Challenges in using electronic health record data for CER: experience of 4 learning organizations and solutions applied

Med Care. 2013 Aug;51(8 Suppl 3):S80-6. doi: 10.1097/MLR.0b013e31829b1d48.


Objective: To document the strengths and challenges of using electronic health records (EHRs) for comparative effectiveness research (CER).

Methods: A replicated case study of comparative effectiveness in hypertension treatment was conducted across 4 health systems, with instructions to extract data and document problems encountered using a specified list of required data elements. Researchers at each health system documented successes and challenges, and suggested solutions for addressing challenges.

Results: Data challenges fell into 5 categories: missing data, erroneous data, uninterpretable data, inconsistencies among providers and over time, and data stored in noncoded text notes. Suggested strategies to address these issues include data validation steps, use of surrogate markers, natural language processing, and statistical techniques.

Discussion: A number of EHR issues can hamper the extraction of valid data for cross-health system comparative effectiveness studies. Our case example cautions against a blind reliance on EHR data as a single definitive data source. Nevertheless, EHR data are superior to administrative or claims data alone, and are cheaper and timelier than clinical trials or manual chart reviews. All 4 participating health systems are pursuing pathways to more effectively use EHR data for CER.A partnership between clinicians, researchers, and information technology specialists is encouraged as a way to capitalize on the wealth of information contained in the EHR. Future developments in both technology and care delivery hold promise for improvement in the ability to use EHR data for CER.

MeSH terms

  • Clinical Coding
  • Comparative Effectiveness Research / organization & administration*
  • Comparative Effectiveness Research / standards
  • Data Collection / methods*
  • Data Collection / standards*
  • Electronic Health Records / organization & administration*
  • Electronic Health Records / standards
  • Humans
  • Multicenter Studies as Topic / methods
  • Multicenter Studies as Topic / standards
  • Natural Language Processing
  • Research Design*
  • Systems Integration