Appl Clin Inform 2017; 08(04): 1012-1021
DOI: 10.4338/ACI-2017-03-RA-0042
Research Article
Schattauer GmbH Stuttgart

Quantifying the Effect of Data Quality on the Validity of an eMeasure

Steven G. Johnson
Stuart Speedie
Gyorgy Simon
Vipin Kumar
Bonnie L. Westra
Further Information

Publication History

10 March 2017

28 August 2017

Publication Date:
14 December 2017 (online)


Objective The objective of this study was to demonstrate the utility of a healthcare data quality framework by using it to measure the impact of synthetic data quality issues on the validity of an eMeasure (CMS178—urinary catheter removal after surgery).

Methods Data quality issues were artificially created by systematically degrading the underlying quality of EHR data using two methods: independent and correlated degradation. A linear model that describes the change in the events included in the eMeasure quantifies the impact of each data quality issue.

Results Catheter duration had the most impact on the CMS178 eMeasure with every 1% reduction in data quality causing a 1.21% increase in the number of missing events. For birth date and admission type, every 1% reduction in data quality resulted in a 1% increase in missing events.

Conclusion This research demonstrated that the impact of data quality issues can be quantified using a generalized process and that the CMS178 eMeasure, as currently defined, may not measure how well an organization is meeting the intended best practice goal. Secondary use of EHR data is warranted only if the data are of sufficient quality. The assessment approach described in this study demonstrates how the impact of data quality issues on an eMeasure can be quantified and the approach can be generalized for other data analysis tasks. Healthcare organizations can prioritize data quality improvement efforts to focus on the areas that will have the most impact on validity and assess whether the values that are reported should be trusted.

Protection of Human and Animal Subjects

De-identified EHR data were used for this research and proper precautions were taken to minimize privacy risk. Patients were allowed to opt out of having their medical data used for research. IRB approval was obtained (University of Minnesota IRB #1412E57982).