Medication data harmonization and utilization patterns during pregnancy across claims, electronic health record, and health information exchange data sources
Jianing Liu, Chienwei Chiang, Xiaofu Liu, Sara K Quinney, Christopher W Bartlett, Shaun Grannis, Lang LiAbstract
Objectives
To harmonize pregnancy medication records across heterogeneous real-world data sources and assess the comparability of recorded medication utilization.
Materials and Methods
We analyzed pregnancy medication records from MarketScan administrative claims, the Indiana Network for Patient Care health information exchange, and the Ohio State University Medical Center electronic health record (EHR) system. A deterministic, rule-based pipeline resolved drug names to RxNorm ingredient concepts and mapped them to Anatomical Therapeutic Chemical (ATC) classes. We evaluated mapping coverage and compared utilization using shared ingredient counts, Jaccard similarity across rank thresholds, correlations, and therapeutic-class distributions.
Results
Of 3094 ingredient components across sources, 3085 (99.7%) resolved to RxNorm concepts; 93.9% of resolved components carried an ATC code (93.4%-94.4% by source). The 3 sources shared 759 ingredients, with pairwise Jaccard similarities of 0.68-0.70 across complete lists. However, claims and EHR shared only 2 of their top 10 medications (Jaccard similarity, 0.11), with similarity increasing steadily as more medications were included in the ranked lists. Anatomical Therapeutic Chemical level-2 analysis identified 15 source-enriched classes. Medications identified in only one source had low recorded utilization.
Discussion
High mapping coverage enabled comparison using standardized medication concepts, but substantial utilization differences remained. These patterns were consistent with differences in care settings and medication capture, although their individual contributions could not be isolated.
Conclusion
This framework supports pregnancy medication research by enabling cross-source comparisons and identifying utilization differences requiring source-specific interpretation. Terminology standardization should be accompanied by consideration of how each source generates and captures medication records.