Display Settings:

Format

Send to:

Choose Destination
We are sorry, but NCBI web applications do not support your browser and may not function properly. More information
    J Gen Intern Med. 2010 Apr;25(4):284-90. doi: 10.1007/s11606-010-1253-9. Epub 2010 Feb 4.

    Primary medication non-adherence: analysis of 195,930 electronic prescriptions.

    Source

    Division of Pharmacoepidemiology and Pharmacoeconomics, Brigham and Women's Hospital, Boston, MA 02120, USA. mfischer@partners.org

    Abstract

    BACKGROUND:

    Non-adherence to essential medications represents an important public health problem. Little is known about the frequency with which patients fail to fill prescriptions when new medications are started ("primary non-adherence") or predictors of failure to fill.

    OBJECTIVE:

    Evaluate primary non-adherence in community-based practices and identify predictors of non-adherence.

    PARTICIPANTS:

    75,589 patients treated by 1,217 prescribers in the first year of a community-based e-prescribing initiative.

    DESIGN:

    We compiled all e-prescriptions written over a 12-month period and used filled claims to identify filled prescriptions. We calculated primary adherence and non-adherence rates for all e-prescriptions and for new medication starts and compared the rates across patient and medication characteristics. Using multivariable regressions analyses, we examined which characteristics were associated with non-adherence.

    MAIN MEASURES:

    Primary medication non-adherence.

    KEY RESULTS:

    Of 195,930 e-prescriptions, 151,837 (78%) were filled. Of 82,245 e-prescriptions for new medications, 58,984 (72%) were filled. Primary adherence rates were higher for prescriptions written by primary care specialists, especially pediatricians (84%). Patients aged 18 and younger filled prescriptions at the highest rate (87%). In multivariate analyses, medication class was the strongest predictor of adherence, and non-adherence was common for newly prescribed medications treating chronic conditions such as hypertension (28.4%), hyperlipidemia (28.2%), and diabetes (31.4%).

    CONCLUSIONS:

    Many e-prescriptions were not filled. Previous studies of medication non-adherence failed to capture these prescriptions. Efforts to increase primary adherence could dramatically improve the effectiveness of medication therapy. Interventions that target specific medication classes may be most effective.

    Comment in

    PMID:
    20131023
    [PubMed - indexed for MEDLINE]
    PMCID:
    PMC2842539
    Free PMC Article

    Images from this publication.See all images (1)Free text

    Figure 1

      Supplemental Content

      Icon for Springer Icon for PubMed Central

      Save items

      Recent activity

      Your browsing activity is empty.

      Activity recording is turned off.

      Turn recording back on

      See more...
      Write to the Help Desk