• Bmc Med · Jun 2018

    Being pragmatic about healthcare complexity: our experiences applying complexity theory and pragmatism to health services research.

    • Katrina M Long, Fiona McDermott, and Graham N Meadows.
    • Southern Synergy, Department of Psychiatry, School of Clinical Sciences at Monash Health, Faculty of Medicine, Nursing and Health Sciences, Monash University, Melbourne, VIC, Australia. katrina.long@monash.edu.
    • Bmc Med. 2018 Jun 20; 16 (1): 94.

    BackgroundThe healthcare system has proved a challenging environment for innovation, especially in the area of health services management and research. This is often attributed to the complexity of the healthcare sector, characterized by intersecting biological, social and political systems spread across geographically disparate areas. To help make sense of this complexity, researchers are turning towards new methods and frameworks, including simulation modeling and complexity theory.DiscussionHerein, we describe our experiences implementing and evaluating a health services innovation in the form of simulation modeling. We explore the strengths and limitations of complexity theory in evaluating health service interventions, using our experiences as examples. We then argue for the potential of pragmatism as an epistemic foundation for the methodological pluralism currently found in complexity research. We discuss the similarities between complexity theory and pragmatism, and close by revisiting our experiences putting pragmatic complexity theory into practice.ConclusionWe found the commonalities between pragmatism and complexity theory to be striking. These included a sensitivity to research context, a focus on applied research, and the valuing of different forms of knowledge. We found that, in practice, a pragmatic complexity theory approach provided more flexibility to respond to the rapidly changing context of health services implementation and evaluation. However, this approach requires a redefinition of implementation success, away from pre-determined outcomes and process fidelity, to one that embraces the continual learning, evolution, and emergence that characterized our project.

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