Iterative heuristic design of temporal graphic displays with clinical domain experts.

Journal Article (Journal Article)

Conventional electronic health record information displays are not optimized for efficient information processing. Graphical displays that integrate patient information can improve information processing, especially in data-rich environments such as critical care. We propose an adaptable and reusable approach to patient information display with modular graphical components (widgets). We had two study objectives. First, reduce numerous widget prototype alternatives to preferred designs. Second, derive widget design feature recommendations. Using iterative human-centered design methods, we interviewed experts to hone design features of widgets displaying frequently measured data elements, e.g., heart rate, for acute care patient monitoring and real-time clinical decision-making. Participant responses to design queries were coded to calculate feature-set agreement, average prototype score, and prototype agreement. Two iterative interview cycles covering 64 design queries and 86 prototypes were needed to reach consensus on six feature sets. Interviewers agreed that line graphs with a smoothed or averaged trendline, 24-h timeframe, and gradient coloring for urgency were useful and informative features. Moreover, users agreed that widgets should include key functions: (1) adjustable reference ranges, (2) expandable timeframes, and (3) access to details on demand. Participants stated graphical widgets would be used to identify correlating patterns and compare abnormal measures across related data elements at a specific time. Combining theoretical principles and validated design methods was an effective and reproducible approach to designing widgets for healthcare displays. The findings suggest our widget design features and recommendations match critical care clinician expectations for graphical information display of continuous and frequently updated patient data.

Full Text

Cited Authors

  • Reese, TJ; Segall, N; Del Fiol, G; Tonna, JE; Kawamoto, K; Weir, C; Wright, MC

Published Date

  • October 2021

Published In

Volume / Issue

  • 35 / 5

Start / End Page

  • 1119 - 1131

PubMed ID

  • 32743757

Pubmed Central ID

  • PMC7854828

Electronic International Standard Serial Number (EISSN)

  • 1573-2614

Digital Object Identifier (DOI)

  • 10.1007/s10877-020-00571-2

Language

  • eng

Conference Location

  • Netherlands