Toward Designing Information Display to Support Critical Care. A Qualitative Contextual Evaluation and Visioning Effort.

Abstract

Electronic health information overload makes it difficult for providers to quickly find and interpret information to support care decisions. The purpose of this study was to better understand how clinicians use information in critical care to support the design of improved presentation of electronic health information. We conducted a contextual analysis and visioning project. We used an eye-tracker to record 20 clinicians' information use activities in critical care settings. We played video recordings back to clinicians in retrospective cued interviews and queried: 1) context and goals of information use, 2) impacts of current display design on use, and 3) processes related to information use. We analyzed interview transcripts using grounded theory-based content analysis techniques and identified emerging themes. From these, we conducted a visioning activity with a team of subject matter experts and identified key areas for focus of design and research for future display designs. Analyses revealed four unique critical care information use activities including new patient assessment, known patient status review, specific directed information seeking, and review and prioritization of multiple patients. Emerging themes were primarily related to a need for better representation of dynamic data such as vital signs and laboratory results, usability issues associated with reducing cognitive load and supporting efficient interaction, and processes for managing information. Visions for the future included designs that: 1) provide rapid access to new information, 2) organize by systems or problems as well as by current versus historical patient data, and 3) apply intelligence toward detecting and representing change and urgency. The results from this study can be used to guide the design of future acute care electronic health information display. Additional research and collaboration is needed to refine and implement intelligent graphical user interfaces to improve clinical information organization and prioritization to support care decisions.