Abstract
The ability to track and detect the activities and process that constitute clinical workflow for performance analysis and error detection has been enhanced with the inclusion of modern technological interventions in clinical environments. One such important intervention is automated location tracking which is a system that detects the movement of clinically relevant entities (physicians, nurses, patients, and equipment). In this chapter, we elucidate the technologies associated with automated location tracking focusing on the two most widely used: Radio-Frequency Identification (RFID) and Bluetooth. We describe specific systems of each type to give readers a general model of the technological requirements for similar setups in clinical environments. Our goal in writing this chapter is the provide readers with an overview of the state-of-the-art technologies and analytic methods. This can hopefully serve as a guide for similar setups in other medical organizations and clinical sites.
The process of using a location tracking system to perform novel workflow data analytics is achieved using computational methods whose efficacy has been enhanced by the continuous collection of tracking data that can be potentially collected. Case studies from our own research in the emergency department at the Mayo Clinic, are used as illustration. Finally, we use visualization techniques that can be used to convey workflow related information as well as a proof-of-concept visualization dashboard, which can be used to provide continuous and consistent feedback to clinical target users. This will facilitate self-assessment of workflow and related behaviors and potentially detect bottlenecks and sources of error.
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The research in this chapter was supported by grant #R01HS022670 from the Agency for Healthcare Research and Quality (AHRQ). The content is sole responsibility of the authors and does not necessarily represent the official views of the AHRQ.
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Vankipuram, A., Patel, V.L. (2019). Automated Location Tracking in Clinical Environments: A Review of Systems and Impact on Workflow Analysis. In: Zheng, K., Westbrook, J., Kannampallil, T., Patel, V. (eds) Cognitive Informatics. Health Informatics. Springer, Cham. https://doi.org/10.1007/978-3-030-16916-9_14
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