Supporting clinical reasoning through visual summarization and presentation of patient data: a systematic review

Clinicians retrieve data from electronic health record (EHR) systems and summarize them into clinical information to accomplish clinical reasoning and decision-making tasks. Visualization, using meaningful summarization methods and intuitive presentation approaches, can enhance this process. This systematic review examines how EHR data are summarized, visualized, and aligned with the 7 clinical reasoning and decision-making tasks shared by clinicians.

We searched 7 databases for research articles on individual patient EHR related to visualization, clinical decision-support, and patient summaries. Evidence from included studies was extracted for EHR data types, information summarization methods, visualization strategies, clinician characteristics, and evaluations. The synthesized evidence generated data-information-visualization (data-info-vis) flows.

We included 112 studies of which 70 (62.5%) conducted detailed usability evaluations, while 42 (37.5%) did not report any evaluations. Gaps remain in deriving actionable insights from EHR data, particularly for tasks requiring data quality reports. Three representative data-info-vis flows emerge. The first uses structured data to generate patterns for temporal visualizations, supporting tasks such as diagnosis and patient management. The second abstracts data into miniature charts, aiding situation-aware understanding and knowledge synthesis. The third features high-level visual metaphors for complex and overarching tasks, such as achieving better care.

This review identifies 2 primary visualization strategies: (1) timeline-based presentations emphasizing temporal trends and longitudinal tracking, and (2) snapshot-based approaches focusing on status overviews and rapid assessments. The identified critical design approaches and distinct data-info-vis flows are tailored to clinical reasoning and decision-making tasks, offering insights for developing visualization-based decision-support tools.