Dataset Information

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

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.

SUBMITTER: Guo GN

PROVIDER: S-EPMC7647230 | biostudies-literature | 2019 Nov

REPOSITORIES: biostudies-literature

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Publications

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

Guo Guan N GN Jonnagaddala Jitendra J Farshid Sanjay S Huser Vojtech V Reich Christian C Liaw Siaw-Teng ST

Journal of the American Medical Informatics Association : JAMIA 20191101 11

<h4>Objective</h4>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 ...[more]

PMID: 31545380

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Project description:PurposeThe aims of this study were to (1) quantify the multidimensional attributes of male and female basketball athletes under 16 years of age (U16) and under 18 years of age (U18), and (2) identify attributes that distinguish selection into a talent pathway according to sex and age group.Methods67 male and 71 female athletes competing in U16 and U18 selection trials for a state based Australian basketball talent pathway completed a multidimensional testing battery. The test battery consisted of anthropometric, physical (20- linear sprint, countermovement jump height, Yo-Yo Intermittent Recovery Test Level 2), technical (Basketball Jump Shooting Accuracy Test), tactical (video decision making), and psychological (Sports Orientation Questionnaire, Psychological Performance Inventory-Alternative) assessments. Mean differences and independent t-tests were used to assess comparative differences between selected and non-selected athletes within each age and sex cohort. Stepwise discriminant analyses were used to identify attributes that were the strongest discriminators of selection in each group (male U16, male U18, female U16, and female U18).ResultsThe discrimminant models showed for male U16 athletes smaller height (ES = -0.18) and greater shooting accuracy (ES = 0.52) was most discriminant of selection. Results were largely homogenous for male U18 athletes with lower visualisation score (ES = -0.62) most discriminant of selection. In female cohorts, faster 20-m sprint time (ES = -0.66) and taller height (ES = 0.58) was most discriminant of selection in U16 athletes while greater shooting accuracy (ES = 0.67), countermovement jump height (ES = 1.04), and height (ES = 0.65) was most discriminant of selection in U18 athletes.ConclusionsThese results emphasise the differing selection priorities within adolescent basketball cohorts according to sex and age group. The testing of anthropometric, physical and technical attributes may hold particular utility in adolescent female basketball given their identified importance to selection across U16 and U18 cohorts.

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Dataset Information

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

Objective

Materials and methods

Results

Conclusion

Publications

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

Similar Datasets

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