Evaluating Foundational Data Quality in the National Patient-Centered Clinical Research Network (PCORnet®)
View/ Open
Author
Qualls, Laura Goettinger
Phillips, Thomas A.
Hammill, Bradley G.
Topping, James
Louzao, Darcy M.
Curtis, Lesley H.
Marsolo, Keith
Published Version
https://doi.org/10.5334/egems.199Metadata
Show full item recordCitation
Qualls, Laura Goettinger, Thomas A. Phillips, Bradley G. Hammill, James Topping, Darcy M. Louzao, Jeffrey S. Brown, Lesley H. Curtis, and Keith Marsolo. 2018. “Evaluating Foundational Data Quality in the National Patient-Centered Clinical Research Network (PCORnet®).” eGEMs 6 (1): 3. doi:10.5334/egems.199. http://dx.doi.org/10.5334/egems.199.Abstract
Introduction: Distributed research networks (DRNs) are critical components of the strategic roadmaps for the National Institutes of Health and the Food and Drug Administration as they work to move toward large-scale systems of evidence generation. The National Patient-Centered Clinical Research Network (PCORnet®) is one of the first DRNs to incorporate electronic health record data from multiple domains on a national scale. Before conducting analyses in a DRN, it is important to assess the quality and characteristics of the data. Methods: PCORnet’s Coordinating Center is responsible for evaluating foundational data quality, or assessing fitness-for-use across a broad research portfolio, through a process called data curation. Data curation involves a set of analytic and querying activities to assess data quality coupled with maintenance of detailed documentation and ongoing communication with network partners. The first cycle of PCORnet data curation focused on six domains in the PCORnet common data model: demographics, diagnoses, encounters, enrollment, procedures, and vitals. Results: The data curation process led to improvements in foundational data quality. Notable improvements included the elimination of data model conformance errors; a decrease in implausible height, weight, and blood pressure values; an increase in the volume of diagnoses and procedures; and more complete data for key analytic variables. Based on the findings of the first cycle, we made modifications to the curation process to increase efficiencies and further reduce variation among data partners. Discussion: The iterative nature of the data curation process allows PCORnet to gradually increase the foundational level of data quality and reduce variability across the network. These activities help increase the transparency and reproducibility of analyses within PCORnet and can serve as a model for other DRNs.Other Sources
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5983028/pdf/Terms of Use
This article is made available under the terms and conditions applicable to Other Posted Material, as set forth at http://nrs.harvard.edu/urn-3:HUL.InstRepos:dash.current.terms-of-use#LAACitable link to this page
http://nrs.harvard.edu/urn-3:HUL.InstRepos:37298244
Collections
- HMS Scholarly Articles [17918]
Contact administrator regarding this item (to report mistakes or request changes)