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Integrating pharmacy and registry data strengthens clinical assessments of patient adherence


Serhal, S and Armour, C and Billot, L and Krass, I and Emmerton, L and Saini, B and Bosnic-Anticevich, S and Bereznicki, B and Bereznicki, L and Shan, S and Campain, A, Integrating pharmacy and registry data strengthens clinical assessments of patient adherence, Frontiers in Pharmacology, 13 Article 869162. ISSN 1663-9812 (2022) [Refereed Article]

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Copyright Statement

Copyright 2022 Serhal, Armour, Billot, Krass, Emmerton, Saini, Bosnic- Anticevich, Bereznicki, Bereznicki, Shan and Campain. This is an open-access article distributed under the terms of the Creative Commons Attribution 4.0 International (CC BY 4.0) License ( The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

DOI: doi:10.3389/fphar.2022.869162


Background: Accurate clinical assessment of patient adherence using reliable and valid measures is essential in establishing the presence of adherence issues and support practices for pharmacists.

Objective: This investigation aims to conduct a novel assessment of patient adherence to asthma controller therapy by combining 1) patient-specific dosage data found in pharmacy dispensing data with 2) centrally collected administrative claims records, to determine the added value of using both sources of data.

Methods: A total of 381 clinically uncontrolled asthma patients, from 95 community pharmacies across three Australian States were recruited and provided consent for the retrieval of their claims records and pharmacy dispensing data. Patients were stratified as multiple or single pharmacy users and adherence scores were calculated via the proportion of days covered (PDC) method using 1) patient claims records, 2) patient pharmacy dispensing data, and 3) combined claims records and pharmacy dispensing data. Cohort and subgroup adherence estimates were then compared.

Results: Low levels of adherence were evident amongst the cohort irrespective of the data source used. PDC estimates based on claims records alone or combined claims records and pharmacy dispensing data were significantly higher than estimates based on pharmacy dispensing data for the total cohort (56%, 52%, 42% respectively, p < 0.001) and more noticeably for multiple pharmacy users (67%, 64%, 35% respectively, p < 0.001). PDC estimates based on combined claims records and pharmacy dispensing data were significantly lower than estimates based on claims records alone, indicating that perhaps standard daily dose is not a robust proxy for prescribed dosage to inhaled respiratory devices in adherence approximations. Poorer adherence was found amongst single pharmacy users than multiple pharmacy users when combined claims records and pharmacy dispensing data (46% compared to 64% respectively, p < 0.001) or claims records alone (51% compared to 67% respectively, p < 0.001) were compared.

Conclusion: Access to routine collected data increases clinical acuity over patient adherence to asthma controller medications and is a valuable resource for health care professionals. A policy of secure accessibility of such data at the patient-pharmacist or patient-GP interface may allow real-time intervention and assist in decision making across numerous therapeutic areas.

Item Details

Item Type:Refereed Article
Keywords:asthma, medication adherence, data linkage, pharmacy, primary care, routinely collected data, pharmacy refill data, pharmaceutical benefits scheme
Research Division:Biomedical and Clinical Sciences
Research Group:Cardiovascular medicine and haematology
Research Field:Respiratory diseases
Objective Division:Health
Objective Group:Clinical health
Objective Field:Treatment of human diseases and conditions
UTAS Author:Bereznicki, B (Dr Bonnie Bereznicki)
UTAS Author:Bereznicki, L (Professor Luke Bereznicki)
ID Code:149365
Year Published:2022
Deposited By:Medicine
Deposited On:2022-03-28
Last Modified:2022-05-31
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