Medicine utilization studies in Australian individual‐level dispensing data: A blinded, multi‐center replicated analysis

Author:

Gillies Malcolm B.12ORCID,Bharat Chrianna23,Camacho Ximena12,Daniels Benjamin12,Hall Kelly24ORCID,Kelly Thu‐Lan24ORCID,Kelty Erin25ORCID,Lin Jialing12,Litchfield Melisa12,Lopez Derrick25,Noghrehchi Firouzeh26,Raubenheimer Jacques26,Varney Bianca12,Pratt Nicole24ORCID

Affiliation:

1. Medicines Intelligence Research Program School of Population Health, UNSW Sydney Kensington Australia

2. Methods and Data Working Group, NHMRC Centre of Research Excellence in Medicines Intelligence University of South Australia, University of New South Wales, University of Sydney, University of Western Australia Australia

3. National Drug and Alcohol Research Centre UNSW Sydney Kensington Australia

4. Quality Use of Medicines and Pharmacy Research Centre, Clinical and Health Sciences University of South Australia Adelaide Australia

5. School of Population and Global Health University of Western Australia Perth Australia

6. The University of Sydney, Faculty of Medicine and Health, School of Medical Sciences, Biomedical Informatics and Digital Health Translational Australian Clinical Toxicology Research Group Australia

Abstract

AbstractPurposeMedicine dispensing data require extensive preparation when used for research and decisions during this process may lead to results that do not replicate between independent studies. We conducted an experiment to examine the impact of these decisions on results of a study measuring discontinuation, intensification, and switching in a cohort of patients initiating metformin.MethodsFour Australian sites independently developed a HARmonized Protocol template to Enhance Reproducibility (HARPER) protocol and executed their analyses using the Australian Pharmaceutical Benefits Scheme 10% sample dataset. Each site calculated cohort size and demographics and measured treatment events including discontinuation, switch to another diabetes medicine, and intensification (addition of another diabetes medicine). Time to event and hazard ratios for associations between cohort characteristics and each event were also calculated. Concordance was assessed by measuring deviations from the calculated median of each value across the sites.ResultsGood agreement was found across sites for the number of initiators (median: 53 127, range: 51 848–55 273), gender (56.9% female, range: 56.8%–57.1%) and age group. Each site employed different methods for estimating days supply and used different operational definitions for the treatment events. Consequently, poor agreement was found for incidence of discontinuation (median 55%, range: 34%–67%), switching (median 3.5%, range: 1%–7%), intensification (median 8%, range: 5%–12%), time to event estimates and hazard ratios.ConclusionsDifferences in analytical decisions when deriving exposure from dispensing data affect replicability. Detailed analytical protocols, such as HARPER, are critical for transparency of operational definitions and interpretations of key study parameters.

Funder

University of New South Wales

National Drug and Alcohol Research Centre

Cancer Institute NSW

National Health and Medical Research Council

Publisher

Wiley

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