User Interface and Visualization for Electronic Health Records
~ SharpC at Maryland ~

photo of doctor in white coat

Participants

Project Description

The University of Maryland is one of the nine institutions participating in the National Center for Cognitive Informatics and Decision Making in Healthcare (NCCD) led by The University of Texas Health Science Center at Houston. NCCD is funded by the Office of the National Coordinator for Health IT under the Strategic Health IT Advanced Research Projects (SHARP) Program. This program seeks to support improvements in the quality, safety and efficiency of health care through advanced information technology. The NCCD award was one of four presented by the Office of the National Coordinator for Health Information Technology (ONC) through the American Recovery and Reinvestment Act of 2009 to address key barriers to health information technology. NCCD's research focus area is Patient-Centered Cognitive Suport.

In the first phase of this project we exploring prototype user interfaces for 1) tracking lab orders (focusing on how to avoid missing labs), and 2) medication reconciliation (focusing on interaction to combine separate lists into a single reconsiled list).
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Publications

Reviews: Medication reconciliation:
Missed labs:

Events

Lectures

Other Project related activies

Project Partners

Sponsorship

This work is supported in part by Grant No. 10510592 for Patient-Centered Cognitive Support under the Strategic Health IT Advanced Research Projects Program (SHARP) from the Office of the National Coordinator for Health Information Technology.

Related Projects from HCIL

Lifelines - Visual summary of a single patient record (1996-1998)
Lifelines2:  Discovering Temporal Categorical Patterns Across Multiple Records
+++NEWS+++ Oct.2011: Lifelines2 is now integrated in i2b2 and BTRIS (see UMd news story).
LifeFlow:  Visualization of event sequences
Searching Categorical Histories with PatternFinder: Query Support for Electronic Health Records
PatternFinder in Amalga: Temporal Query and Result Visualization in Action
Similan: Finding Similar Records from Temporal Categorical Data