NIH HEAL Clinical Data Elements (CDE) implementation: NIH HEAL Initiative IMPOWR network IDEA-CC

被引:16
作者
Adams, Meredith C. B. [1 ,2 ,3 ]
Hurley, Robert W. [4 ,5 ,6 ]
Siddons, Andrew [7 ]
Topaloglu, Umit [8 ]
Wandner, Laura D. [7 ]
机构
[1] Wake Forest Univ, Sch Med, Dept Anesthesiol, Med Ctr Blvd, Winston Salem, NC 27157 USA
[2] Wake Forest Univ, Sch Med, Dept Biomed Informat, Med Ctr Blvd, Winston Salem, NC 27157 USA
[3] Wake Forest Univ, Sch Med, Dept Publ Hlth Sci, Med Ctr Blvd, Winston Salem, NC 27157 USA
[4] Wake Forest Univ, Sch Med, Dept Anesthesiol, Winston Salem, NC 27157 USA
[5] Wake Forest Univ, Sch Med, Dept Neurobiol & Anat, Winston Salem, NC 27157 USA
[6] Wake Forest Univ, Sch Med, Dept Publ Hlth Sci, Winston Salem, NC 27157 USA
[7] NINDS, Bethesda, MD USA
[8] Wake Forest Univ, Sch Med, Dept Canc Biol, Winston Salem, NC 27157 USA
基金
美国国家卫生研究院;
关键词
PAIN; ARCHITECTURE; QUALITY; DRIVEN;
D O I
10.1093/pm/pnad018
中图分类号
R614 [麻醉学];
学科分类号
100217 ;
摘要
Objective The National Institutes of Health (NIH) HEAL Initiative is making data findable, accessible, interoperable, and reusable (FAIR) to maximize the value of the unprecedented federal investment in pain and opioid-use disorder research. This involves standardizing the use of common data elements (CDE) for clinical research. Methods This work describes the process of the selection, processing, harmonization, and design constraints of CDE across a pain and opioid use disorder clinical trials network (NIH HEAL IMPOWR). Results The network alignment allowed for incorporation of newer data standards across the clinical trials. Specific advances included geographic coding (RUCA), deidentified patient identifiers (GUID), shareable clinical survey libraries (REDCap), and concept mapping to standardized concepts (UMLS). Conclusions While complex, harmonization across a network of chronic pain and opioid use disorder clinical trials with separate interventions can be optimized through use of CDEs and data standardization processes. This standardization process will support the robust secondary data analyses. Scaling this process could standardize CDE results across interventions or disease state which could help inform insurance companies or government organizations about coverage determinations. The development of the HEAL CDE program supports connecting isolated studies and solutions to each other, but the practical aspects may be challenging for some studies to implement. Leveraging tools and technology to simplify process and create ready to use resources may support wider adoption of consistent data standards.
引用
收藏
页码:743 / 749
页数:7
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