Development of a Multi-Factorial Data Quality Score for Primary Care Electronic Medical Records
Abstract
As healthcare providers transitioned from paper-based records to electronic medical records (EMRs), researchers gained access to more patient and care data, with greater detail. Current research regarding Canadian primary care EMR data suggests the quality of data is variable. For researchers who wish to use EMR data, it is important to have a method of evaluating data quality that is applicable to multiple EMR datasets so research quality can be assured. There is currently no unified scoring system for primary care EMR data. This thesis built on previous EMR data quality research by developing and testing a composite measure of data quality using previously-validated quality measures that assessed the data quality domains of completeness, correctness, and currency. A composite data quality score was created and tested using data splitting. This scoring system could be used by researchers to examine EMR data quality and compare data quality across data sources.