Characteristics of Persons Using Convenience Clinics for Usual Care in 2022

Abstract

Little is known about the characteristics of individuals using urgent care centers or walk-in retail clinics, collectively called convenience clinics (CC), as places of usual care. Using 2022 National Health Interview Survey data and logistic regression, we identified the factors associated with adults using CCs regularly. Among adults with a place of usual care, 7.5% reported receiving usual care at CCs. Individuals who were younger, working, and uninsured were significantly more likely to report CCs as their usual source of care. Understanding the characteristics of CC users is critical to inform policy for this evolving segment of the health care sector.

BACKGROUND

Convenience clinics (CCs), which we define as both urgent care centers (“urgent care”) that may exist in stand-alone ambulatory medical facilities and walk-in retail health clinics (“retail clinics”) that may be found within existing establishments, such as pharmacies or general merchandise big-box stores or as stand-alone operations, are a class of alternative care options typically designed to treat acute conditions and time-limited health needs typically located in suburban and urban areas (Coster et al., 2017; RAND, 2016; Weinick et al., 2010). CCs are part of a growing sector of alternative care sites for primary care provider office visits (Hildago, 2016; Marso, 2021; Wang et al., 2010). The accessibility of CCs may be an advantage to care provided in primary care provider offices, as many primary care providers have long wait times for appointments (Family Practice Management, 2022). Both urgent care and retail clinics can operate without appointments and maintain walk-in hours during weekdays, evenings, and weekends, offering an alternative to primary care office visits and often less expensive care relative to the emergency department and, in many cases, a primary care setting (Mehrotra et al., 2009; Wang et al., 2010). The staffing models and types of services offered differentiate retail clinics from urgent care centers, as urgent care centers can provide more comprehensive low-acuity to mid-acuity care with an on-staff physician, onsite X-rays, and laboratory testing, and retail clinics provide low-acuity services and treat a limited range of conditions (Urgent Care Association, 2023; Weinick et al., 2010). While CCs may employ a workforce similar to primary care provider offices, the financial incentives for preventive care differ between these settings and may result in different approaches to care. CCs are designed to address acute needs, and providers may not be aware of other services patients require due to limited interoperability of electronic medical records. While CCs may provide some primary care services that are offered in primary care office settings, without linkage to a health system, they may not provide for the continuity of care that supports delivery of comprehensive primary care.

Previous studies have examined utilization patterns among CCs. Patients use CCs because of the accessibility and expediency these facilities offer, the unavailability of primary care, perceived medical needs, and fixed, transparent pricing (Coster et al., 2017; RAND, 2016; Wang et al., 2010). CCs are preferred places for care among millennials, a generation that also reports lower rates of having a regular primary care provider than previous generations (Hildago, 2016). For populations without a primary care provider, as well as those seeking expedited care, CCs are increasingly seen as a source of routine primary care (Marso, 2021). Allen et al. (2021) found that urgent care centers treat patients who would otherwise visit the emergency department for non-emergent conditions, including those with Medicaid and the uninsured. Poon et al. (2018) reported an increase in visits to urgent care and retail clinics from 2008 to 2015 among commercially insured individuals, and patients using these care sites were more likely to be female, in better health; overall, patients were more likely to visit urgent care than emergency departments for low-acuity conditions. Ashwood et al. (2011) reported that among the commercially insured, women, young adults, those without chronic conditions, and high-income individuals living in close proximity to retail clinics were more likely to use retail clinic services.

Although these studies provide important insights into the demand for CCs, they are primarily based on the experience of commercially insured individuals and exclude those who are uninsured. CCs may be of particular value to uninsured individuals as they are more likely to be price-sensitive and attracted to the typically lower and transparent pricing offered through CCs (Aron-Dine et al., 2014). Recent research using the 2019 National Health Interview Survey (NHIS) data found that both women (32%) and men (26%) had 1 or more visits to an urgent care center or retail health clinics in the past 12 months; non-Hispanic white adults were more likely to have 1 or more visits; and as age increased, utilization decreased (Black and Adjaye-Gbewonyo, 2021). This study combined both regular and intermittent users of CCs but did not specifically examine those who reported these settings as a usual source of care.

Understanding the characteristics of patient populations using CCs as a usual source of care is important as the sector continues to grow. From 2008 to 2015, growth increased in the urgent care and retail clinic sectors (Poon et al., 2018). In 2020, urgent care saw a 58% increase in visit volumes due to the demand for COVID-19-related episodic care, and 60% of the total visits were for vaccinations and testing (Siwicki, 2021). Retail clinics were part of the federal government’s COVID-19 vaccination strategy, and people became more comfortable receiving vaccination and testing at these sites (Lagasse, 2023). Prior to the pandemic, CCs explored telehealth options, such as telemedicine kiosks adjacent to pharmacies in retail stores and virtual consults with a primary care clinician if the CC practitioner deemed it necessary (Fong, 2016; Hennessy, 2016). Despite some growth in the CC sector offering virtual visits, visits to brick-and-mortar sites continued during the pandemic, as people visited CCs for testing and to receive COVID-19 vaccination. While trends in telehealth grew exponentially during the pandemic with more flexible regulations and reimbursements for remote health care services, telehealth use at the end of the pandemic is declining, while CC utilization continued to increase (FAIR Health, 2023). Between 2017 and 2022, there was a 200% increase in retail clinic volume and a 70% increase in urgent care (Lagasse, 2023; Witowski, 2023). However, patient factors associated with the regular use of CCs for care in the post-pandemic health care environment remain largely unknown.

Having a usual source of primary care allows for an ongoing patient-provider relationship and leads to improved health outcomes including higher rates of preventive care, more equitable care, and lower costs (Blewett et al., 2008; Huffstetler et al., 2023; Jabbarpour et al., 2022). A recent 2022 report notes trends in usual care may be influenced by the increased popularity of CCs, as these settings provide some primary care services and may substitute as a usual source of care for some people (Jabbarpour et al., 2022). Health systems and insurers continue to acquire, invest in, and partner with CCs as part of a broader strategy to expand access to services (Baumgarten Hempstead, 2023). As the CC sector continues to grow with investments by insurers and health systems, these stakeholders may further want to understand the characteristics of patients using CCs regularly. Identifying the characteristics of regular CC users allows stakeholders to tailor interventions to groups frequenting CCs for care, as well as outreach to populations that do not utilize these services. Stakeholders have noted the importance of building a connection between alternative sites of care, such as CCs, and the broader health system. Understanding patient factors associated with the use of CCs for usual care can inform business plans, strategic decision making, and outreach to connect patients back to the health system. Moreover, if people use CCs as their usual source of care, they may forgo care in other settings, such as primary care, which may have consequences for their overall health. While there is some evidence describing aspects of the CC market among individuals receiving acute care services (Ashwood et al., 2011; Black and Adjaye-Gbewonyo, 2021; Poon et al., 2018), there is very little evidence about the characteristics of patients using these services as a principal source of care. We address this research gap by identifying individual-level demographic, financial, and utilization factors associated with people choosing to regularly use CCs when in need of health care.

METHODS

Conceptual model

Our analysis of the factors associated with CC use is guided by Andersen’s behavioral model of health service use, which identifies the predisposing, enabling, and need factors associated with demand for health care. Originally proposed in 1968, the model was expanded in 1973 (Andersen and Newman model; Andersen, 1995) to include societal and individual determinants of medical care utilization, emphasizing the characteristics of the health service delivery system, changes in social norms and technology, and individual determinants of utilization (Andersen Newman, 1973). Another component of the model proposed by Andersen and Newman in 1995 emphasized the dynamic and recurring nature of health service use (Andersen, 1995). Our conceptual model adopts this fourth version to identify the dynamic and reoccurring enabling, predisposing, and need factors that may be associated with individual’s use of CCs. Predisposing factors include demographics and social factors; enabling factors include income and health insurance; and need factors include perceived need and one’s viewpoint of one’s health status, all of which contribute to health service use in CCs (Bradley et al., 2002).

Data sources

Our analysis used data from the 2022 NHIS, which uses a multistage probability sample to identify a nationally representative set of households in the United States to assess a wide range of health outcomes and patterns of health care use for the non-institutionalized US population. The NHIS has been operating continuously since 1957 with periodic updates to the survey instrument. The final adult response rate for 2022 is 47.7%. The 2022 Sample Adult Questionnaire survey includes one “sample adult” age 18 years or older from each household and was administered to 27 561 adults randomly selected from identified households of the NHIS. The NHIS provides sample weights that allow the findings to reflect the entire US adult population (National Center for Health Statistics, 2022).

Study sample

We restricted the sample of NHIS respondents to those aged 18 years and older who answered yes to the following question: “Is there a place that you USUALLY go to if you are sick and need health care?” (National Center for Health Statistics, 2022). Following previously published methods, those who reported that they had a usual place where they went when they were sick and in need of care were classified as having the usual source of care (Blewett et al., 2008; Brown et al., 2014; Simon et al., 2015). We excluded people reporting having no place or more than 1 place for usual care. There were 6 respondents with missing observations for the variable capturing type of place of usual care that was excluded from the analysis. For all other variables, responses of refused, not ascertained, or unknown were categorized together and coded as “unknown.” One limitation of the NHIS is that the survey combined retail clinics and urgent care centers as a single response category. Thus, our analysis refers to these facilities jointly as CCs.

Outcome variable

Among those who reported having a place they usually go to if they were sick and in need of care, our dependent variable was derived from the NHIS question: “What kind of place [do you go]… a doctor’s office or health center; an urgent care center, a clinic in a drug store or grocery store; a hospital emergency room; a Veterans Affairs (VA) Medical Center or VA outpatient clinic; or some other place?” Urgent care and retail clinics were defined as: “Urgent care centers and clinics in a drug store or grocery store are places where you do not need to make an appointment ahead of time, and do not usually see the same health care provider at each visit” (National Center for Health Statistics, 2022). The outcome variable was a binary indicator of the type of place of usual care, either those reporting CCs as a usual source of care or other settings including doctor’s office/health center, hospital emergency room, VA Medical Center or VA outpatient clinic, some other place, or does not go to one place most often.

Explanatory variables

We chose the following demographic, financial, health insurance status, health status, and health care utilization variables, guided by the Andersen-Newman model:

Predisposing

Predisposing variables included age (categorical: 18–29, 30–39, 40–49, 50–59, and 60 + years), gender (male/female), race (White Only, Black/African American Only, Asian Only, American Indian/Alaska Native Only (AIAN) or AIAN and any other group, Other Single or Multiple Races), ethnicity (Hispanic/Latino), education level (less than high school, General Educational Development (GED)/high school graduation, some college, Associate degree, Bachelor’s degree, and Master’s/Professional/Doctoral degree), and census region of residence (Northeast, Midwest, and South, West), and Urban-Rural County (Large Central Metro, Large Fringe Metro, Medium and Small Metro, and Nonmetropolitan). The race and Hispanic identity variables were reported using the US Census Bureau categories, and adults categorized as Hispanic may self-identify as any race, including multiracial.

Enabling

Enabling variables included health insurance status (uninsured, private, Medicaid/other public/Duel Eligible), other commercial, Medicare, or Medicare Advantage) worked for pay last week at a job or business (yes/no), residence/housing type (owned, rented, other), and poverty ratio (ratio of the family’s income to the federal poverty threshold).

Need

Number of comorbidities including any of the following: hypertension in last 12 months, high cholesterol in last 12 months, overweight/obese currently (based on BMI), asthma currently, ever had type 2 diabetes, ever had depression, ever had arthritis, ever had cancer, ever had chronic obstructive pulmonary disease, ever had coronary heart disease (0 or 1, 2, 3+).

The University of Washington Human Subjects Division determined that this research was exempt from Institutional Review Board review (University of Washington Human Subjects Division, 2024).

Statistical analysis

We generated descriptive statistics based on whether individuals used CCs as their usual source of care. We ran t-tests and Pearson’s chi-square tests for independence to test for statistically significant differences between the continuous and categorical variables. We then estimated a logistic regression model to obtain the odds ratio of reporting CCs for usual care compared to other places of usual care, controlling for the explanatory variables listed earlier. We then estimated the average marginal effects for ease of interpretation (Norton et al., 2024). To account for appropriate variance estimation, we identified the survey design characteristics specified by the NHIS, including appropriate variance structures and population-level weights, and used Stata’s estimation commands to calculate weighted descriptive statistics and conduct weighted regression analyses. Stata’s survey commands automatically incorporate robust variance estimators. All statistical tests were conducted at a 2-sided 5% significance level using the Stata software (version 15) to account for the complex survey design.

RESULTS

Descriptive results

In 2022, 24 395 (unweighted) adults aged 18 years and older in the United States reported having a place they usually visit when they are sick and in need of care. Of those, 7.5% (weighted) went to CCs for care, while 92.5% went to other places for care, including doctors’ offices or health centers, hospital emergency rooms, VA medical centers, VA outpatient clinics, or some other place. In 2022, 51.43% of CC users were male compared to 46.41% people with other places for usual care (P = .01). CC users comprised 71.86% White Only, 13.58% Black or African American Only, 4.07% Asian Only, 2.11% AIAN Only or AIAN and any other group, and 1.47% Other Single or Multiple Races; 6.91% of the respondents’ races were unknown (P = .06). Compared to people who used other types of usual care, more CC users had private insurance (63.50% vs 61.51%), were Medicaid/Duel Eligible (15.06% vs 13.86%), were uninsured (13.94% vs 6.03%), and fewer had Medicare/Medicare Advantage (4.47% vs 12.02%) (P < .01). Compared to people who used other sources of usual care, more CC users reported having recently worked for pay (73.36% vs 58.61%) (P < .01), while fewer reported owning homes (60.81% vs 69.68%) (P < .01). CC users and non-users visited the emergency department in the last 12 months at similar rates (14.18% vs 13.32% visited 1 time, and 5.55% vs 7.21% visited 2 or more times in the last year) (P = .16). Among people who used CCs for usual care, 37.72% reported not going to a CC in the last 12 months, 30.42% reported using a CC 1 time in the last 12 months, 16.19% reported 2 times, and 15.60% reported 3 or more times. Among people reporting other settings as place of usual care, 69.17% reported not going to a CC in the last 12 months, 16.39% reported going 1 time, 7.93% reported 2 times, and 6.25% reported 3 or more times (P < .01). More CC users than non-users reported having 0 or 1 comorbidity (64.02% vs 48.64%), while fewer CC users reported having 3 or more comorbidities (15.11% vs 30.47%) (P < .01; Table 1).

Table 1.

Demographics by Place of Usual Care

	Other Place of Usual Care (n = 22 814)	Convenience Clinic (n = 1581)	P-value
Age, %			<.01
18–29 y	16.90	29.25
30–39 y	15.07	26.14
40–49 y	15.86	16.07
50–59 y	17.14	14.15
60+ y	34.80	14.39
Unknown	.18	.00
Gender, %			.01
Male	46.41	51.43
Race, %			.06
White Only	72.25	71.86
Black or African American Only	12.22	13.58
Asian Only	6.35	4.07
AIAN Only or AIAN and any other group	1.86	2.11
Other Single or Multiple Races	1.36	1.47
Unknown	5.94	6.91
Ethnicity, %			.03
Hispanic	15.78	18.49
Region, %			.44
Northeast	18.41	18.05
Midwest	20.95	21.42
South	36.99	39.20
West	23.65	21.33
Urban-rural county, %			.09
Large Central Metro	29.80	31.76
Large Fringe Metro	25.40	26.39
Medium and Small Metro	30.13	30.46
Nonmetropolitan	14.67	11.40
Education, %			.04
No High School Diploma	10.27	10.67
GED or High School Graduation	26.42	27.78
Some College	16.16	17.74
Associates Degree	13.52	13.05
Bachelor’s Degree	19.93	20.57
Masters/Professional/Doctoral Degree	13.12	9.78
Unknown	.58	.41
Employment, %			<.01
Worked last week	58.61	73.36
No	37.58	23.10
Unknown	3.81	3.54
Poverty ratio (mean)	4.35	4.10	.01
Insurance type, %			<.01
Private insurance	61.51	63.50
Medicaid or dual eligible	13.86	15.06
Other commercial	6.26	2.51
Uninsured	6.03	13.94
Medicare/Medicare advantage	12.02	4.47
Unknown	.31	.51
Residence type, %			<.01
Owned or being bought	69.68	60.81
Rented	24.14	32.78
Other arrangement	1.91	1.86
Unknown	4.27	4.54
Health care utilization, %
Emergency department visits in last 12 mo			.16
0 times	79.35	80.17
1 time	13.32	14.18
2+ times	7.21	5.55
Unknown	.11	.09
Convenience clinic visits in last 12 mo			<.01
0 times	69.17	37.72
1 time	16.39	30.42
2 times	7.93	16.19
3+ times	6.25	15.60
Unknown	.07	.25
Number of comorbidities, %			<.01
0 or 1	48.64	64.02
2	20.88	20.87
3+	30.47	15.11
Self-reported health status, %			<.01
Excellent	54.53	62.98
Good/Fair	41.77	35.34
Poor	3.69	1.68
Unknown	.01	.00

Abbreviations: AIAN, American Indian/Alaska Native; GED, General Educational Development.

Regression results

Predisposing factors

Compared with people ages 18 to 29 years, the odds of using CCs were 35% lower for people ages 40 to 49 years (P < .01), 42% lower for people ages 50 to 59 years (P < .001), and 62% lower for people aged ≥60 years (P < .01), holding all other factors constant. Older age is associated with a 3, 4, and 6 percentage point decrease in the probability of CC use for usual care among those 40 to 49 years, 50 to 59 years, and 60+ years, respectively (P < .01). The odds of using CCs for usual care were 20% higher for men than for women (P = .01), holding all other variables constant. Men are, on average, 1 percentage point more likely to use CCs as a place of usual care (P = .01). The odds of reporting CCs as a place of usual carewere45% lower among people who reported race as Asian Only compared to people who identified as White Only (P < .01), holding all else constant. There were no significant differences in the use of CCs among the other race categories. Compared to people who reported race as White Only, people who reported race as Asian Only have a 3 percentage point lower probability of using CCs for usual care (P ≤ .01; Table 2).

Table 2.

Association between Patient Characteristics and Odds of Using Convenience Clinic As Usual Source of Care: Logistic Regression Results

	OR	P-value	95% CI		Average Marginal Effect (dy/dx)	P-value	95% CI
Age, y
30–39	1.09	.34	.91	1.30	.01	.34	−.01	.02
40–49	.65	<.01	.53	.80	−.03	<.01	−.05	−.02
50–59	.58	<.01	.47	.72	−.04	<.01	−.06	−.02
60+	.38	<.01	.30	.48	−.06	<.01	−.08	−.05
18–29	REF
Gender  Male	1.20	.01	1.05	1.36	.01	.01	.00	.02
Female	REF
Race
Black or African American Only	.87	.20	.71	1.08	−.01	.18	−.02	<.01
Asian Only	.55	<.01	.40	.75	−.03	<.01	−.05	−.02
AIAN Only or AIAN and any other group	.98	.95	.60	1.62	.00	.95	−.04	.03
Other Single or Multiple Races	.76	.30	.45	1.28	−.02	.25	−.05	.01
Unknown	.88	.45	.63	1.23	−.01	.43	−.03	.01
White Only	REF
Ethnicity  Hispanic	.82	.10	.65	1.04	−.01	.08	−.03	<.01
Non-Hispanic	REF
Region  Midwest	1.03	.78	.82	1.30	.00	.78	−.01	.02
South	1.08	.48	.88	1.32	.01	.48	−.01	.02
West	.92	.46	.72	1.16	−.01	.46	−.02	.01
Northeast	REF
Urban-rural county  Large Fringe Metro	1.00	.97	.82	1.20	.00	.97	−.01	.01
Medium and Small Metropolitan	.94	.56	.76	1.16	.00	.56	−.02	.01
Nonmetropolitan	.70	.01	.53	.93	−.02	.01	−.04	−.01
Large Central Metro	REF
Education  GED or High School Diploma	.91	.43	.71	1.16	−.01	.44	−.03	.01
Some College	.92	.54	.70	1.20	−.01	.55	−.03	.01
Associates Degree	.87	.34	.65	1.16	−.01	.35	−.03	.01
Bachelor’s Degree	.84	.21	.65	1.10	−.01	.23	−.03	.01
Masters/Professional/Doctoral Degree	.71	.03	.52	.96	−.02	.03	−.04	<.01
Unknown	.71	.48	.28	1.81	−.02	.42	−.08	.03
No High School Graduation	REF
Employment  No	.80	.01	.68	.94	−.02	.01	−.03	<.01
Unknown	.37	<.01	.19	.70	−.05	<.01	−.07	−.03
Worked last week	REF
Poverty ratio	.98	.16	.95	1.01	.00	.16	.00	.00
Insurance type  Medicaid or dual eligible	1.01	.91	.83	1.24	.00	.91	−.01	.01
Other commercial	.53	<.01	.37	.77	−.03	<.01	−.05	−.02
Uninsured	1.80	<.01	1.45	2.24	.05	<.01	.03	.07
Medicare/Medicare advantage	.87	.29	.66	1.13	−.01	.27	−.02	.01
Unknown	1.51	.42	.55	4.12	.03	.49	−.06	.12
Private insurance	REF
Residence type  Rented	1.15	.07	.99	1.35	.01	.07	.00	.02
Other arrangement	.96	.87	.60	1.53	.00	.87	−.03	.03
Unknown	2.26	.01	1.22	4.19	.07	.04	.00	.14
Owned or being bought	REF
ED visits in last 12 mo  1 time	1.08	.42	.90	1.30	.01	.43	−.01	.02
2+ times	.81	.16	.60	1.09	−.01	.14	−.03	<.01
Unknown	.74	.72	.15	3.72	−.02	.68	−.10	.07
0 times	REF
Number of comorbidities  3+	.65	<.01	.54	.78	−.03	<.01	−.04	−.02
2	.94	.45	.80	1.10	.00	.44	−.02	.01
0 or 1	REF

Abbreviations: AIAN, American Indian/Alaska Native; CI, confidence interval; ED, emergency department; GED, General Educational Development; OR, odds ratio; REF, reference group.

Enabling factors

Holding all other factors constant, the odds of using CCs were 20% lower for people who reported not working compared to those reported working for pay last week (P = .01). Compared to people who worked for pay last week, people who did not work had a 2 percentage point lower probability of using CCs for usual care (P = .01). The odds of using CCs were 80% higher among those who are uninsured compared to those with private insurance (P < .01). Compared to people with private insurance, those without health insurance have a 5 percentage point higher probability of using CCs for usual care (P < .01) Compared to people who reside in large central metro counties, the odds of using CCs for usual care were 30% lower for people residing in nonmetropolitan counties. Compared to people who reside in large central metro counties, people who reside in nonmetropolitan counties had a 2 percentage point lower probability of using CCs for usual care (P = .01; Table 2).

Need factors

Holding all other factors constant, compared to people with no comorbidities, the odds of using CCs were 35% lower for people with 3 or more comorbidities than for those with 0 or 1 comorbidity (P < .01). Compared to people with 0 or 1 comorbidity, people with 3+ comorbidities had a 3 percentage point lower probability of using CCs for usual care (P < .01; Table 2).

DISCUSSION

In this analysis, we found several individual characteristics, including demographic, financial, and health status, as key predictors of people using CCs for usual care. Many of Andersen-Newman’s predisposing and enabling factors were significantly associated with CC use, including individuals’ age and gender (predisposing factors), insurance type, employment status (enabling factors), and health status (need factors) (Andersen, 1995). The odds of using CCs for usual care were significantly lower among older individuals, people not working, and people living in nonmetropolitan areas, as well as people with more comorbidities, whereas the odds of use were higher for men and those with uninsured status. Our findings describe the characteristics of regular users of CCs, inform strategies for providers investing in the CC sector, and highlight the need to ensure that health care services are accessible.

Previous research has reported that retail clinics appeal to younger, healthier, and higher-income patients who live close to the clinics they use, suggesting that CCs satisfy the strong demand for convenience (Ashwood et al., 2011; Black and Adjaye-Gbewonyo, 2021; Poon et al., 2018). Our findings support these previous studies and add insights that suggest CCs may be an important place for usual care among a younger and healthier population, those working, men, and the uninsured living in metropolitan areas. Employees may seek the after-hours and scheduling flexibility that CCs provide to accommodate inflexible work schedules. Similar to a study using NHIS 2019 data that looked at the number of visits to CCs, we found regular users of CCs were more likely to be younger adults (Black Adjaye-Gbewonyo, 2021), however, we did not find significant differences between those who usually use CCs and other settings by ethnicity in 2022. It is possible that the population using CCs as a usual source of care is different from the population that may occasionally visit a CC and seek usual care elsewhere. We also found that the odds of CC use for usual care were higher among people who reported being uninsured, an important insight as previous studies examining CCs have focused primarily on the service use experience of commercially insured populations (Ashwood et al., 2011; Reid et al., 2012; Shrank et al., 2014). CCs may provide an important source of regular care for the uninsured, possibly due to the transparent pricing and low-cost business model that may appeal to a price-sensitive population (Aron-Dine et al., 2014).

Implications for policy and practice

Understanding the factors that explain why individuals choose to receive usual care at a CC is necessary to inform how public and private decision makers can best meet the overall demand for care. For example, we found that men were more likely than women to use CCs for regular care and, therefore, less likely to go to a doctor’s office or other settings—an important population that may need greater outreach to be reconnected back into a health system’s primary care network. By identifying the characteristics of CC patient populations and leveraging this information, outreach strategies can be tailored to groups that may both overutilize and underutilize these services. People who are younger, healthier, working, and uninsured tend to use CCs regularly. Same-day appointments, short wait times, and price transparency may attract populations constrained by work hours, high health care costs, and convenience. Health systems may need to respond to consumer demands by offering greater scheduling flexibility and availability to accommodate the needs of this population. In addition, there may be a need for greater connection between CCs and health systems, and greater incentives to ensure that care is streamlined. In many cases, the integration of care and referrals between urgent care and retail clinics with other health services remains limited, and more work is needed to ensure that CCs can be used as an extension of the health system rather than a stand-alone entity (Villasenor Krouse, 2016). Furthermore, while previous studies have found that CCs provide high-quality care and patient satisfaction (Palms et al., 2018; Woodburn et al., 2007), greater monitoring of the sector is needed to ensure optimal health outcomes over time, especially among those who report CCs as their usual source of care.

Limitations

We cannot distinguish between and among individuals who use urgent care versus retail clinics as their usual place of care. Although our study still provides an important glimpse into the factors associated with CC use, further research is needed to understand the differences in this growth between the urgent care and retail clinic markets, as the 2 market segments may behave differently. We were also unable to determine whether CCs are affiliated with larger health care systems, as this may impact the continuity of care and the care quality that individuals receive. We did not examine the factors associated with the intensity of CC use, though this may be an important area of research in the future as stakeholders may be interested in understanding overall demand. Finally, our analysis is based entirely on the experiences of adults, and there remains a gap in our understanding of the degree to which children receive care through CCs and, if so, the implications for their health outcomes (Laughlin et al., 2014).

CONCLUSION

CCs represent retailers’ and health systems’ attempts to meet the demand for health care, which is often not satisfied through traditional means. This study provides insights into who uses CCs for usual care including people who are younger, without health insurance and working, groups that may need further linkage to health systems and primary care. Our research fills a gap in the extant literature regarding the characteristics of regular users of CCs, but more research is needed to ensure that we better understand the role of these facilities in addressing current and future health care demands.