Applying an Electronic Health Records Data Quality Framework Across Service Sectors: A Case Study of Juvenile Justice System Data. Issue 1 (11th July 2019)

• Record Type: Journal Article
• Authors: Aalsma, Matthew C.; Schwartz, Katherine; Haight, Konrad A.; Jarjoura, G. Roger; Dir, Allyson L.
• Is Part Of: EGEMS. Volume 7:Issue 1(2019)
• Publication Date: 2019-07-11
• Subjects: electronic health records -- data quality -- juvenile justice system -- administrative data -- data linking; Medical records -- Data processing -- Periodicals; Medical care -- Data processing -- Periodicals; Medical Records; Automatic Data Processing; Medical care -- Data processing; Medical records -- Data processing; Periodicals; Periodicals; 651.504261
• DOI: 10.5334/egems.258
• Languages: English
• ISSNs: 2327-9214

Abstract

Context: Integrating electronic health records (EHR) with other sources of administrative data is key to identifying factors affecting the long-term health of traditionally underserved populations, such as individuals involved in the justice system. Linking existing administrative data from multiple sources overcomes many of the limitations of traditional prospective studies of population health, but the linking process assumes high levels of data quality and consistency within administrative data. Studies of EHR, unlike other types of administrative data, have provided guidance to evaluate the utility of big data for population health research. Case Description: Here, an established EHR data quality framework was applied to identify and describe the potential shortcomings of administrative juvenile justice system data collected by one of four case management systems (CMSs) across 12 counties in a Midwest state. The CMS data were reviewed for logical inconsistencies and compared along the data quality dimensions of plausibility and completeness. Major Themes: After applying the data quality framework, several patterns of logical inconsistencies within the data were identified. To resolve these inconsistencies, recommendations regarding data entry, review, and extraction are offered. Conclusion: The recommendations related to achieving quality justice system data can be applied to future efforts to link administrative databases from multiple sources. Increasing trust in administrative data quality related to vulnerable populations ultimately improves knowledge of pressing public health concerns.