IDEAS home Printed from https://ideas.repec.org/a/sae/medema/v39y2019i3p278-293.html
   My bibliography  Save this article

Prescriber Variation in Relation to Prescribing Trends within the Preferred Drugs Initiative in Ireland (2012–2015): An Interrupted Time-Series Study Using Latent Curve Models

Author

Listed:
  • Ronald D. McDowell

    (Health Research Board (HRB) Centre for Primary Care Research, Department of General Practice, Royal College of Surgeons in Ireland Medical School, Dublin 2, Ireland
    Centre for Public Health, School of Medicine, Dentistry and Biomedical Sciences, Queen’s University, Belfast, UK)

  • Kathleen Bennett

    (Division of Population Health Sciences, Royal College of Surgeons in Ireland, Dublin 2, Ireland)

  • Frank Moriarty

    (Health Research Board (HRB) Centre for Primary Care Research, Department of General Practice, Royal College of Surgeons in Ireland Medical School, Dublin 2, Ireland)

  • Sarah Clarke

    (Health Service Executive Medicines Management Programme, Trinity Centre for Health Sciences, St. James’s Hospital, Dublin 8, Ireland)

  • Michael Barry

    (National Centre for Pharmacoeconomics, Trinity Centre for Health Sciences, St. James’s Hospital, Dublin 8, Ireland)

  • Tom Fahey

    (Health Research Board (HRB) Centre for Primary Care Research, Department of General Practice, Royal College of Surgeons in Ireland Medical School, Dublin 2, Ireland)

Abstract

Objectives. To examine the impact of the Preferred Drugs Initiative (PDI), an Irish health policy aimed at reducing prescribing variation. Design. Interrupted time series spanning 2012 to 2015. Setting. Health Service Executive pharmacy claims data for General Medical Services (GMS) patients, approximately 40% of the Irish population. Participants. Prescribers issuing preferred drug group items to GMS adults before and after PDI guidelines. Primary Outcome. The percentage coverage of PDI medications within each drug class per calendar quarter per prescriber. Methods. Latent curve models with structured residuals (LCM-SRs) were used to model coverage of the preferred drugs over time. The number of GMS adults receiving medication and the percentage who were 65 years and older at the start of the study were included as covariates. Results. In the quarter following PDI guidelines, coverage of the preferred drugs increased most in absolute terms for proton pump inhibitors (PPIs) (1.50% [SE 0.15], P

Suggested Citation

  • Ronald D. McDowell & Kathleen Bennett & Frank Moriarty & Sarah Clarke & Michael Barry & Tom Fahey, 2019. "Prescriber Variation in Relation to Prescribing Trends within the Preferred Drugs Initiative in Ireland (2012–2015): An Interrupted Time-Series Study Using Latent Curve Models," Medical Decision Making, , vol. 39(3), pages 278-293, April.
    • Handle: RePEc:sae:medema:v:39:y:2019:i:3:p:278-293
    DOI: 10.1177/0272989X18818165
    as

    Download full text from publisher

    File URL: https://journals.sagepub.com/doi/10.1177/0272989X18818165
    Download Restriction: no
    File URL: https://libkey.io/10.1177/0272989X18818165?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    References listed on IDEAS

    as
    1. A. ConwayLenihan & S. Ahern & S. Moore & J. Cronin & N. Woods, 2016. "Factors influencing the variation in GMS prescribing expenditure in Ireland," Health Economics Review, Springer, vol. 6(1), pages 1-8, December.
    2. Maria Ferrao Barbosa & Harvey Goldstein, 2000. "Discrete Response Multilevel Models for Repeated Measures: An Application to Voting Intentions Data," Quality & Quantity: International Journal of Methodology, Springer, vol. 34(3), pages 323-330, August.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.

      Corrections

      All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:sae:medema:v:39:y:2019:i:3:p:278-293. See general information about how to correct material in RePEc.

      If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

      If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

      If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

      For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: SAGE Publications (email available below). General contact details of provider: .

      Please note that corrections may take a couple of weeks to filter through the various RePEc services.

      IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.