Abstract
Health information technology frequently leads to unintended consequences (UICs) post implementation. We believe a key cause of UICs are various HIT mediated connections between people and processes. To better manage UICs we first need to understand the nature of these connections. Business Process Management (BPM) approaches can help support HIT design but to date there are no methods focused on identifying patterns of HIT connectivity. This poster describes our three stage method to identify and model HIT connectivity patterns and then map the patterns to existing BPM workflow patterns. We use our method to analyze a case study of a perioperative information system to provide preliminary examples of individual and collaborative connectivity patterns.
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Acknowledgment
We acknowledge funding support from a Discovery Grant from the Natural Sciences and Engineering Research Council of Canada.
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Harris, A., Kuziemsky, C. (2019). Connectivity Patterns for Supporting BPM in Healthcare. In: Arai, K., Kapoor, S., Bhatia, R. (eds) Advances in Information and Communication Networks. FICC 2018. Advances in Intelligent Systems and Computing, vol 887. Springer, Cham. https://doi.org/10.1007/978-3-030-03405-4_49
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DOI: https://doi.org/10.1007/978-3-030-03405-4_49
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