Interactive Information Visualization to Explore and Query Electronic Health Records

TitleInteractive Information Visualization to Explore and Query Electronic Health Records
Publication TypeJournal Article
Year of Publication2013
AuthorsRind, A., T. D. Wang, W. Aigner, S. Miksch, K. Wongsuphasawat, C. Plaisant, and B. Shneiderman
JournalFoundations and Trends in Human-Computer Interaction
Date Published02/2013
ISBN Number978-1-60198-642-9

Physicians are confronted with increasingly complex patient histories from which they must make life-critical treatment decisions.  At the same time, clinical researchers are eager to study the growing databases of patient histories to detect unknown patterns, ensure quality control, and discover surprising outcomes.  Designers of Electronic Health Record systems (EHRs) have great potential to apply  innovative visual methods to support clinical decision-making and research. This work surveys the state-of-the-art of information visualization systems for exploring and querying EHRs, as described in the scientific literature. We examine how systems differ in their features and highlight how these differences are related to their design and the medical scenarios they tackle.  The systems are compared on a set of criteria: (1) data types covered, (2) multivariate analysis support, (3) number of patient records used (one or multiple), and (4) user intents addressed.  Based on our survey and evidence gained from evaluation studies, we believe that effective information visualization can facilitate analysis of EHRs  for patient treatment and clinical research.  Thus, we encourage the information visualization community to study the application of their systems in health care. Our survey is written for both scientific researchers and designers of future user interfaces for EHRs.  We hope it will help them understand this vital domain and appreciate the features and virtues of existing systems  so they can create still more advanced systems.  We identify potential future research topics in interactive support for data abstraction, in systems for intermittent users such as patients, and in more detailed evaluations.


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