Decision-Making in Australia’s Healthcare System and Insights From Complex Adaptive Systems Theory

Abstract

Complex adaptive systems theory has the potential as a guide for teaching and practice. Healthcare managers and authorities need to be prepared for complexity and ambiguity and cannot expect the evidence-based reviews to tell them everything they need to know. They should learn that strict decision-making approaches, though conservative, are no more protective of complex decisions than risk seeking and adaptive processes. 1. Background As healthcare delivery becomes more complex, so do healthcare allocation decisions. Several challenges confront healthcare systems in the resourcing and provision Background: Identifying the optimal allocation of resources to improve health and evaluating the ever-changing nature of healthcare delivery programs have proved challenging. Little is known about how decision-makers actually identify the optimal allocation of resources to improve health. Objectives: This study seeks to elucidate how decision-makers decide in complex health-care situations, what tools or methods to employ and why. Patients and Methods: A theoretical sample of 25 Australian healthcare executives was recruited to participate in individual, semi-structured interviews. The participants were managers at each level of organizational structure with responsibilities for healthcare resource allocation. They were interviewed on their perspectives about the weightiest allocation decisions they had made in the past. All interviews were digitally recorded, transcribed and analysed thematically. Results: We found that decision-making in Australia's healthcare system is never an individual rational choice. Allocation decision-making involved a multifaceted interplay of elements in situations of action. It was not exclusively rational and no single meth-odological framework is sufficient. Decision-making relates to contextual run-time factors which change while the system is operating. Problems that combine complexity with uncertainty resisted evidence-based decision-making. Our findings revealed that Australia's healthcare systems exhibits most, if not all, underlying features of complex adaptive systems and confirmed that Cynefin sense-making model can be applied heu-ristically to analysis of decision-making in healthcare resource allocation. Conclusions: Healthcare decision-making and policy environment is becoming increasingly complex and interdependent. The way forward is only understood through con-textual knowledge and relativist understanding of the decision contexts, uncertainty, multiplicity and broader stakeholder involvement.