Finding the Needles in a Haystack: a Journey to Improve Data Quality in EHRs
Qingxia (Cindy) Chen, PhD Vanderbilt University Medical Center
Electronic Health Records (EHR) systems have been increasingly implemented at US hospitals. Large amounts of longitudinal and detailed patient information, including lab tests, medications, disease status, and treatment outcome, have been accumulated and are available electronically. These large clinical databases are valuable and cost-effective data sources for clinical and translational research. Dense and irregularly recorded vital signs and lab measurements are great components of EHRs with potential entry errors. Manual evaluation is time- and cost-consuming and hence infeasible if not impossible. Using weight and height as examples, we will illustrate the challenges and possible solutions. We will also apply the methods to a Growth Chart Study using EHR data.