Standardizing Representation of Medication in LMICs: Case of Malawi and RxNORM

Abstract

Background:

Sharing medication data between different health systems is essential for continuity of care. To provide common and consistent representation of medication data across disparate health systems, the National Library of Medicine (NLM) developed RxNORM; a normalized naming system for generic and branded drugs that facilitates semantic interoperation between different drug terminologies. RxNORM has become the standard vocabulary for representing medicines in the United States.

Objective: To assess the extent to which RxNORM concepts can be used to accurately represent essential medicine from a setting outside the United States.

Methods: To assess the coverage of RxNORM for medicine outside the United States, we used the 2015 Malawi Essential Medicines (MEML-2015) list as a test case. Terms from the list were transcribed electronically for easy processing and matched to RxNORM concepts using exact and partial matching algorithms. Results from the electronic matching were manually verified for correctness. All terms that could not be matched using the algorithms were manually searched for in RxNORM to ensure accurate classification as a term without a corresponding RxNORM concept.

Results: Of the 603 unique MEML-2015 medicines, 63% could be accurately represented by active RxNORM concepts. Anti-infectives were the class of medicines with the most unmatched medicines. Four other classes of medicine had complete coverage by RxNORM concepts.

Conclusion: A significant number of essential medicines could not be accurately represented using RxNORM concepts. A framework for adding such medicine as RxNORM concepts while maintaining continuous integration with periodical RxNORM updates is needed.