Objective: To understand the complex effects of interruption in healthcare. Materials and methods: As interruptions have been well studied in other domains, the authors undertook a systematic review of experimental studies in psychology and human–computer interaction to identify the task types and variables influencing interruption effects. Results: 63 studies were identified from 812 articles retrieved by systematic searches. On the basis of interruption profiles for generic tasks, it was found that clinical tasks can be distinguished into three broad types: procedural, problem-solving, and decision-making. Twelve experimental variables that influence interruption effects were identified. Of these, six are the most important, based on the number of studies and because of their centrality to interruption effects, including working memory load, interruption position, similarity, modality, handling strategies, and practice effect. The variables are explained by three main theoretical frameworks: the activation-based goal memory model, prospective memory, and multiple resource theory. Discussion: This review provides a useful starting point for a more comprehensive examination of interruptions potentially leading to an improved understanding about the impact of this phenomenon on patient safety and task efficiency. The authors provide some recommendations to counter interruption effects. Conclusion: The effects of interruption are the outcome of a complex set of variables and should not be considered as uniformly predictable or bad. The task types, variables, and theories should help us better to identify which clinical tasks and contexts are most susceptible and assist in the design of information systems and processes that are resilient to interruption.
|Number of pages||7|
|Journal||Journal of the American Medical Informatics Association|
|Publication status||Published - 1 Jan 2012|
LI, Y. W. S., MAGRABI, F., & COIERA, E. (2012). A systematic review of the psychological literature on interruption and its patient safety implications. Journal of the American Medical Informatics Association, 19(1), 6-12. https://doi.org/10.1136/amiajnl-2010-000024