moved from deterministic and “objective” factors, to incorporate cultural aspects and the exploitation of the potential offered by networks, interactions and feedback mechanisms enabled by developments in primary care informatics