Sociodemographic characteristics of communities served by retail clinics.
OBJECTIVE
As a rapidly growing new health care delivery model in the United States, retail clinics have been the subject of much debate and controversy. Located physically within a retail store, retail clinics provide simple acute and preventive services for a fixed price and without an appointment. Some hope that retail clinics can be a new safety-net provider for the poor and those without a primary care physician. To better understand the potential for retail clinics to achieve this goal, we describe the sociodemographic characteristics of the communities in which they operate.


METHODS
We created an inventory of all retail clinics in the United States and determined the proportion that are in a health professional shortage area (HPSA). We defined each retail clinic's catchment area as all census blocks that were less than a 5-minute driving distance from the clinic. We compared the sociodemographic characteristics of the population within and outside of these retail clinic catchment areas.


RESULTS
Of the 982 clinics in 32 states, 88.4% were in an urban area and 12.5% were in an HPSA (20.9% of the US population lives within an HPSA). Compared with the rest of the urban population, the population living within a retail clinic catchment area has a higher median household income ($52,849 vs $46,080), is better educated (32.6% vs 24.9% with a college degree), and is as likely to be uninsured (17.7% vs 17.0%). In a multivariate model, the census block's median household income had the strongest association with whether the census block was in a retail clinic catchment area (odds ratio, 3.63; 95% CI, 3.26-4.05; median income, > or =$54,779 vs <$30,781, respectively).


CONCLUSIONS
We found that relatively few retail clinics are located in HPSAs and that, compared with the rest of the urban population, the population living in close proximity to a retail clinic has a higher income.
Rudavsky
Rena
R
RAND Health, Pittsburgh, PA, USA.
Mehrotra
Ateev
A
D000554:Ambulatory Care Facilities / Q000600:supply & distribution*; D002391:Catchment Area, Health / Q000706:statistics & numerical data; D019352:Censuses; D003695:Delivery of Health Care / Q000706:statistics & numerical data*; D004522:Educational Status; D040362:Geographic Information Systems; D006297:Health Services Accessibility / Q000706:statistics & numerical data; D006302:Health Services Research; D006801:Humans; D007182:Income; D019458:Insurance Coverage / Q000706:statistics & numerical data; D008507:Medically Underserved Area; D015999:Multivariate Analysis; D020380:Needs Assessment / Q000706:statistics & numerical data; D057184:Practice Patterns, Nurses' / Q000706:statistics & numerical data*; D012423:Rural Health / Q000706:statistics & numerical data; D012959:Socioeconomic Factors; D012984:Software; D014481:United States; D014504:Urban Health / Q000706:statistics & numerical data