Reporting Data Quality Assessment Results: Identifying Individual and Organizational Barriers and Solutions. Issue 1 (4th September 2017)

• Record Type: Journal Article
• Authors: Callahan, Tiffany; Barnard, Juliana; Helmkamp, Laura; Maertens, Julie; Kahn, Michael
• Is Part Of: EGEMS. Volume 5:Issue 1(2017)
• Publication Date: 2017-09-04
• Subjects: Medical records -- Data processing -- Periodicals; Medical care -- Data processing -- Periodicals; Medical Records; Automatic Data Processing; Medical care -- Data processing; Medical records -- Data processing; Periodicals; Periodicals; 651.504261
• DOI: 10.5334/egems.214
• Languages: English
• ISSNs: 2327-9214

Abstract

Introduction: Electronic health record (EHR) data are known to have significant data quality issues, yet the practice and frequency of assessing EHR data is unknown. We sought to understand current practices and attitudes towards reporting data quality assessment (DQA) results by data professionals. Methods: The project was conducted in four Phases: (1) examined current DQA practices among informatics/CER stakeholders via engagement meeting (07/2014); (2) characterized organizations conducting DQA by interviewing key personnel and data management professionals (07-08/2014); (3) developed and administered an anonymous survey to data professionals (03-06/2015); and (4) validated survey results during a follow-up informatics/CER stakeholder engagement meeting (06/2016). Results: The first engagement meeting identified the theme of unintended consequences as a primary barrier to DQA. Interviewees were predominantly medical groups serving distributed networks with formalized DQAs. Consistent with the interviews, most survey (N=111) respondents utilized DQA processes/programs. A lack of resources and clear definitions of how to judge the quality of a dataset were the most commonly cited individual barriers. Vague quality action plans/expectations and data owners not trained in problem identification and problem-solving skills were the most commonly cited organizational barriers. Solutions included allocating resources for DQA, establishing standards and guidelines, and changing organizational culture. Discussion: Several barriers affecting DQA and reporting were identified. Community alignment towards systematic DQA and reporting is needed to overcome these barriers. Conclusion: Understanding barriers and solutions to DQA reporting is vital for establishing trust in the secondary use of EHR data for quality improvement and the pursuit of personalized medicine.