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The American Journal of Managed Care October 2014
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Quality of Care at Retail Clinics for 3 Common Conditions
William H. Shrank, MD, MSHS; Alexis A. Krumme, MS; Angela Y. Tong, MS; Claire M. Spettell, PhD; Olga S. Matlin, PhD; Andrew Sussman, MD; Troyen A. Brennan, MD, JD; and Niteesh K. Choudhry, MD, PhD
Physician Compensation Strategies and Quality of Care for Medicare Beneficiaries
Bruce E. Landon, MD, MBA; A. James O'Malley, PhD; M. Richard McKellar, BA; James D. Reschovsky, PhD; and Jack Hadley, PhD
Increasing Access to Specialty Care: Patient Discharges From a Gastroenterology Clinic
Delphine S. Tuot, MDCM, MAS; Justin L. Sewell, MD, MPH; Lukejohn Day, MD; Kiren Leeds, BA; and Alice Hm Chen, MD, MPH
Increasing Preventive Health Services via Tailored Health Communications
Kathleen T. Durant, PhD; Jack Newsom, ScD; Elizabeth Rubin, MPA; Jan Berger, MD, MJ; and Glenn Pomerantz, MD
The Duration of Office Visits in the United States, 1993 to 2010
Meredith K. Shaw; Scott A. Davis, MA; Alan B. Fleischer, Jr, MD; and Steven R. Feldman, MD, PhD
Evaluation of Collaborative Therapy Review to Improve Care of Heart Failure Patients
Harleen Singh, PharmD; Jessina C. McGregor, PhD; Sarah J. Nigro, PharmD; Amy Higginson, BS; and Greg C. Larsen, MD
Extending the 5Cs: The Health Plan Tobacco Cessation Index
Victor Olaolu Kolade, MD
Caregiver Presence and Patient Completion of a Transitional Care Intervention
Gary Epstein-Lubow, MD; Rosa R. Baier, MPH; Kristen Butterfield, MPH; Rebekah Gardner, MD; Elizabeth Babalola, BA; Eric A. Coleman, MD, MPH; and Stefan Gravenstein, MD, MPH
Ninety-Day Readmission Risks, Rates, and Costs After Common Vascular Surgeries
Eleftherios S. Xenos, MD, PhD; Jessica A. Lyden, BSc; Ryan L. Korosec, MBA, CPA; and Daniel L. Davenport, PhD
Using Electronic Health Record Clinical Decision Support Is Associated With Improved Quality of Care
Rebecca G. Mishuris, MD, MS; Jeffrey A. Linder, MD, MPH; David W. Bates, MD, MSc; and Asaf Bitton, MD, MPH
The Impact of Pay-for-Performance on Quality of Care for Minority Patients
Arnold M. Epstein, MD, MA; Ashish K. Jha, MD, MPH; and E. John Orav, PhD
Healthcare Utilization and Diabetes Management Programs: Indiana 2006-2010
Tilicia L. Mayo-Gamble, MA, MPH; and Hsien-Chang Lin, PhD
Predictors of High-Risk Prescribing Among Elderly Medicare Advantage Beneficiaries
Alicia L. Cooper, MPH, PhD; David D. Dore, PharmD, PhD; Lewis E. Kazis, ScD; Vincent Mor, PhD; and Amal N. Trivedi, MD, MPH

Quality of Care at Retail Clinics for 3 Common Conditions

William H. Shrank, MD, MSHS; Alexis A. Krumme, MS; Angela Y. Tong, MS; Claire M. Spettell, PhD; Olga S. Matlin, PhD; Andrew Sussman, MD; Troyen A. Brennan, MD, JD; and Niteesh K. Choudhry, MD, PhD
Quality of care for 3 conditions, based on widely accepted objective measures, was superior in MinuteClinics compared with ambulatory care facilities or emergency departments.
Evaluation of quality of care across retail clinics in a geographically diverse population has not been undertaken to date. We sought to evaluate and compare the quality of care for otitis media, pharyngitis, and urinary tract infection received in retail medical clinics in CVS pharmacies (“MinuteClinics” [MCs]), ambulatory care facilities (ACFs), and emergency departments (EDs).

We used 14 measures constructed from RAND Corporation’s Quality Assurance Tools and guidelines from the American Academy of Pediatrics, the American Academy of Family Physicians, and the Infectious Diseases Society of America. Our cohort was drawn from Aetna medical and prescription claims, 2009-2012. Members were matched on visit date, condition, and propensity score. Generalized estimating equations were used to compare quality across clinic type, overall, and by index condition.

We matched 75,886 episodes of care, of which 20,153 were eligible for at least 1 quality measure. MCs performed better than EDs and ACFs in 7 measures. In a multivariable model, MCs performed better than ACFs and EDs across all quality measures ([OR 0.42; 95% CI, 0.40-0.45; P <.0001; ACF vs MC] [OR 0.29; 95% CI, 0.27-0.31; P <.0001; ED vs MC]). Results for each condition were significant at P <.0001.

Quality of care for these conditions based on widely accepted objective measures was superior in MinuteClinics compared with ACFs and EDs.

Am J Manag Care. 2014;20(10):794-801
  • These findings are consistent with previous studies demonstrating that quality of care is not compromised, and even appears superior, in retail clinics for specific acute conditions.
  • When taken together with evidence suggesting that retail clinics are more cost-effective and even cost saving to patients, these results underscore the potential of retail clinics for offering care of higher quality and lower cost at a time of primary care shortages.
  • More extensive studies exploring costs for chronic disease management and the role of retail clinics in improving care coordination and population health management are warranted.
Retail clinics have become increasingly prevalent in the United States. As of September 2014, there are about 1760 retail clinics,1,2 a number that by some estimates will grow to 2800, with 10.8 million annual visits made to them, by 2015.3 Retail clinics aim to treat a limited range of clinical conditions that are routine family medical problems, and thus can serve as an alternative to care in physicians’ offices, ambulatory/urgent care facilities (ACFs), or emergency departments (EDs).4 These clinics typically rely on nurse practitioners and physician assistants who deliver care based on strict adherence to clinical practice guidelines.

With increasing calls for healthcare delivery systems that can reduce the cost of care, offer more convenient primary care options to patients, and address primary care shortages, retail clinics may offer an attractive option.5,6 Recent studies suggest that retail clinics deliver care at substantially lower cost than ACFs and EDs, and have been associated with lower cost of care to the patient.7,8 Overall patient satisfaction is high, with walk-in care convenience and fixed, transparent pricing cited as 2 main attractions of the retail clinic model.4

At the same time, some have expressed concern that the retail clinic model of care may not provide care equivalent in quality to what is available in other settings.9,10 Professional physician organizations, such as the American Academy of Pediatrics (AAP) and the American Academy of Family Physicians (AAFP), have expressed ongoing concern about retail clinics, including questions about overall quality of care and the use of tests for the purpose of diagnosis without appropriate follow-up.10-12 Notwithstanding these concerns, evidence regarding quality of care for acute conditions in particular, which account for the majority of retail clinic services, has suggested that the quality of care is high. A study by Jacoby et al evaluating retail clinic performance on 2 Healthcare Effectiveness Data and Information Set (HEDIS) measures—the appropriate testing of children with strep throat and appropriate treatment of children with upper respiratory tract infection—concluded that retail clinics ranked above the 90th percentile for the former measure and between the 50th and 90th percentiles for the latter.13 A study by Rohrer et al evaluating return visits for children treated for ear infection found a lower rate of return visits within 2 weeks in retail clinics compared with standard office clinics,14 while a different analysis of retail clinics in Minnesota by Mehrotra et al examined 14 performance measures for care of 3 common conditions treated at retail clinics and found that the quality of care was superior to that received at ACFs and EDs.15 Nonetheless, evidence in this domain remains sparse. As the prevalence of these clinics grows, a contemporary evaluation of quality of care for acute conditions in a geographically diverse population is essential. We applied the performance measures for urinary tract infection (UTI), strep throat (pharyngitis), and ear infection (otitis media; OM) used in analysis of retail clinics in Minnesota by Mehrotra et al to a nationally representative cohort to compare the quality of care in retail clinics with that in ACFs and EDs.


This study was approved by the institutional review board of Partners Healthcare System, Boston, Massachusetts, and Harvard University, Cambridge, Massachusetts.

Study Population

We used nationwide medical and prescription claims from Aetna, a large healthcare benefits company, with dates of service from January 1, 2009, through December 31, 2012. The study population included commercial members with a visit to a MinuteClinic (the retail medical clinics in CVS pharmacies, with locations in 25 states and the District of Columbia during the study period), an ACF facility, or an ED for OM, pharyngitis, or UTI during this period. ACF visits were defined using Aetna’s definition of all visits to outpatient clinics including non-ED urgent care clinics, same-day surgeries, and same-day ambulatory hospital encounters. The analysis was restricted to the first episode of care for 1 of the 3 index conditions in the study period; if a member had episodes of care for more than 1 index condition, only the earliest episode and corresponding index condition were considered. Clinic type was identified using place of service codes, including specific codes for retail clinics, and conditions were identified using International Classification of Disease, Ninth Revision, Clinical Modification (ICD-9-CM) codes for OM (381, 382, 388.7), pharyngitis (034, 462, 463), and UTI (599, 595). Members were required to be continuously enrolled for the 6 months prior to and 60 days after their index episode.

Matching Episodes of Care

We matched members with MinuteClinic episodes of care to those from ACFs and EDs in a 1:1:1 fashion on the following criteria: month of index visit, index condition, and a propensity score. The propensity score was constructed from the following baseline characteristics: age, gender, tertile of household income (per zip code from 2000 US Census data), index condition, number of prescription medications and medical visits in the 6 months prior to the index visit, and Charlson Comorbidity Index score using ICD-9-CM codes from the 6 months prior to the index visit. Matching was operationalized using a validated SAS macro with a 0.05 caliper for the propensity score.16 We sampled without replacement, meaning an individual is a member of only 1 matched set.

Some zip codes in the 2000 US Census do not have income data available, and so members living in these zip codes were grouped into the second income tertile. A multiple imputation (N = 10) of these missing values was conducted as a sensitivity analysis.

Measuring Quality of Care

Quality of care was assessed using 14 measures constructed from RAND Corporation’s Quality Assurance (QA) Tools as well as guidelines from the AAP, the AAFP, and the Infectious Diseases Society of America, measures also employed in the analysis by Mehrotra et al of retail clinics in Minnesota (eAppendix Table 1 available at The RAND QA Tools were developed through comprehensive evaluation of research literature and clinical guidelines, and are considered a gold standard for measurement of whether patients are receiving evidence-based healthcare including appropriate diagnosis, treatment, and follow-up.17-23

Each measure is a binary marker of quality of clinical care (eg, throat culture or rapid strep test ordered on day of initial visit or day after in diagnosis of pharyngitis) and was oriented such that a higher score (ie, 1) indicates higher quality. There were 5 measures assessing quality of care for OM, and 6 and 3 measures for pharyngitis and UTI, respectively.

Statistical Analyses

We evaluated whether performance on each quality measure differed between visits to MinuteClinics and ACFs or EDs using χ2 tests. To compare overall quality across the 3 clinic types, we used a generalized estimating equation with a binomial distribution and a logit link. Because members were typically eligible for more than 1 quality measure and up to as many as 5 measures, this model accounted for correlation across member responses using an exchangeable covariance matrix. We included the quality measure in the model as a categorical variable to account for differing mean success rates across measures. We compared this analysis with a multivariable analysis that also adjusted for the following baseline characteristics: gender, age, income, number of medications, and number of medical visits in the 6 months prior to the visit.

We excluded quality measure 11 from all models, as did Mehrotra et al, because from a clinical perspective, the measure does not discriminate high versus low quality of care as distinctly as the other 13 measures. We used SAS, version 9.3 (SAS Institute, Cary, North Carolina) to conduct all analyses.


Study Population and Matched Cohort

We identified 1,231,866 eligible members with an index episode for 1 of the 3 conditions occurring at 1 of the clinic types during the 3-year study period (Table 1). The majority of episodes (91%) were ACF visits, with 6% and 2% occurring at EDs and MinuteClinics, respectively. The majority of cases seen in MinuteClinics were for pharyngitis (61% vs 51% and 37% in ACFs and EDs, respectively), whereas the majority of cases seen in EDs were for UTI (40% vs 19.3% and 9.4% for ACFs and MinuteClinics, respectively).

Members seen in MinuteClinics tended to have lower Charlson Comorbidity Index scores and fewer physician visits in the 6 months prior to index. Children under 5 years of age comprised 3.4% of cases seen at MinuteClinics, compared with 10.6% and 13.7% in EDs and ACFs, respectively. Members seen in EDs generally lived in lower- income zip codes, followed by ACFs (second lowest) and MinuteClinics (highest).

After matching on propensity score, index condition, and index month, matches were found for 25,334 members (87% of eligible MinuteClinic episodes). The matched cohort was predominantly female (61%) and the majority (54%) were aged between 18 and 44 years. Most episodes were for pharyngitis (58%), while three-fourths of members had had at least 1 doctor’s visit in the 6 months prior (74%), and about half had 1 to 5 unique medication fills in the 6 months prior (51%).

Quality of Care

There were 20,153 members from the matched cohort who were eligible for at least 1 quality measure; the number for which they were eligible ranged from 1 to 5. MinuteClinics had higher success rates than both EDs and ACFs in 7 of 14 measures (Table 2). Differences in success rates across sites of care were statistically significant (P = .05) in 10 measures, including all pharyngitis and UTI measures and 1 OM measure. Pooled, unadjusted success rates by index condition are presented in the Figure.

MinuteClinics performed better than ACFs and EDs across all quality measures ([OR 0.43; 95% CI, 0.40-0.45, comparing ACFs with MinuteClinics; OR 0.29; 95% CI, 0.27-0.31 comparing EDs with MinuteClinics]) with both results significant at P <.0001 (Table 3). Results were very similar after adjustment for baseline covariates ([OR 0.42; 95% CI, 0.40-0.45, comparing ACFs with MinuteClinics; OR 0.29; 95% CI, 0.27-0.31, comparing EDs with MinuteClinics]).

Results stratified by each of the conditions individually were also similar. The difference in quality between MinuteClinics and other clinic types was most pronounced for UTI ([OR 0.31; 95% CI, 0.27-0.35, comparing ACFs with MinuteClinics; OR 0.28; 95% CI, 0.25-0.32, comparing EDs with MinuteClinics]), and least pronounced for OM ([OR 0.82; 95% CI, 0.75-0.89, comparing ACFs with MinuteClinics; OR 0.73; 95% CI, 0.67-0.80, comparing EDs with MinuteClinics]). Results across each index condition remained statistically significant at P <.0001.

Sensitivity Analysis

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