196391 Database and tools for the investigation of climate-mediated human disease

Monday, November 9, 2009

Jan Ihmels, PhD , Jaz Interactive, San Francisco, CA
Mark S. Smith, MD , Department of Emergency Medicine, Washington Hospital Center, Washington, DC
Alexey Kontsevoy , Health Solution Group/Enterprise R&D/Medical Media Lab, Microsoft Corporation, Washington, DC
Craig Feied, MD , Azyxxi-Health Solutions Group, Microsoft Corporation, Washington, MD
Jonathan Handler, MD , Azyxxi-Health Solutions Group, Microsoft Corporation, Washington, MD
David Roseman, MHA , Department of Emergency Medicine, Washington Hospital Center, Washington, DC
Andrea Valenta, MSN , Department of Emergency Medicine, Washington Hospital Center, Washington, DC
Michael Gillam, MD , Azyxxi-Health Solutions Group, Microsoft Corporation, Washington, MD
Dennis Fantin, PhD , Department of Chemistry and Biochemistry, California Polytechnic State University, San Luis Obispo, CA
The Climate Query database is designed to support research involving the interrelationships between meteorological factors and human disease. This database joins more than 88 terabytes of deidentified emergency department patient records from seven hospitals in the Washington D.C./Baltimore area with meteorological data obtained from the National Climatic Data Center (NCDC).

The database has been instantiated into the Microsoft Amalga™ system at the Center for Medical Informatics at MedStar Health in Washington D.C. The NCDC data is integrated with the existing patient records using automated parsing protocols. This allows for the investigation of connections between health-related and climate-related parameters.

A standard statistical toolset is linked to the database and can be utilized to evaluate a variety of climate and weather-mediated effects. One tool describes the ability to correlate a continuous numerical variable to a categorical set of variables.

At the core of the system are software modules that perform data retrieval and processing steps such as the passage of data over web services for analysis in MATLAB or SAS. Processed data from these systems, in XML for example, can then be presented to the end user, making it possible to generalize existing studies that were previously limited to a specific health condition, patient group and/or meteorological parameter. Such generalized studies will facilitate the search for novel relationships between climate, weather and human disease. Furthermore, any existing analysis can be re-evaluated as more data is added, resulting in ‘dynamic' studies that reflect the most current and comprehensive data available.

Learning Objectives:
At the completion of the session the learner will be able to: 1. Identify previously observed correlations between weather and human health conditions. 2. Explain the concept of a dynamic scientific study and it's advantages over traditional paper-based solutions. 3. Discuss the use of informatics to develop a database to support research and decision-making related to human disease that is caused, triggered, modified, or predicted by changes in climatologic conditions.

Keywords: Health Information Systems, Climate

Presenting author's disclosure statement:

Qualified on the content I am responsible for because: My doctorate work in computational genomics centered on the statistical and computational analysis of large biomedical datasets. Combined with my background in programming and database techniques, this puts me in a good position for the project described.
Any relevant financial relationships? No

I agree to comply with the American Public Health Association Conflict of Interest and Commercial Support Guidelines, and to disclose to the participants any off-label or experimental uses of a commercial product or service discussed in my presentation.

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