Assessing EHR Data for Use in Clinical Improvement and Research.

Area of Science:

• Nursing Informatics
• Health Data Science
• Clinical Research

Background:

• Electronic health records (EHRs) offer valuable data for clinical improvement and nursing research.
• However, EHR data quality often falls short of clinical and research requirements due to inherent errors and omissions.
• Secondary analysis of EHR data requires careful data acquisition and quality assessment.

Purpose of the Study:

• To introduce nurses to the secondary analysis of electronic health record (EHR) data.
• To outline a theory-based process for evaluating and cleaning EHR data for research and clinical improvement.
• To provide practical guidance on determining data fitness for use.

Main Methods:

• Description of data acquisition steps for EHR data.
• Presentation of a systematic, theory-based process for data quality evaluation.
• Utilizing six data quality dimensions: completeness, correctness, concordance, plausibility, currency, and relevance.

Main Results:

• A structured approach to examining EHR data quality is presented.
• The process helps identify and address errors and omissions in EHR data.
• Case studies illustrate common data quality problems and their resolutions.

Conclusions:

• Nurses and researchers can enhance the reliability of EHR data through systematic quality evaluation and cleaning.
• This methodology ensures that EHR data are fit for secondary analysis in clinical improvement and research.
• Adopting these practices improves the utility of EHR data for evidence-based healthcare.