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PatternFinder in AMALGA: Temporal Query Formulation and Result Visualization in Action

 

Project Description

The core ideas of PatternFinder has been implemented in real medical systems.  Through the collaboration with Washington Hospital Center, we have integrated both the sophisticated query specification for temporal patterns and the ball-and-chain result visualization with their production system Amalga (previously called Azyxxi).  The query forms have adopted the look and feel of the existing Amalga interface to help physicians and medical personnel to adapt.  The query form has been simplified to not overwhelm the users.  The top screenshot shows  patients with Hemoglobin level increasing by 50% within 10 days then decreasing 30% within 10 days.  Results are presented both in a table view (bottom) and in the visual overview (to the right).  For each patient all events that match the query are summarized, and users can expand to see more details about all combinations of matching events. The three filters have green, purple, and blue circles, which show up in the results display on the left side, indicating a match for a filter.

Currently the implementation is undergoing internal usability testing with real data and physicians who routinely access them.

 Participants

Videos

June, 2007: Demo of an early implementation (.avi, 2.41MB)

Publications

Plaisant, C., Lam, S., Shneiderman, B., Smith, M., Roseman, D., Marchand, G., Gillam, M., Feied, C., Handler, J., Rappaport, H. (May 2008)
Searching Electronic Health Records for Temporal Patterns in Patient Histories: A Case Study with Microsoft Amalga
To appear in AMIA 2008 Fall symposium (final PDF version)

Lam, S., (May 2008)
PatternFinder in Microsoft Amalga: Temporal Query Formulation and Result Visualization in Action - CS dept. Honors Paper

Sponsors and Partners

This project is supported in part by the Washington Hospital Center 

Related Projects from HCIL

PatternFinder:  Integrated interface for visual query and result-set visualization for search and discovery of temporal patterns within multivariate and categorical data sets.

Lifelines:  Visualizing patient records, criminal records, and personal histories.

Lifelines2: Discovering temporal categorical patterns across multiple records.

Related Workshops from HCIL

Personal Medical Devices Workshop: Increasing Patient Healthcare Participation (June 3, 2004)

Interactive Visual Exploration of Electronic Health Records (May 30, 2008)