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Intensive care units (ICUs) are complex and data-rich environments. Dataroutinely collected in the ICUs provides tremendous opportunities for machinelearning, but their use comes with significant challenges. Complex problems mayrequire additional input from humans which can be provided through a process ofdata annotation. Annotation is a complex, time-consuming process that requiresdomain expertise and technical proficiency. Existing data annotation tools failto provide an effective solution to this problem. In this study, weinvestigated clinicians' approach to the annotation task. We focused onestablishing the characteristics of the annotation process in the context ofclinical data and identifying differences in the annotation workflow betweendifferent staff roles. The overall goal was to elicit requirements for asoftware tool that could facilitate an effective and time-efficient dataannotation. We conducted an experiment involving clinicians from the ICUsannotating printed sheets of data. The participants were observed during thetask and their actions were analysed in the context of Norman's InteractionCycle to establish the requirements for the digital tool. The annotationprocess followed a constant loop of annotation and evaluation, during whichparticipants incrementally analysed and annotated the data. No distinguishabledifferences were identified between how different staff roles annotate data. Weobserved preferences towards different methods for applying annotation whichvaried between different participants and admissions. We established 11requirements for the digital data annotation tool for the healthcare setting.We conducted a manual data annotation activity to establish the requirementsfor a digital data annotation tool, characterised the clinicians' approach toannotation and elicited 11 key requirements for effective data annotationsoftware.

Capturing Requirements for a Data Annotation Tool for Intensive Care: Experimental User-Centered Design Study