[Ieee_vis] Exploring Temporal Patterns in Electronic Health Records - Workshop - May 23

[Catherine Plaisant]

Workshop: Exploring Temporal Patterns in Electronic Health Records

May 23, 2013

University of Maryland

Organizers: Ben Shneiderman, Catherine Plaisant

Contact: plaisant at cs.umd.edu<mailto:plaisant at cs.umd.edu>

Webpage: www.cs.umd.edu/hcil/eventflow/workshop2013/<http://www.cs.umd.edu/hcil/eventflow/workshop2013/>


Electronic Health Record (EHR) databases contain millions of patient records including events such as diagnoses, test results or medication prescriptions. The use of EHR databases could be dramatically improved if easy-to-use interfaces allowed clinical researchers and quality improvement analysts to explore complex temporal patterns in order to build and test hypotheses regarding the benefits, risks, comparative effectiveness, and appropriateness of treatments or medication regimens. Novel strategies in interface design and information visualization are needed.<http://www.cs.umd.edu/hcil/eventflow/workshop2013/>



Format: This Thursday workshop will focus on in-depth discussions and presentations of the work of our collaborators and external researchers: 1) Users of HCIL tools such as EventFlow www.cs.umd.edu/hcil/eventflow<http://www.cs.umd.edu/hcil/eventflow>  will be invited to report on their case studies, and 2) other researchers working on similar topics will be invited to present their work. There will be ample time for discussion after each talk. Again, to hear the talks given by HCIL faculty and students please plan to attend other sessions of the symposium (talks on Wednesday and demos Thursday morning).



To participate: The workshop is opened to all (space permitting, so register early). If you are interested in presenting Please send email to Catherine Plaisant at plaisant at cs.umd.edu<mailto:plaisant at cs.umd.edu>  (preferably by May 1st) . Please summarize what you would like to present, and provide pointers to papers and screen shots as needed. We welcome those using visual approaches, statistical methods, machine learning, etc. to study temporal patterns in patient histories, where the goals may be to find common patterns, rare events, or matches to a given patient.  Topics might include data cleaning, integration from multiple sources, coping with incomplete or conflicting information, and presentation of result sets. If we receive too many requests, we may ask you to bring a poster for presentation during the breaks.

THIS WORKSHOP IS AN EVENT OF THE 30th HCIL ANNUAL SYMPOSIUM www.cs.umd.edu/hcil/soh<http://www.cs.umd.edu/hcil/soh>  May 22-23
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