Comparison of the cohort selection performance of Australian Medicines Terminology to Anatomical Therapeutic Chemical mappings

Guan N Guo; Jitendra Jonnagaddala; Sanjay Farshid; Vojtech Huser; Christian Reich; Siaw-Teng Liaw

doi:10.1093/jamia/ocz143

Comparison of the cohort selection performance of Australian Medicines Terminology to Anatomical Therapeutic Chemical mappings

J Am Med Inform Assoc. 2019 Nov 1;26(11):1237-1246. doi: 10.1093/jamia/ocz143.

Authors

Guan N Guo^{1

2}, Jitendra Jonnagaddala^{1

2}, Sanjay Farshid¹, Vojtech Huser³, Christian Reich⁴, Siaw-Teng Liaw^{1

2}

Affiliations

¹ School of Public Health and Community Medicine, University of New South Wales, Sydney, Australia.
² WHO Collaborating Centre for eHealth, University of New South Wales, Sydney, Australia.
³ Lister Hill National Centre for Biomedical Communications, National Library of Medicine National Institutes of Health, Bethesda, Maryland, USA.
⁴ IQVIA, Cambridge, Massachusetts, USA.

Abstract

Objective: Electronic health records are increasingly utilized for observational and clinical research. Identification of cohorts using electronic health records is an important step in this process. Previous studies largely focused on the methods of cohort selection, but there is little evidence on the impact of underlying vocabularies and mappings between vocabularies used for cohort selection. We aim to compare the cohort selection performance using Australian Medicines Terminology to Anatomical Therapeutic Chemical (ATC) mappings from 2 different sources. These mappings were taken from the Observational Medical Outcomes Partnership Common Data Model (OMOP-CDM) and the Pharmaceutical Benefits Scheme (PBS) schedule.

Materials and methods: We retrieved patients from the electronic Practice Based Research Network data repository using 3 ATC classification groups (A10, N02A, N06A). The retrieved patients were further verified manually and pooled to form a reference standard which was used to assess the accuracy of mappings using precision, recall, and F measure metrics.

Results: The OMOP-CDM mappings identified 2.6%, 15.2%, and 24.4% more drugs than the PBS mappings in the A10, N02A and N06A groups respectively. Despite this, the PBS mappings generally performed the same in cohort selection as OMOP-CDM mappings except for the N02A Opioids group, where a significantly greater number of patients were retrieved. Both mappings exhibited variable recall, but perfect precision, with all drugs found to be correctly identified.

Conclusion: We found that 1 of the 3 ATC groups had a significant difference and this affected cohort selection performance. Our findings highlighted that underlying terminology mappings can greatly impact cohort selection accuracy. Clinical researchers should carefully evaluate vocabulary mapping sources including methodologies used to develop those mappings.

Keywords: Australian Medicines Terminology; anatomical therapeutic chemical classification; clinical trials; cohort selection; electronic health records.

Publication types

Comparative Study
Research Support, N.I.H., Extramural
Research Support, Non-U.S. Gov't

MeSH terms

Australia
Electronic Health Records*
Humans
Information Storage and Retrieval / methods
Patient Selection*
Pharmaceutical Preparations / classification*
Systematized Nomenclature of Medicine
Terminology as Topic*
Vocabulary, Controlled*

Substances

Pharmaceutical Preparations