Evidence map›Paper›PMID 40452459›Full record

ArticlePharmacoepidemiology and drug safety2025

Estimation of the Duration of Antihypertensive Prescriptions: Validation of a Data-Driven Approach Using Rotterdam Study Data.

Chau L B Ho, David Youens, Walter P Abhayaratna, Max K Bulsara, Jeff Hughes, Rachael Moorin, Sallie-Anne Pearson, David B Preen, Christopher M Reid, Rikje Ruiter and 6 more

Abstract readValidation Study
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Article in Pharmacoepidemiology and drug safety, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

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2 · The registry

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3 · Its place in the literature

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4 · The record

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5 · Who and what money

Authors and funding

16 authors.

Chau L B HoSchool of Population Health, Faculty of Health Sciences, Curtin University, Perth, Australia.ORCID https://orcid.org/0000-0002-4285-9409
David YouensSchool of Population Health, Faculty of Health Sciences, Curtin University, Perth, Australia.
Walter P AbhayaratnaCanberra Health Services, ACT, Canberra, Australia.
Max K BulsaraInstitute for Health Research, The University of Notre Dame Australia, Fremantle, Australia.
Jeff HughesCurtin Medical School, Curtin University, Perth, Australia.
Rachael MoorinSchool of Population Health, Faculty of Health Sciences, Curtin University, Perth, Australia.
Sallie-Anne PearsonSchool of Population Health, University of New South Wales, Sydney, Australia.
David B PreenSchool of Population and Global Health, The University of Western Australia, Perth, Australia.
Christopher M ReidSchool of Population Health, Faculty of Health Sciences, Curtin University, Perth, Australia.
Rikje RuiterDepartment of Epidemiology, Erasmus MC - University Medical Centre, Rotterdam, the Netherlands.
Christobel M SaundersMedical School, The University of Western Australia, Perth, Australia.
Bruno H StrickerDepartment of Epidemiology, Erasmus MC - University Medical Centre, Rotterdam, the Netherlands.
John StubbsIndependent Cancer Consumer Advisor, Sydney, Australia.
Frank J A van RooijDepartment of Epidemiology, Erasmus MC - University Medical Centre, Rotterdam, the Netherlands.
Cameron WrightSchool of Population Health, Faculty of Health Sciences, Curtin University, Perth, Australia.
Ninh Thi HaSchool of Population Health, Faculty of Health Sciences, Curtin University, Perth, Australia.

Funding

National Health and Medical Research Council APP2014896
6 · The paper itself

Abstract

objectivesAdministrative medicine dispensing data often omit prescribed duration, which is important for research on adherence or other pharmacoepidemiological topics. While the reverse waiting time distribution (rWTD) method has been widely used to estimate prescribed durations, its accuracy in real-world dispensing data is unknown. We assessed the performance of the rWTD method against the actual prescribed duration recorded in the Rotterdam Study.

methods100 725 antihypertensive (AHT) prescriptions from 2018 to 2019 were extracted from the Rotterdam Study's medicine data. Data were constructed into five scenarios with increasing variability in the number of medicines included and variations in prescribed duration. The rWTD with 10 random index dates with or without adjustment for the quantity of dispensed medicine was conducted in all scenarios. Relative differences and limit of agreement ratio based on Bland-Altman analysis were used to examine agreement between estimated and actual prescribed durations.

resultsrWTD models without adjustment for the quantity of dispensed medicine performed well only in the most homogenous scenario. In scenarios with greater data variability, performance improved significantly when adjusted for the quantity of dispensed medicine. Relative difference decreased from ≥ 65% in models without covariates to ≤ 20% with covariates, and the limit of agreement ratio decreased from ≥ 36.8 in models without covariates to ≤ 5.3 with covariates. Stratification analysis by subclass of the AHT medicines provided similar results.

conclusionsThe study demonstrated that as data variability increased, the accuracy of the rWTD estimations decreased. However, the rWTD can produce good estimates (relative difference from 0% to 28%) of prescribed duration for AHT medicines, with the highest accuracy in the model adjusting for the quantity of dispensed medicine or stratification of the data with a relative difference less than 20% and the limit of agreement ratio less than 5.3 for the estimation at the 90th percentile of inter-arrival density. Since this validation was limited to antihypertensive medicines, generalizing the finding to other chronic-use medicines should be undertaken with caution.

Indexed as

Antihypertensive AgentsDrug PrescriptionsHypertensionPharmacoepidemiologyAgedAged, 80 and overDatabases, FactualFemaleHumansMaleMiddle AgedNetherlandsTime FactorsAntihypertensive Agentshypertensionpharmacoepidemiologyprescription durationwaiting time distribution

Identifiers

PMID40452459
PMCPMC12127836

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