Methods and dimensions of electronic health record data quality assessment: enabling reuse for clinical research

First Review

Objective

The purpose of this paper is to review the methods and dimensions of data quality assessment in regards to the secondary use of electronic health records (EHR) data for research. The goal is to develop a knowledge base on the methods used in establishing the suitability of EHR data for specific research goals.

Methods

A literary review was performed on clinical research literature discussing data quality assessment methods for EHR. A search was performed using standard electronic bibliographic tools. Through iterative review of the data abstracted, broad dimensions of data quality and general categories of assessment strategies were derived.

Results

The majority of literature reviewed focused on structured data alone (73%), or a combination of structured and unstructured data (22%). Five different dimensions of data quality were derived from the literature, which include: completeness, correctness, concordance, plausibility, and currency. Similarly, the common methods of data quality assessment were identified in seven categories, which includes: gold standard, data element agreement, element presence, data source agreement, distribution comparison, validity check, and log review.

Discussion

Secondary use of clinical data is essential to research, and on examination of methods used by clinical researchers to investigate the quality and suitability of EHR data, it shows that quality may be difficult to measure. Recommendations are given for researchers interested in the reuse of EHR data for clinical research. Researchers may consider the adoption of consistent taxonomy of EHR quality; remain aware of the task-dependence of data quality; integrate work on data quality assessment from other fields; and adopt systematic, empirically driven, statistically based methods of data quality assessment.

Conclusion

The reuse of EHR data is promising in the area of research, but problems arise with data quality derived from the EHR. This in turn necessitates the use of quality assessment methodologies to determine the suitability of these data for any given research.

My Comments

Secondary use of health data is essential to the clinical research field as well as quality improvement and patient safety. That being said, it is imperative to ensure the quality of data derived from EHR, and whether it is suitable for the specific research goals. This paper looks at the assessment of EHR data quality and makes recommendations on what researchers should adopt with secondary use of EHR.