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Electronic health record data quality assessment and tools: a systematic review
Abigail E Lewis1,2, Nicole Weiskopf3, Zachary B Abrams2
1Division of Computational and Data Sciences, Washington University in St. Louis, St. Louis, Missouri, USA.
Summary
Recent studies show increased publications on electronic health record (EHR) data quality assessment. While common dimensions like completeness are consistently evaluated, a standardized approach for EHR data quality remains elusive, highlighting the need for scalable guidelines.
Area of Science:
- Health Informatics
- Data Science
- Medical Record Management
Background:
- Electronic Health Records (EHRs) are crucial for healthcare delivery and research.
- Assessing the quality of EHR data is essential for reliable clinical decision-making and research outcomes.
- A 2013 literature review established baseline methodologies for EHR data quality assessment.
Conclusions:
- Despite increased research, a standardized methodology for EHR data quality assessment is still lacking.
- There is a need for scalable and flexible guidelines to enhance the efficiency, transparency, comparability, and interoperability of EHR data quality assessment.
- Automation may facilitate a generalized approach to EHR data quality assessment.
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