Abstract
This quality improvement study examines trends in pharmacy closures in the United States between 2009 and 2015, as well as pharmacy, community, and market factors that might be associated with such closures.
Despite the critical role of pharmacies in the pharmaceutical supply chain and evidence that pharmacy closures contribute to nonadherence of prescription medications,1 there is limited information on the prevalence and risk factors for pharmacy closure. In this study, we examined trends in pharmacy closures in the United States between 2009 and 2015, and analyzed pharmacy, community, and market factors that might be associated with such closures. We hypothesized that pharmacies disproportionately serving publicly insured populations were at increased risk for closure owing to lower pharmacy reimbursement rates from Medicaid and Medicare.2 We also hypothesized that independent pharmacies were more likely to close because they often do not participate in preferred pharmacy networks.3
Methods
We used several data sources to conduct these analyses. National Council for Prescription Drug Programs data was used to determine the number and type of pharmacies (ie, chain, independent, mass merchandise, grocery, government, and/or clinic based) in operation that closed in the United States from 2009 through 2015.4 Pharmacy addresses were geocoded using ArcGIS, version 10.4 and linked to the American Community Survey 5-year data (2011-2015), Health Resources and Service Administration (HRSA) data, and US Census data to derive community (ie, urbanity, percentage minority, percentage living in poverty, medically underserved area status) and market (ie, ratio of public vs privately insured individuals, percentage uninsured, number of pharmacies per 10 000 persons) characteristics for each pharmacy at the county level.
This analysis included pharmacies in operation at any point during the study period except those that newly opened in 2015. First, we quantified the prevalence of our primary outcome of interest, pharmacy closure, over time at the national level. Second, we used Kaplan-Meier survival curves and discrete-time proportional hazard models to identify risk factors for pharmacy closure stratified by urbanity. We stratified by urbanity because pharmacies located in rural areas may operate under different financial incentives, including tiered pharmacy reimbursement rates for Medicaid prescriptions.5 Pharmacies that opened prior to 2009 entered the models that year; pharmacies that newly opened between 2009 and 2014 entered the models in the year of the opening. This study design provided six 1-year intervals during which a pharmacy closure could occur. We used a significance value of 5% in all testing; P values reported are 2-sided. Statistical analyses were performed with Stata, version 14. The institutional review board at the University of Illinois at Chicago determined that this study did not need approval because it was not considered human-subject research.
Results
From 2009 to 2015, the total number of US pharmacies increased by 7.8% from 62 815 to 67 721. Of the 74 883 pharmacies in operation at any point during this period, 9564 (12.8%) had closed by 2015 (Figure). The risk of closure was significantly greater in urban compared with nonurban areas (cumulative hazard rate from bivariate analyses: 16.2% vs 13.2%; multivariate hazard ratio [HR], 1.10; 95% CI, 1.04-1.17) (Table). In both urban (27.2%; HR, 3.15; 95% CI, 2.89-3.43) and nonurban (23%; HR, 2.90; 95% CI, 2.72-3.08) areas, independent pharmacies were more likely to close than their counterparts. In urban areas, pharmacies serving disproportionately low-income (HR, 1.9; 95% CI, 1.13-1.47), uninsured (HR, 2.11; 95% CI, 1.90-2.33), and publicly insured (HR, 2.29; 95% CI, 1.82-2.88) populations were at increased risk of closure. These factors were not associated with closure in nonurban areas.
Figure. Trends in Pharmacies in Operation, Closures, and Openings in the United States From 2009 Through 2015.
Trends in the number of pharmacies in operation and pharmacy openings and closures are statistically significant at P < .01 using Poisson regression. A total of 77 510 pharmacies were in operation between 2009 and 2015, of which 9568 pharmacies closed and 14 614 were newly opened. Aggregate closure rates were estimated among all pharmacies that were in operation at some point during 2009 through 2015, excluding pharmacies newly opened in 2015 (n = 74 883 pharmacies). Closure rates are defined as the number of pharmacies that closed divided by the number of pharmacies in operation during 2009 through 2015. Annualized mean closure rates were 2.5% (95% CI, 2.1%-3.0%).
Table. Proportional Hazard Model of Pharmacy Closures in the United States, 2009 Through 2015a.
| Characteristic | Urban (n = 23 159)b | Nonurban (n = 51 724)b | ||||
|---|---|---|---|---|---|---|
| Cumulative Hazard Rate | Hazard Ratio (95% CI) | Cumulative Hazard Rate | Hazard Ratio (95% CI) | |||
| Unadjusted | Multivariatec | Unadjusted | Multivariatec | |||
| Overall | 0.16 | 1.22 (1.17-1.28)d | 1.10 (1.04-1.17)d | 0.13 | 1 [Reference] | 1 [Reference] |
| Pharmacy type | ||||||
| Chain | 0.08 | 1 [Reference] | 1 [Reference] | 0.08 | 1 [Reference] | 1 [Reference] |
| Independent | 0.27 | 3.15 (2.89-3.43)d | 3.29 (3.01-3.59)d | 0.23 | 2.90 (2.72-3.08)d | 2.98 (2.80-3.17)d |
| Mass | 0.06 | 0.66 (0.54-0.82)d | 0.65 (0.53-0.81)d | 0.06 | 0.77 (0.69-0.87)d | 0.78 (0.70-0.88)d |
| Food | 0.13 | 1.49 (1.28-1.73)d | 1.45 (1.25-1.69)d | 0.10 | 1.30 (1.18-1.44)d | 1.30 (1.18-1.44)d |
| Clinic/government | 0.32 | 3.80 (3.30-4.37)d | 3.61 (3.14-4.15)d | 0.27 | 3.41 (3.07-3.79)d | 3.50 (3.14-3.89)d |
| County Characteristics e | ||||||
| Racial/ethnic minority, % | ||||||
| <50 | 0.14 | 1 [Reference] | 1 [Reference] | 0.13 | 1 [Reference] | 1 [Reference] |
| ≥50 | 0.17 | 1.18 (1.09-1.27)d | 0.72 (0.66-0.79)d | 0.15 | 1.12 (1.04-1.19)d | 1.12 (1.04-1.21)d |
| Living in poverty, % | ||||||
| <20 | 0.14 | 1 [Reference] | 1 [Reference] | 0.13 | 1 [Reference] | 1 [Reference] |
| ≥20 | 0.23 | 1.61 (1.50-1.74)d | 1.29 (1.13-1.47)d | 0.14 | 1.02 (0.95-1.09) | 0.92 (0.85-1.00) |
| Medically underserved area | ||||||
| No | 0.16 | 1 [Reference] | 1 [Reference] | 0.14 | 1 [Reference] | 1 [Reference] |
| Yes | 0.17 | 1.06 (0.95-1.19) | 1.14 (1.01-1.28)f | 0.13 | 0.93 (0.88-0.97)d | 0.84 (0.80-0.89)d |
| Market Characteristics | ||||||
| Uninsured, %g | ||||||
| <20 | 0.15 | 1 [Reference] | 1 [Reference] | 0.13 | 1 [Reference] | 1 [Reference] |
| ≥20 | 0.26 | 1.74 (1.59-1.89)d | 2.11 (1.90-2.33)d | 0.14 | 1.05 (0.94-1.18) | 0.96 (0.84-1.08) |
| Ratio of private to public insuranceg | ||||||
| ≥4.0 | 0.14 | 1 [Reference] | 1 [Reference] | 0.13 | 1 [Reference] | 1 [Reference] |
| 2.0-3.9 | 0.15 | 1.04 (0.93-1.18) | 1.07 (0.94-1.21) | 0.13 | 1.00 (0.94-1.05) | 0.94 (0.88-0.99)f |
| <2.0 | 0.23 | 1.65 (1.45-1.88)d | 2.29 (1.82-2.88)d | 0.14 | 1.01 (0.93-1.10) | 0.89 (0.80-0.99)f |
| No. of pharmacies per 10 000 personsh | ||||||
| Tertile 1 (<1.9) | 0.16 | 1 [Reference] | 1 [Reference] | 0.12 | 1 [Reference] | 1 [Reference] |
| Tertile 2 (≥1.9-2.4) | 0.17 | 1.11 (1.02-1.21)f | 0.89 (0.81-0.97)d | 0.14 | 1.17 (1.10-1.24)d | 1.14 (1.07-1.22)d |
| Tertile 3 (≥2.5) | 0.17 | 1.07 (0.99-1.16) | 0.35 (0.30-0.40)d | 0.15 | 1.28 (1.20-1.36)d | 1.16 (1.08-1.24)d |
Sample includes all pharmacies that were in operation at some point during 2009 through 2015 but excluding pharmacies newly opened in 2015. The 7-year study interval represented 454 371 pharmacy-years.
Urbanity is based on the National Center of Health Statistics’ Urban-Rural Classification Scheme for Counties. Counties containing a central city and located in a metropolitan statistical area of 1 million or more population were classified as urban. All other counties were considered nonurban.
The multivariate model is adjusted for all covariates listed in this table.
P < .05.
County characteristics derived from American Community Survey and Health Resources and Services Administration data and applied to individual pharmacies. Counties were designated as predominately minority if more than 50% of the population self-identified as nonwhite and designated as low income if 20% of the population had a household income below the federal poverty level. We used Health Resources and Services Administration data to identify counties that are designated by the federal government as medically underserved areas.
P < .01.
American Community Survey data was used to derive county-level information on insurance coverage. Payer mix was defined as a categorical variable based on the ratio of private insurance to public insurance (percentage of individuals with private vs public insurance alone) as less than 2.0, 2.0 to 3.9, and 4.0 or more. Uninsured rate was defined as binary variable (<20% or ≥20% of individuals are uninsured).
We obtained annual estimates from the US Census Bureau’s Population Estimates Program to derive information on total population for each county for each year. Pharmacy density was defined as the number of pharmacies per 10 000 persons based on the total number of active pharmacies and the total population in a specific county for the year prior to the closure.
Discussion
Despite the growing number of pharmacies in the United States, findings from this study indicate that 1 in 8 pharmacies had closed between 2009 and 2015, which disproportionately affected independent pharmacies and low-income neighborhoods. Although efforts to promote pharmacy access have focused on addressing pharmacy closures in rural areas,6 we found that pharmacies located in low-income, urban areas are at greater risk of closing. These findings suggest that policies aimed at reducing pharmacy closures should consider payment reforms, including increases in pharmacy reimbursement rates for Medicaid and Medicare prescriptions. The findings also suggest the importance of understanding the influence of preferred pharmacy networks in order to protect independent pharmacies most at risk for closure, especially in urban areas. Such efforts are important because pharmacy closures are associated with nonadherence to prescription medications, and declines in adherence are worse in patients using independent pharmacies that subsequently closed.1
References
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