Abstract
The work of a hospital’s medical staff is safety critical and often occurs under severe time constraints. To provide timely and effective cognitive support to medical teams working in such contexts, guidelines in the form of best practice workflows for healthcare have been developed by medical organizations. However, the high cognitive load imposed in such stressful and rapidly changing environments poses significant challenges to the medical staff or team in adhering to these workflows. In collaboration with physicians and nurses from Carle Foundation Hospital, we first studied and modeled medical team’s individual responsibilities and interactions in cardiac arrest resuscitation and decomposed their overall task into a set of distinct cognitive tasks that must be specifically supported to achieve successful human-centered system design. We then developed a medical Best Practice Guidance (BPG) system for reducing medical teams’ cognitive load, thus fostering real-time adherence to best practices. We evaluated the resulting system with physicians and nurses using a professional patient simulator used for medical training and certification. The evaluation results point to a reduction of cognitive load and enhanced adherence to medical best practices.
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Cardiac arrest is a sudden stop in effective blood circulation due to abrupt loss of heart function.
Giving sodium bicarbonate without providing adequate ventilation to the patient may further worsen acidosis.
Code 99 is an emergent situation where the patient is not breathing and/or has no pulse.
IV or IO infusion is to infuse fluid or medication directly into the patient’s vein or marrow.
Confirmation bias is a tendency to search for or interpret information in a way that confirms one’s preconceptions, leading to statistical errors [27].
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This work is funded by NSF (CNS 13-30077 and CNS 13-29886).
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Wu, P., Nam, MY., Choi, J. et al. Supporting Emergency Medical Care Teams with an Integrated Status Display Providing Real-Time Access to Medical Best Practices, Workflow Tracking, and Patient Data. J Med Syst 41, 186 (2017). https://doi.org/10.1007/s10916-017-0829-x
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DOI: https://doi.org/10.1007/s10916-017-0829-x