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    Factors affecting general practitioners' decisions to adopt new prescription drugs - Cohort analyses using Australian longitudinal physician survey data

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    Author
    Zhang, Y; Méndez, SJ; Scott, A
    Date
    2019-02-07
    Source Title
    BMC Health Services Research
    Publisher
    BioMed Central
    University of Melbourne Author/s
    Mendez, Susan; Scott, Anthony; Zhang, Yuting
    Affiliation
    Melbourne Institute of Applied Economic and Social Research
    Metadata
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    Document Type
    Journal Article
    Citations
    Zhang, Y., Méndez, S. J. & Scott, A. (2019). Factors affecting general practitioners' decisions to adopt new prescription drugs - Cohort analyses using Australian longitudinal physician survey data. BMC Health Services Research, 19 (1), https://doi.org/10.1186/s12913-019-3889-4.
    Access Status
    Open Access
    URI
    http://hdl.handle.net/11343/253781
    DOI
    10.1186/s12913-019-3889-4
    Abstract
    Background: We investigate factors affecting Australian general practitioners' decisions to adopt novel oral anticoagulants (NOACs) for the prevention of stroke/systemic embolism among patients with atrial fibrillation. Australia has a national homogeneous review and coverage system, which enables us to distinguish physician level factors while maintaining system level factors and patient coverage information constant. Methods: We conduct a cohort analyses by using longitudinal physician survey data from the Medicine in Australia: Balancing Employment and Life panel survey of Australian physicians (MABEL). MABEL data contain rich physician-level information such as age, gender, education, risk preferences, personality, physicians' communications with other medical professionals, and other practice characteristics. Importantly, the survey data were linked, with physician's consent, to actual utilization data from the Australian Pharmaceutical Benefits Scheme and the Medicare Benefits Schedule between January 1, 2012 and December 31, 2015. We measure speed (days until first time prescribing) of adopting NOACs. We estimate a Cox proportional hazard model to estimate factors affecting the adoption speed. Results: Several factors predict earlier adoption of NOACs: being male, more likely to take clinical risk, higher prescribing volume, being a principal or partner in the practice instead of an employee, spending less time in a typical consultation, and practicing in more affluent areas or areas with a higher proportion of older patients. GPs in Queensland are more likely to adopt NOACs and more likely to be extensive early adopters compared to other GPs. Other characteristics including physician personality, family circumstances, their involvement with public hospitals and teaching activities, and the distance between physician practice location to other clinics in the area are not statistically associated with earlier adoption. Conclusions: Our paper is one of the first to study the relationship between GPs' risk preferences, personality and their decisions to adopt new prescription drugs. Because NOACs are commonly prescribed and considered more cost-effective than their older counterpart, understanding factors affecting physicians' decisions to adopt NOACs has direct policy implications. Our results also highlight that even with universal coverage for prescription drugs, access to new drugs is different among patients, partially because who their doctors are and where they practice.

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