In:
eGEMs (Generating Evidence & Methods to improve patient outcomes), Ubiquity Press, Ltd., Vol. 5, No. 1 ( 2017-06-12), p. 8-
Abstract:
Objective: To compare rule-based data quality (DQ) assessment approaches across
multiple national clinical data sharing organizations.Methods: Six organizations with established data quality assessment (DQA) programs provided documentation or source code
describing current DQ checks. DQ checks were mapped to the categories within the data verification context of the harmonized DQA terminology. To ensure all DQ checks were
consistently mapped, conventions were developed and four iterations of mapping performed. Difficult-to-map DQ checks were discussed with research team members until
consensus was achieved.Results: Participating organizations provided 11,026 DQ checks, of which 99.97 percent were successfully mapped to a DQA category. Of the mapped DQ
checks (N=11,023), 214 (1.94 percent) mapped to multiple DQA categories. The majority of DQ checks mapped to Atemporal Plausibility (49.60 percent), Value Conformance (17.84
percent), and Atemporal Completeness (12.98 percent) categories.Discussion: Using the common DQA terminology, near-complete (99.97 percent) coverage across a wide range of
DQA programs and specifications was reached. Comparing the distributions of mapped DQ checks revealed important differences between participating organizations. This
variation may be related to the organization’s stakeholder requirements, primary analytical focus, or maturity of their DQA program. Not within scope, mapping checks
within the data validation context of the terminology may provide additional insights into DQA practice differences.Conclusion: A common DQA terminology provides a means to
help organizations and researchers understand the coverage of their current DQA efforts as well as highlight potential areas for additional DQA development. Sharing DQ checks
between organizations could help expand the scope of DQA across clinical data networks.
Type of Medium:
Online Resource
ISSN:
2327-9214
Language:
Unknown
Publisher:
Ubiquity Press, Ltd.
Publication Date:
2017
detail.hit.zdb_id:
2734659-6
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