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Aligning temporal data by sentinel events: discovering patterns in electronic health records
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Conference on Human Factors in Computing Systems archive
Proceeding of the twenty-sixth annual SIGCHI conference on Human factors in computing systems table of contents
Florence, Italy
SESSION: Health and Wellness table of contents
Pages 457-466  
Year of Publication: 2008
ISBN:978-1-60558-011-1
Authors
Taowei David Wang  University of Maryland, College Park, MD, USA
Catherine Plaisant  University of Maryland, College Park, MD, USA
Alexander J. Quinn  University of Maryland, College Park, MD, USA
Roman Stanchak  University of Maryland, College Park, MD, USA
Shawn Murphy  Massachusetts General Hospital, Boston, MA, USA
Ben Shneiderman  University of Maryland, College Park, MD, USA
Sponsors
ACM: Association for Computing Machinery
SIGCHI: ACM Special Interest Group on Computer-Human Interaction
Publisher
ACM  New York, NY, USA
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ABSTRACT

Electronic Health Records (EHRs) and other temporal databases contain hidden patterns that reveal important cause-and-effect phenomena. Finding these patterns is a challenge when using traditional query languages and tabular displays. We present an interactive visual tool that complements query formulation by providing operations to align, rank and filter the results, and to visualize estimates of the intervals of validity of the data. Display of patient histories aligned on sentinel events (such as a first heart attack) enables users to spot precursor, co-occurring, and aftereffect events. A controlled study demonstrates the benefits of providing alignment (with a 61% speed improvement for complex tasks). A qualitative study and interviews with medical professionals demonstrates that the interface can be learned quickly and seems to address their needs.


REFERENCES

Note: OCR errors may be found in this Reference List extracted from the full text article. ACM has opted to expose the complete List rather than only correct and linked references.

 
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Collaborative Colleagues:
Taowei David Wang: colleagues
Catherine Plaisant: colleagues
Alexander J. Quinn: colleagues
Roman Stanchak: colleagues
Shawn Murphy: colleagues
Ben Shneiderman: colleagues