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Development and exploration of polymedication network from Pharmaceutical and Medicare Benefits Scheme data

Published: 29 January 2019 Publication History

Abstract

Polypharmacy or concurrent intake of multiple medications is often associated with negative health outcomes and adverse drug reactions. Routinely collected administrative health data can be a potential and inexpensive alternative to study large population to understand this polypharmacy phenomenon and associated risk. However, synthesizing medication intakes from pharmaceutical records of administrative data can be challenging. In this study, we proposed a graph or network-based approach to understand polypharmacy utilizing the 10% Pharmaceutical and Medicare Benefits Scheme sample data in Australian healthcare context. We proposed methods to identify drug regimens from discrete information of drug dispenses. A polymedication network is then generated from the regimens. We also explored potential relationship among patients' age, medical and pharmaceutical costs and several categories of polymedication regimens. The result showed complex relationships among various drugs and signified the multimorbidity nature of the targeted treatments. Especially the long-term polymedication regimens are found to be focused on treating chronic conditions like cardiovascular diseases, diabetes, asthma, COPD and acid reflux, consistent with the Australian population's disease burden. The methods and networked approach presented in this study can act as a basis for further pharmacovigilance and identifying adverse drug reactions.

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Cited By

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  • (2023)Identification of polypharmacy patterns in new‐users of metformin using the Apriori algorithm: A novel framework for investigating concomitant drug utilization through association rule miningPharmacoepidemiology and Drug Safety10.1002/pds.558332:3(366-381)Online publication date: 9-Jan-2023
  • (2022)Major areas of interest of artificial intelligence research applied to health care administrative data: a scoping reviewFrontiers in Pharmacology10.3389/fphar.2022.94451613Online publication date: 18-Jul-2022
  • (2020)A Systematic Review of Network Studies Based on Administrative Health DataInternational Journal of Environmental Research and Public Health10.3390/ijerph1707256817:7(2568)Online publication date: 9-Apr-2020

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  1. Development and exploration of polymedication network from Pharmaceutical and Medicare Benefits Scheme data

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    cover image ACM Other conferences
    ACSW '19: Proceedings of the Australasian Computer Science Week Multiconference
    January 2019
    486 pages
    ISBN:9781450366038
    DOI:10.1145/3290688
    Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

    In-Cooperation

    • CORE - Computing Research and Education
    • Macquarie University-Sydney

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    New York, NY, United States

    Publication History

    Published: 29 January 2019

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    Author Tags

    1. Administrative data
    2. Data mining
    3. Medical informatics
    4. Network science
    5. Polymedication network
    6. Polypharmacy

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    • Research
    • Refereed limited

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    ACSW 2019
    ACSW 2019: Australasian Computer Science Week 2019
    January 29 - 31, 2019
    NSW, Sydney, Australia

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    ACSW '19 Paper Acceptance Rate 61 of 141 submissions, 43%;
    Overall Acceptance Rate 61 of 141 submissions, 43%

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    Cited By

    View all
    • (2023)Identification of polypharmacy patterns in new‐users of metformin using the Apriori algorithm: A novel framework for investigating concomitant drug utilization through association rule miningPharmacoepidemiology and Drug Safety10.1002/pds.558332:3(366-381)Online publication date: 9-Jan-2023
    • (2022)Major areas of interest of artificial intelligence research applied to health care administrative data: a scoping reviewFrontiers in Pharmacology10.3389/fphar.2022.94451613Online publication date: 18-Jul-2022
    • (2020)A Systematic Review of Network Studies Based on Administrative Health DataInternational Journal of Environmental Research and Public Health10.3390/ijerph1707256817:7(2568)Online publication date: 9-Apr-2020

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