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

J Gen Intern Med. 2010 Apr;25(4):284-90. doi: 10.1007/s11606-010-1253-9. Epub 2010 Feb 4.

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.

Publication types

  • Research Support, N.I.H., Extramural
  • Research Support, U.S. Gov't, P.H.S.

MeSH terms

  • Adolescent
  • Adult
  • Aged
  • Child
  • Child, Preschool
  • Community Pharmacy Services / statistics & numerical data*
  • Confidence Intervals
  • Databases, Factual
  • Electronic Prescribing / statistics & numerical data*
  • Female
  • Health Care Surveys
  • Humans
  • Infant
  • Information Systems / organization & administration
  • Information Systems / statistics & numerical data
  • Male
  • Medical Records Systems, Computerized / organization & administration
  • Medical Records Systems, Computerized / statistics & numerical data*
  • Medication Adherence / statistics & numerical data*
  • Middle Aged
  • Odds Ratio
  • Statistics as Topic
  • Time Factors
  • United States
  • Young Adult