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Primary Medication Non-Adherence: Analysis of 195,930 Electronic Prescriptions

Journal of General Internal Medicine volume 25, pages 284–290 (2010)Cite this article

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.

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Acknowledgements

We acknowledge the assistance of BCBSMA, Tufts HP, and ZixCorp in providing data. The investigators retained control over all aspects of the analyses and presentation of results.

The research was supported by AHRQ grant R01 HS15175.

Dr. Brookhart is supported by a career development grant from NIH (AG12084).

Dr. Shrank is supported by a career development grant from NIH (HL090505).

Conflict of Interest

None disclosed.

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Authors and Affiliations

  1. Division of Pharmacoepidemiology and Pharmacoeconomics, Brigham and Women’s Hospital, 1620 Tremont Street, Suite 3030, Boston, MA, 02120, USA

    Michael A. Fischer MD, MS, Margaret R. Stedman PhD, Joyce Lii MS, MA, William H. Shrank MD, MSHS & M. Alan Brookhart PhD

  2. Institute for Health Policy, Massachusetts General Hospital, Boston, MA, USA

    Christine Vogeli PhD & Joel S. Weissman PhD

Authors
  1. Michael A. Fischer MD, MS
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  2. Margaret R. Stedman PhD
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  3. Joyce Lii MS, MA
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  4. Christine Vogeli PhD
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  5. William H. Shrank MD, MSHS
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  6. M. Alan Brookhart PhD
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  7. Joel S. Weissman PhD
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Corresponding author

Correspondence to Michael A. Fischer MD, MS.

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Fischer, M.A., Stedman, M.R., Lii, J. et al. Primary Medication Non-Adherence: Analysis of 195,930 Electronic Prescriptions. J GEN INTERN MED 25, 284–290 (2010). https://doi.org/10.1007/s11606-010-1253-9

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  • DOI: https://doi.org/10.1007/s11606-010-1253-9

KEY WORDS

  • adherence
  • non-adherence
  • electronic prescribing
  • health information technology