Using common data elements to foster interoperability of research on health disparities
Common data elements (CDEs) are standardized questions, variables, or measures with specific sets of responses that are used across multiple studies. They are organized around a particular research topic or question, validated, and defined via a consensus building process. Their use fosters compara...
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| मुख्य लेखकों: | , |
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| स्वरूप: | लेख |
| भाषा: | अंग्रेज़ी |
| प्रकाशित: |
International Association for Social Science Information Service and Technology
2025-06-01
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| श्रृंखला: | IASSIST Quarterly |
| विषय: | |
| ऑनलाइन पहुंच: | https://iassistquarterly.com/index.php/iassist/article/view/1112 |
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| सारांश: | Common data elements (CDEs) are standardized questions, variables, or measures with specific sets of responses that are used across multiple studies. They are organized around a particular research topic or question, validated, and defined via a consensus building process. Their use fosters comparability of results and findings across studies. CDEs are more common in NIH-funded clinical and biomedical research than in social, behavioral, and economic (SBE) research. Yet the community-driven, consensus-building approach to defining CDEs makes them well suited to measuring complex social phenomena. The Social, Behavioral, and Economic COVID Coordinating Center at ICPSR (SBE CCC) is leading the effort to establish CDEs for SBE research into the effects of the COVID-19 pandemic. We are collaborating with fifteen NIH-funded research teams who are examining pandemic-related health disparities related to race, ethnicity, sex, geography, income, and other factors. In this article, we discuss ways in which CDEs support research into health disparities and describe our process for identifying, validating, and building consensus on CDEs related to COVID public health policies.
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| आईएसएसएन: | 2331-4141 |