Uncertainty, Emergence and Adaptation: A Complex Adaptive Systems Approach to Quality Improvement

TY - JOUR

T1 - Uncertainty, Emergence and Adaptation: A Complex Adaptive Systems Approach to Quality Improvement

AU - McLachlan, Scott

AU - Wilson, William

AU - Dube, Kudakwashe

AU - Jayamaha, Nihal

PY - 2023/2/16

Y1 - 2023/2/16

N2 - The healthcare quality improvement (QI) literature is replete with examples stating that continued failure to regard healthcare as a complex adaptive system (CAS) reduces the effectiveness of quality improvement initiatives. Recommendations and strategies for managing change within CAS exist but the specific mechanisms that bring about successful change within CAS and the implications for quality practitioners are under-explored. This article presents a generalizable model for QI within CAS and provides a specifically CAS explanation for incremental change. We develop a conceptual model from foundational CAS principles that is then operationalized as an agent-based simulation model. Our model captures critical complex system behavior in a generic manner easily applied to different improvement contexts. We tested the simulation model using a recognizably complex healthcare improvement case: reducing antipsychotic prescribing levels in aged residential care. Non-linear phase transitions were observed in the agent network, conditioned on the network’s ability to learn solution options and simultaneously maintain cooperation. We believe that a CAS explanation of change can assist practitioners navigating complex QI activities.

AB - The healthcare quality improvement (QI) literature is replete with examples stating that continued failure to regard healthcare as a complex adaptive system (CAS) reduces the effectiveness of quality improvement initiatives. Recommendations and strategies for managing change within CAS exist but the specific mechanisms that bring about successful change within CAS and the implications for quality practitioners are under-explored. This article presents a generalizable model for QI within CAS and provides a specifically CAS explanation for incremental change. We develop a conceptual model from foundational CAS principles that is then operationalized as an agent-based simulation model. Our model captures critical complex system behavior in a generic manner easily applied to different improvement contexts. We tested the simulation model using a recognizably complex healthcare improvement case: reducing antipsychotic prescribing levels in aged residential care. Non-linear phase transitions were observed in the agent network, conditioned on the network’s ability to learn solution options and simultaneously maintain cooperation. We believe that a CAS explanation of change can assist practitioners navigating complex QI activities.

M3 - Article

JO - Quality Management Journal

JF - Quality Management Journal

ER -