Multiple Scale Visualization of Electronic Health Records to Support Finding Medical Narratives

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dc.contributor.authorLinden, Sanne van deren_US
dc.contributor.authorWijk, Jarke J. vanen_US
dc.contributor.authorFunk, Mathiasen_US
dc.contributor.editorOeltze-Jafra, Steffen and Smit, Noeska N. and Sommer, Björn and Nieselt, Kay and Schultz, Thomasen_US
dc.date.accessioned2021-09-21T08:09:49Z
dc.date.available2021-09-21T08:09:49Z
dc.date.issued2021
dc.description.abstractElectronic Health Records (EHRs) contain rich medical information about patients, possibly hundreds of notes, lab results, images and other information. Doctors can easily be overwhelmed by this wealth of information. For their daily work, they need to derive narratives from all this information to get insights into the main issues of their patients. Standard solutions show all the information in linear lists, often leading to cognitive overload; research solutions provide timelines and relations between the notes but provide too much fragmented information. We propose MEDeNAR, a system for enabling medical professionals to obtain insights from EHRs based on the different tasks in their workflow. The key aspects of our system are the introduction of an intermediate level that summarizes the information using clustering and NLP methods. The results are visualized along a timeline and provide easy access to the detailed descriptions in notes and lab results at the EHR level. We designed the system using an iterative design process in collaboration with 18 doctors, two nurses and 14 domain experts. During the final evaluation, the doctors ranked our system higher than a standard baseline solution and a variation for the used NLP methods.en_US
dc.description.sectionheadersFrom the spatial to the abstract
dc.description.seriesinformationEurographics Workshop on Visual Computing for Biology and Medicine
dc.identifier.doi10.2312/vcbm.20211351
dc.identifier.isbn978-3-03868-140-3
dc.identifier.issn2070-5786
dc.identifier.pages113-122
dc.identifier.urihttps://doi.org/10.2312/vcbm.20211351
dc.identifier.urihttps://diglib.eg.org:443/handle/10.2312/vcbm20211351
dc.publisherThe Eurographics Associationen_US
dc.subjectHuman centered computing
dc.subjectVisualization toolkits
dc.subjectUser interface toolkits
dc.titleMultiple Scale Visualization of Electronic Health Records to Support Finding Medical Narrativesen_US
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VCBM 2021: Eurographics Workshop on Visual Computing for Biology and Medicine