Informing Environmental Health Decisions Through Data Integration Proceedings of a Workshop—in Brief (2018) / Chapter Skim
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Informing Environmental Health Decisions Through Data Integration: Proceedings of a Workshop - in Brief
Informing Environmental Health Decisions Through Data Integration: Proceedings of a Workshop - in Brief
Pages 1-11
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PROMISE, PERILS, AND FOUNDATIONS FOR DATA INTEGRATION The purpose of data integration for environmental health research and decision-making is to improve public health by monitoring environmental exposures and health outcomes, said Lance Waller from Emory University. The ultimate goal, Waller explained, is to link exposure and health outcome datasets to identify, propose, test, implement, and evaluate potential interventions.
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One of the main thrusts of data science, and particularly artificial intelligence, is not just solving problems faster by using existing methods designed for "small" datasets, but rethinking the analytical problem from the lens of being able to bring in more data, integrate them in new ways, and calibrate results with what is already known about a particular problem. When it comes to integrating data, Chris Gennings from the Icahn School of Medicine at Mount Sinai cautioned that big data are not always better.
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In addition, NIEHS has been developing a framework of environmental health science language and an ontology and has created several new offices that work together to further the applications of data science, big data, and data integration to environmental health issues. Birnbaum noted that there are plans to morph the CHEAR infrastructure into a health environmental assessment resource (HEAR)
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In the future, said Ritchie, geocoding using mobile sensors, zip codes, and questionnaires will be important for using EHR data in environmental health studies given that most environmental exposure data are not captured in the EHR today. However, there are databases with geolocated environmental data that could be integrated with EHR data.
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As an example of the type of research that is enabled by a huge, integrated database of health information, Butte described how he has used data in the University of California Research eXchange, which integrates EHR data from more than 15 million individuals in the University of California health system, to create maps of cause of death for Californians in the state. The map for alcohol-related illnesses was rather simple, while the map for heart disease was far more complex and showed that a major cause of death among individuals who have had a heart attack was sepsis that developed several years later.
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Since then, OpenTox has been constituted as an international nonprofit that recognizes the importance of open data, as well as open knowledge, methods, tools, and resources supporting productive toxicology, safety assessment, and risk management. Hardy said that OpenTox, which has encouraged the formation of local chapters, sponsors community activities such as data hackathons and workshops that bring data scientists and scientists from other fields together to develop data processing tools.
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SCIENCE, OPEN COLLABORATION, AND NEW METHODS The opportunity today in the world of data networking, said John Wilbanks of the nonprofit Sage Bionetworks, is in determining how to connect data silos, which is different than building data commons. In thinking about this problem, Wilbanks alluded to the three pillars of modern scientific methods -- team science, open science, and participant-centered science -- and 13 See https://cordis.europa.eu/project/rcn/97715_en.html.
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In the team phase, the research teams compare evidence to select the top targets, and in the final open phase, research and data will be presented to the larger community for input and external use. In another project on colorectal cancer subtyping, the individual teams generated four papers on four different subtypes using four different datasets and algorithms.
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By mapping the indoor space and combining building data with environmental and physiological measures, it is possible to understand how to design or modify spaces to optimize human performance and health, said Lunden. Currently, outdoor air pollution monitoring occurs with broad spatial resolution, but by piggybacking on Google's Street View cars, Aclima has been able to create what Lunden called hyper-local, city-wide maps of ozone, nitric and nitrous oxide, carbon black or soot, and particulate matter across different particle size ranges for the entire San Francisco–Oakland metropolitan area.
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Many workshop presenters and discussants emphasized that developing approaches for integrating data from multiple disparate sources has great potential for informing environmental health decisions. As emphasized by Waller, Gennings, and many other workshop participants, the challenges associated with data integration are significant, but investigators are making headway and producing results in forms that decision-makers find valuable.
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Ritchie, University of Pennsylvania; and Lance Waller, Emory University. Planning Committee for Informing Environmental Health Decisions Through Data Integration: Kim Boekelheide (Chair)
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