Mapping the multicausality of medication errors Using system dynamics to identify the underlying mechanisms that produce medication errors
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2022-07-04
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en
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Medication errors are complex and multicausal in nature that cover multiple scientific fields. While many studies address specific parts of the system, this study provides an overview of the complexity of the whole system. For this reason, this study uses system dynamics to map the multicausality of medication errors by identifying the key mechanisms with regard to causal relationships and feedback loops. A causal loop diagram (CLD) built with a group of experts from different domains visualises the system's structure in which this complex and multicausal behaviour arises. The system's structure is mapped based on the knowledge and experiences of the experts during multiple group model building sessions. Hereafter, semi-structured interviews have been conducted to validate the structure of the CLD. Network analysis has been used to identify the central drivers of the system. The results show that three types of dynamics impact the multicausality of medication errors, including endogenous and exogenous factors that form eight reinforcing and three balancing feedback loops. The central drivers in the CLD are the interaction between de endogenous variables' quality of communication, workload, and caregivers' knowledge and skills, suggesting that they may be potential leverage points for interventions. These outcomes increase the understanding of the multicausality of factors impacting medication errors and can support policymakers in developing effective interventions to prevent medication errors. This study encourages future researchers to delve deeper into the model by creating a quantified model that can run simulations to explore the effects of risk factors on medication errors.
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Faculteit der Managementwetenschappen