Abstract
Data from electronic health records (EHRs) are becoming accessible for use in clinical improvement projects and nursing research. But the data quality may not meet clinicians' and researchers' needs. EHR data, which are primarily collected to document clinical care, invariably contain errors and omissions. This article introduces nurses to the secondary analysis of EHR data, first outlining the steps in data acquisition and then describing a theory-based process for evaluating data quality and cleaning the data. This process involves methodically examining the data using six data quality dimensions-completeness, correctness, concordance, plausibility, currency, and relevance-and helps the clinician or researcher to determine whether data for each variable are fit for use. Two case studies offer examples of problems that can arise and their solutions.
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
