Trends in retail clinic use among the commercially insured

Am J Manag Care. 2011 Nov;17(11):e443-448.


Objectives: To describe trends in retail clinic use among commercially insured patients and to identify which patient characteristics predict retail clinic use.

Study design: Retrospective cohort analysis of commercial insurance claims sampled from a population of 13.3 million patients in 22 markets in 2007 to 2009.

Methods: We identified 11 simple acute conditions that can be managed at a retail clinic and described trends in retail clinic utilization for these conditions. We used multiple logistic regressions to identify predictors of retail clinic versus another care site for these conditions and assessed whether those predictors changed over time.

Results: Retail clinic use increased 10-fold from 2007 to 2009. By 2009, 6.9% of all visits for the 11 conditions were to a retail clinic. Proximity to a retail clinic was the strongest predictor of use. Patients living within 1 mile of a retail clinic were 7.5% more likely to use one than those living 10 to 20 miles away (P <.001). Women (+0.9%, P <.001), young adults (+1.6%, P <.001), patients without a chronic condition (+0.9%, P <.001), and patients with high incomes (+2.6%, P <.001) were more likely to use retail clinics. All these associations became stronger over time. There was no association between primary care physician availability and retail clinic use.

Conclusions: If these trends continue, health plans will see a dramatic increase in retail clinic utilization. While use is increasing on average, it is particularly increasing among young, healthy, and higher income patients living close to retail clinics.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Acute Disease
  • Community Health Centers / statistics & numerical data*
  • Confidence Intervals
  • For-Profit Insurance Plans / statistics & numerical data*
  • Health Services Accessibility / statistics & numerical data*
  • Health Services Needs and Demand / statistics & numerical data*
  • Humans
  • Insurance Coverage / statistics & numerical data*
  • Logistic Models
  • Multivariate Analysis
  • Retrospective Studies
  • Statistics as Topic
  • United States