This cohort study of patients with acne evaluates the association of patients’ race/ethnicity and sex with health care use and specific treatments for acne.
Key Points
Question
Are race/ethnicity and sex associated with differences in health care use and prescribing patterns among patients with acne?
Findings
In this cohort study of 29 928 patients with acne, compared with non-Hispanic white patients, non-Hispanic black patients were more likely to be prescribed topical retinoids or topical antibiotics and less likely to receive prescriptions for oral antibiotics, spironolactone, and isotretinoin. Male patients were more likely to be prescribed isotretinoin than female patients; patients with Medicaid were less likely to receive prescriptions for topical retinoids and systemic therapies.
Meaning
The findings suggest that there may be racial/ethnic, sex, and insurance-based disparities in health care use and treatment for acne.
Abstract
Importance
Our understanding of potential racial/ethnic, sex, and other differences in health care use and treatment for acne is limited.
Objective
To identify potential disparities in acne care by evaluating factors associated with health care use and specific treatments for acne.
Design, Setting, and Participants
This retrospective cohort study used the Optum deidentified electronic health record data set to identify patients treated for acne from January 1, 2007, to June 30, 2017. Patients had at least 1 International Classification of Diseases, Ninth Revision (ICD-9) or International Statistical Classification of Diseases and Related Health Problems, Tenth Revision (ICD-10) code for acne and at least 1 year of continuous enrollment after the first diagnosis of acne. Data analysis was performed from September 1, 2019, to November 20, 2019.
Main Outcomes and Measures
Multivariable regression was used to quantify associations between basic patient demographic and socioeconomic characteristics and the outcomes of health care use and treatment for acne during 1 year of follow-up.
Results
A total of 29 928 patients (median [interquartile range] age, 20.2 [15.4-34.9] years; 19 127 [63.9%] female; 20 310 [67.9%] white) met the inclusion criteria for the study. Compared with non-Hispanic white patients, non-Hispanic black patients were more likely to be seen by a dermatologist (odds ratio [OR], 1.20; 95% CI, 1.09-1.31) but received fewer prescriptions for acne medications (incidence rate ratio, 0.89; 95% CI, 0.84-0.95). Of the acne treatment options, non-Hispanic black patients were more likely to receive prescriptions for topical retinoids (OR, 1.25; 95% CI, 1.14-1.38) and topical antibiotics (OR, 1.35; 95% CI, 1.21-1.52) and less likely to receive prescriptions for oral antibiotics (OR, 0.80; 95% CI, 0.72-0.87), spironolactone (OR, 0.68; 95% CI, 0.49-0.94), and isotretinoin (OR, 0.39; 95% CI, 0.23-0.65) than non-Hispanic white patients. Male patients were more likely to be prescribed isotretinoin than female patients (OR, 2.44; 95% CI, 2.01-2.95). Compared with patients with commercial insurance, those with Medicaid were less likely to see a dermatologist (OR, 0.46; 95% CI, 0.41-0.52) or to be prescribed topical retinoids (OR, 0.82; 95% CI, 0.73-0.92), oral antibiotics (OR, 0.87; 95% CI, 0.79-0.97), spironolactone (OR, 0.50; 95% CI, 0.31-0.80), and isotretinoin (OR, 0.43; 95% CI, 0.25-0.75).
Conclusions and Relevance
The findings identify racial/ethnic, sex, and insurance-based differences in health care use and prescribing patterns for acne that are independent of other sociodemographic factors and suggest potential disparities in acne care. In particular, the study found underuse of systemic therapies among racial/ethnic minorities and isotretinoin among female patients with acne. Further study is needed to confirm and understand the reasons for these differences.
Introduction
Acne is common across all races/ethnicities and both sexes and is responsible for a substantial burden of disease, including the development of depression.1,2,3,4,5,6,7 Prior work8,9,10 has suggested that racial/ethnic disparities in health care use exist for a variety of dermatologic diseases, including atopic dermatitis and psoriasis. However, our understanding of the associations of race/ethnicity, sex, and other factors with health care use and treatment for acne remains limited.
Prior studies11,12,13 using the National Ambulatory Medical Care Survey (NAMCS) data identified that Medicaid insurance, black race, Asian race, Hispanic/Latino ethnicity, and male sex were each associated with a lower likelihood of receiving care from a dermatologist than a nondermatologist for acne.11 Black patients with acne were less likely than white patients to receive any prescription for acne or isotretinoin.12,13 In addition, female patients were observed to be less likely to receive isotretinoin despite having more visits for acne than men.12 Smaller studies14,15 among other populations have also suggested associations between race/ethnicity and socioeconomic status and isotretinoin treatment and between Hispanic ethnicity and health care use for acne.
Much of the existing literature remains limited by its focus on specific acne treatments (namely isotretinoin) or lack of patient-level data. As a result, there is a knowledge gap regarding the associations between patients’ sociodemographic characteristics and prescribing patterns across a broad range of topical and systemic treatments for acne. Thus, the purpose of this study was to identify potential disparities in acne care by evaluating the associations between health care use and prescribing patterns for acne and patient-level factors, such as race/ethnicity, sex, and other sociodemographic factors, among a US cohort of patients.
Methods
Study Design and Data Source
We performed a retrospective cohort study using the Optum deidentified electronic health record data set from January 1, 2007, to June 30, 2017. Our study used a 10% random sample of the complete database that was available to the investigators and includes data for 8.2 million patients. Optum’s longitudinal electronic health record repository is derived from dozens of health care organizations in the United States that include more than 700 hospitals and 7000 clinics.16,17,18 Approximately 83% of individuals included in this data set are cared for by integrated delivery networks, meaning that most of a person’s health care encounters are likely to occur within this network and will be captured in the database.17 The data captured in the database include demographics, medications prescribed and administered, and coded diagnoses and procedures. Data analysis was performed from September 1, 2019, to November 20, 2019. The institutional review board of the University of Pennsylvania deemed this study exempt from institutional review board approval, and informed consent was not required.
Study Population
Study inclusion criteria were as follows: (1) at least 1 International Classification of Diseases, Ninth Revision (ICD-9) or International Statistical Classification of Diseases and Related Health Problems, Tenth Revision (ICD-10) code for acne (codes 706.1, L70.0, L70.1, L70.8, and L70.9); (2) at least 6 months of continuous enrollment before the index date without any prescriptions for acne treatments or clinical encounters for acne during this period; and (3) at least 1 year of continuous enrollment after the index date. The date of the first diagnosis code for acne that met the study inclusion criteria was defined as the index date. The final 2 criteria were chosen to increase the likelihood of identifying a patient with a new diagnosis of acne and to ensure adequate follow-up to identify subsequent health care use in the first year after the diagnosis. A previous study19 validated the accuracy of the ICD-9 and ICD-10 codes to identify patients with acne.
Outcomes
Outcomes were evaluated during 1 year of follow-up after the index date. Health care use outcomes were defined as number of clinical encounters for acne and any dermatologist encounter for acne. Treatment outcomes were defined as number of prescriptions for acne therapies and any prescription for each of the following acne therapy categories: topical retinoids, topical antibiotics, oral antibiotics, spironolactone, oral contraceptives, and isotretinoin. Combination topicals were classified according to their individual components (eg, combination of adapalene and benzoyl peroxide was categorized as a topical retinoid).
Covariates
Age, sex, race/ethnicity, insurance type, region of residence, mean household income, and educational level were evaluated as factors that may be associated with health care use and treatment for acne. Race/ethnicity was categorized as non-Hispanic white (hereafter referred to as white), non-Hispanic black (hereafter referred to as black), non-Hispanic Asian (hereafter referred to as Asian), Hispanic of any race (hereafter referred to as Hispanic), or other. Insurance status was defined by the insurance type used for at least 70% of encounters. If no single insurance type was used for at least 70% of encounters, the patient was categorized as mixed/uninsured if they were listed as uninsured for any encounters and mixed/insured if all their encounters listed at least 1 type of insurance coverage. Household income was provided as a mean based on the first 3 digits of the patient’s zip code. Similarly, the educational level was provided as an overall percentage of individuals who had received a college education in the geographic area that corresponded to the first 3 digits of the patient’s zip code.
Statistical Analysis
Multivariable regression models were used to quantify the associations between basic patient demographic and socioeconomic characteristics and the outcomes of health care use and treatment for acne during 1 year of follow-up. Each outcome had been identified a priori with independent hypotheses; thus, statistical adjustments for multiple comparisons were not performed. Multivariable analyses included the following variables: age at diagnosis, sex, race/ethnicity, region, insurance type, whether the patient had been seen by a dermatologist (for number of visits and prescriptions and specific acne treatment outcomes), mean household income, and percentage with college education. Multivariable logistic regression was used to evaluate the likelihood of seeing a dermatologist and the likelihood of receiving a prescription for specific treatment categories within the first year of acne diagnosis. Negative binomial regression was used to examine the number of visits and prescriptions within the first year of acne diagnosis (zero-truncated models were used for number of visits because all patients had at least 1 visit). Negative binomial models rather than Poisson models were chosen for these outcomes because the data were overdispersed as assessed by the dispersion parameter α. Statistical significance was defined by a 2-sided P < .05. Statistical analyses were performed using Stata 15 (StataCorp).
Results
Study Cohort
A total of 29 928 patients (median age, 20.2 years; interquartile range [IQR], 15.4-34.9 years; 19 127 [63.9%] female; 20 310 [67.9%] white) met the inclusion criteria for the study. (Table 1). The most common insurance coverage was commercial insurance (14 492 [48.4%]), followed by mixed insurance carriers (5751 [19.2%]), Medicaid (2011 [6.7%]), Medicare (730 [2.4%]), and uninsured (687 [2.3%]). Regional distribution of patients across the United States was as follows: Northeast, 4526 (15.1%); Midwest, 16 680 (55.7%); South, 5732 (19.2%); and West, 2990 (10.0%).
Table 1. Demographic Characteristics of the Study Patientsa.
| Characteristic | Race/Ethnicity | |||||
|---|---|---|---|---|---|---|
| Non-Hispanic White (n = 20 310) | Non-Hispanic Black (n = 2388) | Non-Hispanic Asian (n = 867) | Hispanic (n = 1646) | Other (n = 4717) | Overall (N = 29 928) | |
| Age at diagnosis, median (IQR), y | 20.2 (15.6-35.6) | 20.8 (14.9-37.6) | 22.0 (15.3-34.9) | 17.8 (14.8-31.0) | 19.3 (15.3-32.5) | 20.2 (15.4-34.9) |
| Female | 13 030 (64.2) | 1665 (69.7) | 576 (66.4) | 1006 (61.1) | 2850 (60.4) | 19 127 (63.9) |
| Census region | ||||||
| Midwest | 12 548 (61.8) | 1376 (57.6) | 327 (37.7) | 548 (33.3) | 1881 (39.9) | 16 680 (55.7) |
| Northeast | 2912 (14.3) | 172 (7.2) | 126 (14.5) | 275 (16.7) | 1041 (22.1) | 4526 (15.1) |
| South | 3418 (16.8) | 730 (30.6) | 142 (16.4) | 555 (33.7) | 887 (18.8) | 5732 (19.2) |
| West | 1432 (7.1) | 110 (4.6) | 272 (31.4) | 268 (16.3) | 908 (19.3) | 2990 (10.0) |
| Insurance type | ||||||
| Commercial | 10 791 (53.1) | 1020 (42.7) | 361 (41.6) | 571 (34.7) | 1749 (37.1) | 14 492 (48.4) |
| Medicaid | 1023 (5.0) | 434 (18.2) | 39 (4.5) | 234 (14.2) | 281 (6.0) | 2011 (6.7) |
| Medicare | 562 (2.8) | 82 (3.4) | 8 (0.9) | 13 (0.8) | 65 (1.4) | 730 (2.4) |
| Uninsured | 496 (2.4) | 41 (1.7) | 4 (0.5) | 46 (2.8) | 100 (2.1) | 687 (2.3) |
| Mixed: insured | 4058 (20.0) | 429 (18.0) | 196 (22.6) | 346 (21.0) | 722 (15.3) | 5751 (19.2) |
| Mixed: uninsured | 295 (1.5) | 40 (1.7) | 11 (1.3) | 87 (5.3) | 51 (1.1) | 484 (1.6) |
| Unknown | 2601 (12.8) | 315 (13.2) | 225 (26.0) | 324 (19.7) | 1684 (35.7) | 5149 (17.2) |
| Other | 484 (2.4) | 27 (1.1) | 23 (2.7) | 25 (1.5) | 65 (1.4) | 624 (2.1) |
| Mean household income per $1000, median (IQR), $ | 42.0 (38.7-49.4) | 39.6 (36.3-46.9) | 48.6 (41.6-53.7) | 42.4 (38.7-49.2) | 44.4 (39.0-51.9) | 42.2 (38.8-49.5) |
| College education, median (IQR), % | 25 (20-29) | 25 (21-29) | 29 (24-37) | 24 (21-28) | 26 (20-26) | 25 (20-29) |
| PCOS | 169 (0.8) | 18 (0.8) | 6 (0.7) | 14 (0.9) | 37 (0.8) | 244 (0.8) |
| Seen by a dermatologist at least once | 7983 (39.3) | 932 (39.0) | 360 (41.5) | 499 (30.3) | 1954 (41.4) | 11 728 (39.2) |
| Acne visits, median (IQR), No. | 1 (1-2) | 1 (1-2) | 1 (1-2) | 1 (1-2) | 1 (1-2) | 1 (1-2) |
| Prescriptions, median (IQR), No. | 1 (0-3) | 1 (0-2) | 1 (0-2) | 1 (0-2) | 1 (0-2) | 1 (0-2) |
Abbreviations: IQR, interquartile range; PCOS, polycystic ovary syndrome.
Data are presented as number (percentage) of patients unless otherwise indicated.
Health Care Use
The median number of acne visits during the first year after the index date was 1 (IQR, 1-2), and 11 728 patients (39.2%) were seen by a dermatologist at least once. Although there were no differences in total number of acne visits across racial/ethnic groups, Hispanic patients were less likely (odds ratio [OR], 0.78; 95% CI, 0.70-0.88) and black patients were more likely (OR, 1.20; 95% CI, 1.09-1.31) to be seen by a dermatologist than white patients in adjusted analyses. In a post hoc evaluation, the likelihood of seeing a dermatologist varied by region and insurance status, suggesting complex interactions. In particular, compared with white patients with acne, black patients were more likely to see a dermatologist in the Midwest (OR, 1.95; 95% CI, 1.73-2.19) and less likely to see a dermatologist in the South (OR, 0.48; 95% CI, 0.39-0.59). Black patients with commercial (OR, 1.27; 95% CI, 1.11-1.45), Medicaid (OR, 2.07; 95% CI, 1.54-2.77), and Medicare (OR, 2.31; 95% CI, 1.38-3.86) insurance and those who were uninsured (OR, 2.59; 95% CI, 1.13-5.94) were also more likely than white patients with similar insurance to see a dermatologist. In contrast, although male patients had more acne visits than female patients (incidence rate ratio [IRR], 1.10; 95% CI, 1.02-1.19), men (OR, 0.89; 95% CI, 0.84-0.93) were less likely to be seen by a dermatologist in adjusted analyses (Table 2). Compared with patients with commercial insurance, those with Medicaid had more visits (IRR, 1.34; 95% CI, 1.19-1.51), and those without insurance had fewer visits (IRR, 0.75; 95% CI, 0.61-0.94) for acne. However, compared with commercial insurance, Medicaid (OR, 0.46; 95% CI, 0.41-0.52) and lack of insurance (OR, 0.43; 95% CI, 0.36-0.52), in particular, were each associated with lower odds of having a dermatologist visit.
Table 2. Likelihood of Dermatologist Treatment.
| Characteristic | Seen by a Dermatologist at Least Once, No./Total No. (%) | Adjusted OR (95% CI) |
|---|---|---|
| Race/ethnicity | ||
| Non-Hispanic white | 7983/20 310 (39.3) | Reference |
| Non-Hispanic black | 932/2388 (39.0) | 1.20 (1.09-1.31) |
| Non-Hispanic Asian | 360/867 (41.5) | 0.92 (0.79-1.06) |
| Hispanic | 499/1646 (30.3) | 0.78 (0.70-0.88) |
| Other | 1954/4717 (41.4) | 1.01 (0.94-1.08) |
| Age at diagnosis | NA | 1.02 (1.02-1.03) |
| Sex | ||
| Female | 6591/19 127 (34.5) | Reference |
| Male | 3195/10 801 (29.6) | 0.89 (0.84-0.93) |
| Region | ||
| Midwest | 4861/16 680 (29.1) | Reference |
| Northeast | 2381/4526 (52.6) | 1.73 (1.60-1.86) |
| South | 1540/5732 (26.9) | 0.76 (0.71-0.81) |
| West | 1004/2990 (33.6) | 1.02 (0.93-1.11) |
| Insurance type | ||
| Commercial | 5045/14 492 (34.8) | Reference |
| Medicaid | 290/2011 (14.4) | 0.46 (0.41-0.52) |
| Medicare | 350/730 (48.0) | 0.83 (0.70-0.98) |
| Uninsured | 107/687 (15.6) | 0.43 (0.36-0.52) |
| Mixed: insured | 1691/5751 (29.4) | 0.84 (0.79-0.90) |
| Mixed: uninsured | 118 /484(24.4) | 0.81 (0.66-0.99) |
| Unknown | 2014/5149 (39.1) | 1.06 (0.99-1.14) |
| Other | 171/624 (27.4) | 0.95 (0.80-1.13) |
| Mean household income per $1000 | NA | 1.02 (1.02-1.02) |
| Percentage with college education | NA | 1.01 (1.01-1.02) |
Abbreviations: NA, not applicable; OR, odds ratio.
Prescribing Patterns
The median number of acne prescriptions given during the first year after the index date across all patients was 1 (IQR, 0-2). In adjusted analyses, black patients received fewer prescriptions for acne medications than white patients (IRR, 0.89; 95% CI, 0.84-0.95), and male patients received fewer prescriptions (IRR, 0.84; 95% CI, 0.81-0.86) for acne than female patients. In addition, Medicaid (IRR, 0.89; 95% CI, 0.84-0.95) and lack of insurance (IRR, 0.51; 95% CI, 0.43-0.61) were each associated with fewer prescriptions for acne mediations compared with commercial insurance (Table 3).
Table 3. Number of Dermatologist Visits and Acne Prescriptions.
| Characteristic | Visits | Prescriptions | ||
|---|---|---|---|---|
| No., Median (IQR) | Adjusted IRR (95% CI) | No., Median (IQR) | Adjusted IRR (95% CI) | |
| Race/ethnicity | ||||
| Non-Hispanic white | 1 (1-2) | Reference | 1 (0-3) | Reference |
| Non-Hispanic black | 1 (1-2) | 0.99 (0.88-1.12) | 1 (0-2) | 0.89 (0.84-0.95) |
| Non-Hispanic Asian | 1 (1-2) | 0.96 (0.84-1.10) | 1 (0-2) | 0.94 (0.86-1.02) |
| Hispanic | 1 (1-2) | 1.00 (0.86-1.15) | 1 (0-2) | 0.95 (0.88-1.02) |
| Other | 1 (1-2) | 0.92 (0.85-1.01) | 1 (0-2) | 0.85 (0.81-0.89) |
| Age at diagnosis | NA | 0.98 (0.98-0.98) | NA | 0.98 (0.98-0.98) |
| Sex | ||||
| Female | 1 (1-2) | Reference | 1 (0-3) | Reference |
| Male | 1 (1-2) | 1.10 (1.02-1.19) | 1 (0-2) | 0.84 (0.81-0.86) |
| Region | ||||
| Midwest | 1 (1-2) | Reference | 1 (0-3) | Reference |
| Northeast | 1 (1-2) | 0.99 (0.89-1.10) | 1 (0-2) | 0.85 (0.81-0.90) |
| South | 1 (1-2) | 1.47 (1.35-1.60) | 1 (0-2) | 0.93 (0.89-0.97) |
| West | 1 (1-2) | 0.97 (0.88-1.08) | 1 (0-2) | 0.95 (0.90-1.01) |
| Insurance type | ||||
| Commercial | 1 (1-2) | Reference | 1 (0-3) | Reference |
| Medicaid | 1 (1-2) | 1.34 (1.19-1.51) | 1 (0-2) | 0.89 (0.84-0.95) |
| Medicare | 1 (1-1) | 1.35 (0.73-2.48) | 0 (0-1) | 0.93 (0.81-1.06) |
| Uninsured | 1 (1-2) | 0.75 (0.61-0.94) | 0 (0-1) | 0.51 (0.43-0.61) |
| Mixed: insured | 1 (1-2) | 1.05 (0.96-1.14) | 1 (0-2) | 0.94 (0.90-0.98) |
| Mixed: uninsured | 1 (1-2) | 1.37 (0.68-2.77) | 1 (0-2) | 0.90 (0.80-1.02) |
| Unknown | 1 (1-2) | 0.83 (0.76-0.90) | 0 (0-2) | 0.84 (0.80-0.89) |
| Other | 1 (1-2) | 1.01 (0.86-1.20) | 2 (0-3) | 1.11 (1.02-1.21) |
| Mean household income, $1000 | NA | 0.99 (0.99-1.00) | NA | 1.00 (1.00-1.00) |
| Percentage with college education | NA | 1.01 (1.00-1.01) | NA | 0.99 (0.99-0.99) |
| Seen by a dermatologist at least once | NA | 2.92 (2.72-3.13) | NA | 1.80 (1.74-1.86) |
Abbreviations: IQR, interquartile range; IRR, incidence rate ratio; NA, not applicable.
With regard to specific acne treatments, compared with white patients, black patients were more likely to be prescribed topical retinoids (OR, 1.25; 95% CI, 1.14-1.38) and topical antibiotics (OR, 1.35; 95% CI, 1.21-1.52) and less likely to be prescribed oral antibiotics (OR, 0.80; 95% CI, 0.72-0.87), spironolactone (OR, 0.68; 95% CI, 0.49-0.94), and isotretinoin (OR, 0.39; 95% CI, 0.23-0.65) in adjusted analyses. Asian patients were more likely to be prescribed topical antibiotics (OR, 1.47; 95% CI, 1.23-1.75) and less likely to be prescribed oral antibiotics (OR, 0.80; 95% CI, 0.69-0.94) than white patients. There were no statistically significant differences in the odds of receiving prescriptions for spironolactone (OR, 0.77; 95% CI, 0.59-1.01) or isotretinoin (OR, 0.68; 95% CI, 0.42-1.12) between Hispanic and white patients. Hispanic patients (OR, 0.62; 95% CI, 0.54-0.71), black patients (OR, 0.64; 95% CI, 0.53-0.76), and Asian patients (OR, 0.74; 95% CI, 0.56-0.96) were each less likely than white patients to be prescribed combined oral contraceptives.
Male patients were more likely to be prescribed oral antibiotics (OR, 1.12; 95% CI, 1.06-1.18) and isotretinoin than female patients (OR, 2.44; 95% CI, 2.01-2.95) (Table 4). In addition, among a subgroup of 10 312 patients who had been prescribed an oral antibiotic or spironolactone, male patients were more likely to be prescribed isotretinoin than female patients (OR, 2.18; 95% CI, 1.70-2.82).
Table 4. Adjusted ORs for Specific Acne Prescription Treatments.
| Characteristic |
Topical Retinoid | Topical Antibiotic | Oral Antibiotic | Spironolactonea | Oral Contraceptivea | Isotretinoin | ||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| No. (%) | Adjusted OR (95% CI) | No. (%) | Adjusted OR (95% CI) | No. (%) | Adjusted OR (95% CI) | No. (%) | Adjusted OR (95% CI) | No. (%) | Adjusted OR (95% CI) | No. (%) | Adjusted OR (95% CI) | |
| Race/ethnicity | ||||||||||||
| Non-Hispanic white | 8084 (27.0) | Reference | 4430 (14.8) | Reference | 10 630 (35.5) | Reference | 435 (2.3) | Reference | 1778 (9.3) | Reference | 536 (1.8) | Reference |
| Non-Hispanic black | 9186 (30.7) | 1.25 (1.14-1.38) | 5489 (18.3) | 1.35 (1.21-1.52) | 9024 (30.2) | 0.80 (0.72-0.87) | 352 (1.8) | 0.68 (0.49-0.94) | 1258 (6.6) | 0.64 (0.53-0.76) | 188 (0.6) | 0.39 (0.23-0.65) |
| Non-Hispanic Asian | 8630 (28.8) | 1.12 (0.96-1.32) | 6110 (20.4) | 1.47 (1.23-1.75) | 8561 (28.6) | 0.80 (0.69-0.94) | 221 (1.2) | 0.58 (0.31-1.10) | 1434 (7.5) | 0.74 (0.56-0.96) | 414 (1.4) | 0.86 (0.48-1.55) |
| Hispanic | 7473 (25.0) | 0.96 (0.85-1.09) | 4309 (14.4) | 1.06 (0.92-1.23) | 9818 (32.8) | 0.95 (0.86-1.07) | 232 (1.2) | 0.77 (0.59-1.01) | 1116 (5.8) | 0.62 (0.54-0.71) | 309 (1.0) | 0.68 (0.42-1.12) |
| Other | 7005 (23.4) | 0.84 (0.78-0.91) | 3762 (12.6) | 0.86 (0.78-0.95) | 7925 (26.5) | 0.72 (0.67-0.78) | 304 (1.6) | 1.11 (0.74-1.67) | 1160 (6.1) | 0.78 (0.62-0.97) | 336 (1.1) | 0.69 (0.51-0.93) |
| Age at diagnosis | NA | 0.96 (0.96-0.97) | NA | 0.99 (0.98-0.99) | NA | 0.99 (0.99-1.00) | NA | 1.03 (1.02-1.03) | NA | 0.97 (0.96-0.97) | NA | 0.97 (0.96-0.98) |
| Sex | ||||||||||||
| Female | 8021 (26.8) | Reference | 4489 (15.0) | Reference | 9667 (32.3) | Reference | NA | NA | NA | NA | 299 (1.0) | Reference |
| Male | 7931 (26.5) | 0.88 (0.83-0.94) | 4399 (14.7) | 0.94 (0.87-1.00) | 10 505 (35.1) | 1.12 (1.06-1.18) | NA | NA | NA | NA | 748 (2.5) | 2.44 (2.01-2.95) |
| Region | ||||||||||||
| Midwest | 8236 (27.5) | Reference | 4837 (16.2) | Reference | 10 760 (36.0) | Reference | 385 (2.0) | Reference | 1808 (9.5) | Reference | 506 (1.7) | Reference |
| Northeast | 8067 (27.0) | 0.86 (0.79-0.94) | 4787 (16.0) | 0.86 (0.78-0.96) | 8180 (27.3) | 0.74 (0.68-0.80) | 199 (1.0) | 0.59 (0.42-0.82) | 1179 (6.2) | 0.75 (0.65-0.88) | 390 (1.3) | 0.75 (0.55-1.04) |
| South | 7566 (25.3) | 0.99 (0.92-1.07) | 3007 (10.0) | 0.60 (0.54-0.66) | 9753 (32.6) | 0.91 (0.85-0.97) | 544 (2.8) | 1.17 (0.96-1.43) | 1371 (7.2) | 0.79 (0.70-0.90) | 465 (1.6) | 1.07 (0.84-1.38) |
| West | 7257 (24.2) | 1.06 (0.96-1.17) | 4554 (15.2) | 1.02 (0.90-1.15) | 8698 (29.1) | 0.91 (0.83-1.00) | 416 (2.2) | 1.18 (0.88-1.58) | 1439 (7.5) | 0.97 (0.82-1.14) | 310 (1.0) | 0.84 (0.57-1.24) |
| Insurance type | ||||||||||||
| Commercial | 8799 (29.4) | Reference | 4639 (15.5) | Reference | 10 782 (36.0) | Reference | 519 (2.7) | Reference | 1807 (9.4) | Reference | 624 (2.1) | Reference |
| Medicaid | 7602 (25.4) | 0.82 (0.73-0.92) | 5686 (19.0) | 1.34 (1.18-1.52) | 9718 (32.5) | 0.87 (0.79-0.97) | 190 (1.0) | 0.50 (0.31-0.80) | 1417 (7.4) | 0.65 (0.54-0.79) | 208 (0.7) | 0.43 (0.25-0.75) |
| Medicare | 4729 (15.8) | 1.14 (0.91-1.42) | 3442 (11.5) | 1.04 (0.81-1.34) | 8486 (28.4) | 0.80 (0.67-0.95) | 498 (2.6) | 0.31 (0.18-0.53) | 393 (2.1) | 0.50 (0.29-0.85) | 123 (0.4) | 0.47 (0.15-1.53) |
| Uninsured | 6973 (23.3) | 0.35 (0.27-0.45) | 1556 (5.2) | 0.35 (0.25-0.49) | 6622 (22.1) | 0.50 (0.42-0.60) | 56 (0.3) | 0.10 (0.02-0.39) | 919 (4.8) | 0.40 (0.28-0.57) | 174 (0.6) | 0.37 (0.14-1.01) |
| Mixed: insured | 7991 (26.7) | 0.97 (0.90-1.04) | 4579 (15.3) | 1.03 (0.95-1.13) | 10 247 (34.2) | 0.94 (0.88-1.01) | 319 (1.7) | 0.61 (0.48-0.77) | 1646 (8.6) | 0.91 (0.81-1.02) | 411 (1.4) | 0.74 (0.57-0.96) |
| Mixed: uninsured | 3172 (10.6) | 0.78 (0.62-0.97) | 4280 (14.3) | 1.01 (0.77-1.31) | 9832 (32.9) | 0.86 (0.71-1.04) | 316 (1.7) | 0.56 (0.26-1.21) | 1344 (7.0) | 0.76 (0.53-1.10) | 186 (0.6) | 0.31 (0.10-0.97) |
| Unknown | 6614 (22.1) | 0.68 (0.63-0.74) | 3771 (12.6) | 0.76 (0.69-0.84) | 7916 (26.5) | 0.73 (0.67-0.78) | 223 (1.2) | 0.50 (0.37-0.67) | 1196 (6.3) | 0.80 (0.69-0.91) | 279 (0.9) | 0.48 (0.35-0.66) |
| Other | 11642 (38.9) | 1.71 (1.44-2.03) | 4549 (15.2) | 1.04 (0.83-1.30) | 11 894 (39.7) | 1.14 (0.97-1.34) | 398 (2.1) | 0.76 (0.43-1.34) | 2299 (12.0) | 1.30 (1.00-1.69) | 384 (1.3) | 0.58 (0.28-1.18) |
| Mean household income per $1000 | NA | 1.00 (1.00-1.01) | NA | 1.02 (1.01-1.02) | NA | 1.00 (1.00-1.00) | NA | 0.97 (0.96-0.98) | NA | 1.00 (0.99-1.00) | NA | 0.99 (0.97-1.00) |
| Percentage with college education | NA | 0.99 (0.99-1.00) | NA | 0.99 (0.98-1.00) | NA | 0.99 (0.98-0.99) | NA | 1.01 (1.00-1.03) | NA | 1.00 (1.00-1.01) | NA | 1.00 (0.98-1.02) |
| Seen by a dermatologist at least once | NA | 3.38 (3.19-3.58) | NA | 1.70 (1.58-1.82) | NA | 1.24 (1.17-1.31) | NA | 1.73 (1.46-2.05) | NA | 0.66 (0.59-0.73) | NA | 4.48 (3.68-5.47) |
Abbreviations: NA, not applicable; OR, odds ratio.
Among women only.
Compared with those with commercial insurance, those with Medicaid were less likely to receive prescriptions for topical retinoids (OR, 0.82; 95% CI, 0.73-0.92), oral antibiotics (OR, 0.87; 95% CI, 0.79-0.97), spironolactone (OR, 0.50; 95% CI, 0.31-0.80), and isotretinoin (OR, 0.43; 95% CI, 0.25-0.75).
A post hoc stratified analysis was performed to compare prescribing patterns between patients seen by a dermatologist at least once and those never having seen a dermatologist and identified similar treatment patterns (eTable in the Supplement).
Discussion
In this retrospective cohort study of patients with acne, we found racial/ethnic, sex, and insurance-based differences in health care use and prescribing patterns for acne that were independent of other sociodemographic factors that were available in the data set and that suggest that disparities may exist in acne care. Of particular note, despite being more likely to see a dermatologist and having a similar number of visits for acne, black patients generally received fewer prescriptions for acne, were less likely to receive prescriptions for systemic treatments (ie, oral antibiotics, combined oral contraceptives, spironolactone, and isotretinoin), and were more likely to receive prescriptions for topical treatments (ie, topical retinoids and topical antibiotics) than white patients. A similar acne treatment pattern was also observed among Asian patients, who were more likely than white patients to receive topical antibiotics and less likely to receive oral antibiotics and oral contraceptives. In addition, Hispanic patients were less likely than white patients to receive prescriptions for oral contraceptives; there were no statistically significant differences in the likelihood of receiving prescriptions for spironolactone or isotretinoin between the 2 groups. The increased odds of prescriptions for topical retinoids among minorities who generally have darker skin types could be related to management of postinflammatory hyperpigmentation.20 However, the reduced use of specific systemic medications among minorities may suggest undertreatment in these populations.
The factors underlying these associations are not entirely clear. Of note, our observation of black patients with acne being more likely than white patients to see a dermatologist is in contrast to prior studies11,13 using NAMCS data. Post hoc analyses of our data suggest that our findings may be explained by a combination of interactions with region and insurance status. In the Optum data set used for this study, particular overrepresentation of the Midwest, in which black patients with acne had nearly 2-fold higher odds of seeing a dermatologist than white patients, appears to be a major contributor to the discrepant findings. Among patients residing in the South, the region that was most represented in NAMCS data,11 black patients were less likely than white patients to see a dermatologist for acne, similar to prior publications.11,13 Nevertheless, acne treatment pattern differences persisted even after accounting for dermatologist visits, unlike what was observed in the study by Rogers et al.13
It is unlikely that differences in acne severity account for the different treatment patterns observed. Most of the literature, to date, does not support major differences in acne severity or quality of life impact by race/ethnicity.7,21 In fact, a study22 suggests that black adolescents may be slightly more likely to report severe acne, which would warrant more systemic treatment among this group and may, in part, contribute to the differences in the likelihood to see a dermatologist that we observed. Although a prior study12 suggested that cost may be a factor associated with racial/ethnic differences in isotretinoin prescribing, our findings highlight that these differences persisted after controlling for mean household income. Our study did not investigate specific reasons for the racial/ethnic differences in acne care that we observed, but other literature suggests that these differences may be due to a broad spectrum of factors, including risk aversion,23 medical distrust,24,25 and physician bias, among others.26 These factors deserve further study.
We also observed that female patients were less likely to be prescribed isotretinoin than male patients. This finding persisted among a subgroup of patients who had been prescribed an oral antibiotic or spironolactone and thus were more likely to have moderate to severe acne. In light of multiple studies27,28 suggesting that acne may have a greater influence on quality of life among female patients compared with male patients, it is particularly notable that our study findings suggest sex disparities in isotretinoin prescriptions that may indicate undertreatment of acne among female patients. Given the burdens of iPLEDGE, a risk management distribution program mandated by the US Food and Drug Administration for isotretinoin, and larger decreases in prescriptions for female patients than male patients after its introduction, it is possible that differences in the burden of iPLEDGE between male and female patients may result in underuse of isotretinoin among female patients with acne.29,30,31 Thus, our findings raise additional questions about whether the benefits of iPLEDGE outweigh its potential unintended negative effects.29,32,33,34
Patients with Medicaid and patients without insurance were less likely to be seen by a dermatologist and less likely to be prescribed treatments for acne than those with commercial insurance. These findings are consistent with prior work35,36 that suggests that Medicaid patients may have reduced access to dermatologic care. The fact that Medicaid reimburses at lower rates than other payers may adversely affect access to care.37 Increasing payer parity and alternative care models, such as teledermatology, may be important to ensure that patients with all insurance types have equal access to acne care.38
Although patients with Medicaid were less likely than those with commercial insurance to be seen by a dermatologist, patients with Medicaid had more acne visits. The underlying factors behind this observation are also unclear. It is possible that patients with Medicaid may be more likely to need follow-up visits to manage ongoing acne activity because they are less likely to receive any treatment, including systemic treatments, for their acne. This possibility, too, warrants further study.
Strengths and Limitations
Our study adds to the existing literature by providing additional insight into the health care use and specific prescribing patterns for acne using a national electronic health record database. Strengths of our study include a detailed examination of specific treatment classes for acne and sociodemographic factors that may be associated with health care use for and treatment of acne on a patient level with relatively granular racial/ethnic groups.
The results of this study should, however, be interpreted in the context of its limitations. Given that the study was conducted using automated data from an electronic medical records database that lacks associated pharmacy claims data, we were unable to determine whether patients picked up the prescriptions documented in the electronic medical record. Because primary nonadherence for acne treatments is common, our results may overestimate the number of prescriptions actually received.39 Nevertheless, the data provide important insight into the prescribing patterns of physicians. In addition, we did not have data on acne severity and clinical outcomes; thus, we could not assess the influence of these factors on our results, although prior studies7,21 have suggested that acne severity does not differ significantly by race/ethnicity or sex. We were also unable to directly assess whether greater treatment use among white patients, particularly for systemic treatments, represents overtreatment. However, the proportions of white patients receiving any systemic treatment or specifically isotretinoin approximate the prevalence estimates for moderate to severe (15%-30%)2,40,41 and severe acne (2%-5%)1,41 for which these treatments are respectively indicated, arguing against overtreatment of acne among this group. Over-the-counter treatments (eg, benzoyl peroxide) were not captured in our data set, although many patients presenting to a medical practitioner for acne care may be specifically seeking prescription treatments. The Midwest region was relatively overrepresented in our data set, and although we adjusted for geographic region in our analyses, our findings many not be generalizable to all US regions. Also, although we accounted for the sociodemographic and other factors that were available in our data set and that may be associated with acne care, there may be residual unmeasured confounding that affects the suggested racial/ethnic, sex, and insurance-based differences in acne care that we observed.
Conclusions
Our findings suggest the presence of racial/ethnic, sex, and insurance-based disparities in health care use and treatment for acne and raise particular concern for undertreatment among racial/ethnic minority and female patients. Further study is needed to confirm our findings, provide understanding of the reasons for these potential disparities, and develop strategies to ensure equitable care for patients with acne.
eTable. Prescribing Patterns Between Patients Seen by a Dermatologist at Least Once and Those Never Having Seen a Dermatologist
References
- 1.Stathakis V, Kilkenny M, Marks R. Descriptive epidemiology of acne vulgaris in the community. Australas J Dermatol. 1997;38(3):115-123. doi: 10.1111/j.1440-0960.1997.tb01126.x [DOI] [PubMed] [Google Scholar]
- 2.Collier CN, Harper JC, Cafardi JA, et al. . The prevalence of acne in adults 20 years and older. J Am Acad Dermatol. 2008;58(1):56-59. doi: 10.1016/j.jaad.2007.06.045 [DOI] [PubMed] [Google Scholar]
- 3.Vallerand IA, Lewinson RT, Parsons LM, et al. . Risk of depression among patients with acne in the U.K.: a population-based cohort study. Br J Dermatol. 2018;178(3):e194-e195. doi: 10.1111/bjd.16099 [DOI] [PubMed] [Google Scholar]
- 4.Huang Y-C, Cheng Y-C. Isotretinoin treatment for acne and risk of depression: a systematic review and meta-analysis. J Am Acad Dermatol. 2017;76(6):1068-1076.e9. doi: 10.1016/j.jaad.2016.12.028 [DOI] [PubMed] [Google Scholar]
- 5.Sundström A, Alfredsson L, Sjölin-Forsberg G, Gerdén B, Bergman U, Jokinen J. Association of suicide attempts with acne and treatment with isotretinoin: retrospective Swedish cohort study. BMJ. 2010;341:c5812. doi: 10.1136/bmj.c5812 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 6.Karimkhani C, Dellavalle RP, Coffeng LE, et al. . Global skin disease morbidity and mortality: an update from the Global Burden of Disease Study 2013. JAMA Dermatol. 2017;153(5):406-412. doi: 10.1001/jamadermatol.2016.5538 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 7.Callender VD, Alexis AF, Daniels SR, et al. . Racial differences in clinical characteristics, perceptions and behaviors, and psychosocial impact of adult female acne. J Clin Aesthet Dermatol. 2014;7(7):19-31. [PMC free article] [PubMed] [Google Scholar]
- 8.Fischer AH, Shin DB, Margolis DJ, Takeshita J. Racial and ethnic differences in health care utilization for childhood eczema: an analysis of the 2001-2013 Medical Expenditure Panel Surveys. J Am Acad Dermatol. 2017;77(6):1060-1067. doi: 10.1016/j.jaad.2017.08.035 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 9.Fischer AH, Shin DB, Gelfand JM, Takeshita J. Health care utilization for psoriasis in the United States differs by race: an analysis of the 2001-2013 Medical Expenditure Panel Surveys. J Am Acad Dermatol. 2018;78(1):200-203. doi: 10.1016/j.jaad.2017.07.052 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 10.Berk DR, Kanzler MH. What determines whether patients with skin conditions visit dermatologists? J Am Acad Dermatol. 2005;52(4):734. doi: 10.1016/j.jaad.2004.10.871 [DOI] [PubMed] [Google Scholar]
- 11.Patel VM, Schwartz RA. Disparities in access to a dermatologist for acne care in the United States. Int J Dermatol. 2017;56(6):e131-e133. doi: 10.1111/ijd.13481 [DOI] [PubMed] [Google Scholar]
- 12.Fleischer AB Jr, Simpson JK, McMichael A, Feldman SR. Are there racial and sex differences in the use of oral isotretinoin for acne management in the United States? J Am Acad Dermatol. 2003;49(4):662-666. doi: 10.1067/S0190-9622(03)01584-6 [DOI] [PubMed] [Google Scholar]
- 13.Rogers AT, Semenov YR, Kwatra SG, Okoye GA. Racial disparities in the management of acne: evidence from the National Ambulatory Medical Care Survey, 2005-2014. J Dermatolog Treat. 2018;29(3):287-289. doi: 10.1080/09546634.2017.1371836 [DOI] [PubMed] [Google Scholar]
- 14.Moodie P, Jaine R, Arnold J, Bignall M, Metcalfe S, Arroll B. Usage and equity of access to isotretinoin in New Zealand by deprivation and ethnicity. N Z Med J. 2011;124(1346):34-43. [PubMed] [Google Scholar]
- 15.Lopez I, Zapata L Jr, Sosa JJ, et al. . Acne knowledge of Hispanic parents of teenagers with mild to moderate acne. Pediatr Dermatol. 2016;33(5):e292-e293. doi: 10.1111/pde.12934 [DOI] [PubMed] [Google Scholar]
- 16.Nunes AP, Yang J, Radican L, et al. . Assessing occurrence of hypoglycemia and its severity from electronic health records of patients with type 2 diabetes mellitus. Diabetes Res Clin Pract. 2016;121:192-203. doi: 10.1016/j.diabres.2016.09.012 [DOI] [PubMed] [Google Scholar]
- 17.Walker AM, Zhou X, Ananthakrishnan AN, et al. . Computer-assisted expert case definition in electronic health records. Int J Med Inform. 2016;86:62-70. doi: 10.1016/j.ijmedinf.2015.10.005 [DOI] [PubMed] [Google Scholar]
- 18.Mannino DM, Yu T-C, Zhou H, Higuchi K. Effects of GOLD-adherent prescribing on COPD symptom burden, exacerbations, and health care utilization in a real-world setting. Chronic Obstr Pulm Dis. 2015;2(3):223-235. doi: 10.15326/jcopdf.2.3.2014.0151 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 19.Ejaz A, Malaiyandi V, Kim WB, Rogalska T, Alhusayen R. Validating the diagnostic code for acne in a tertiary care dermatology centre. Eur J Dermatol. 2015;25(5):469-471. doi: 10.1684/ejd.2015.2606 [DOI] [PubMed] [Google Scholar]
- 20.Woolery-Lloyd HC, Keri J, Doig S. Retinoids and azelaic acid to treat acne and hyperpigmentation in skin of color. J Drugs Dermatol. 2013;12(4):434-437. [PubMed] [Google Scholar]
- 21.Gorelick J, Daniels SR, Kawata AK, et al. . Acne-related quality of life among female adults of different races/ethnicities. J Dermatol Nurses Assoc. 2015;7(3):154-162. doi: 10.1097/JDN.0000000000000129 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 22.Cheng CE, Irwin B, Mauriello D, Liang L, Pappert A, Kimball AB. Self-reported acne severity, treatment, and belief patterns across multiple racial and ethnic groups in adolescent students. Pediatr Dermatol. 2010;27(5):446-452. doi: 10.1111/j.1525-1470.2010.01286.x [DOI] [PubMed] [Google Scholar]
- 23.Constantinescu F, Goucher S, Weinstein A, Smith W, Fraenkel L. Understanding why rheumatoid arthritis patient treatment preferences differ by race. Arthritis Rheum. 2009;61(4):413-418. doi: 10.1002/art.24338 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 24.Boulware LE, Cooper LA, Ratner LE, LaVeist TA, Powe NR. Race and trust in the health care system. Public Health Rep. 2003;118(4):358-365. doi: 10.1016/S0033-3549(04)50262-5 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 25.LaVeist TA, Nickerson KJ, Bowie JV. Attitudes about racism, medical mistrust, and satisfaction with care among African American and white cardiac patients. Med Care Res Rev. 2000;57(suppl 1):146-161. doi: 10.1177/1077558700057001S07 [DOI] [PubMed] [Google Scholar]
- 26.Hall WJ, Chapman MV, Lee KM, et al. . Implicit racial/ethnic bias among health care professionals and its influence on health care outcomes: a systematic review. Am J Public Health. 2015;105(12):e60-e76. doi: 10.2105/AJPH.2015.302903 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 27.Chernyshov PV, Zouboulis CC, Tomas-Aragones L, et al. . Quality of life measurement in hidradenitis suppurativa: position statement of the European Academy of Dermatology and Venereology task forces on Quality of Life and Patient-Oriented Outcomes and Acne, Rosacea and Hidradenitis Suppurativa. J Eur Acad Dermatol Venereol. 2019;33(9):1633-1643. doi: 10.1111/jdv.15519 [DOI] [PubMed] [Google Scholar]
- 28.Berg M, Lindberg M. Possible gender differences in the quality of life and choice of therapy in acne. J Eur Acad Dermatol Venereol. 2011;25(8):969-972. doi: 10.1111/j.1468-3083.2010.03907.x [DOI] [PubMed] [Google Scholar]
- 29.Mori WS, Houston N, Moreau JF, et al. . Personal burden of isotretinoin therapy and willingness to pay for electronic follow-up visits. JAMA Dermatol. 2016;152(3):338-340. doi: 10.1001/jamadermatol.2015.4763 [DOI] [PubMed] [Google Scholar]
- 30.Pinheiro SP, Kang EM, Kim CY, Governale LA, Zhou EH, Hammad TA. Concomitant use of isotretinoin and contraceptives before and after iPledge in the United States. Pharmacoepidemiol Drug Saf. 2013;22(12):1251-1257. doi: 10.1002/pds.3481 [DOI] [PubMed] [Google Scholar]
- 31.Chaudhry SB, Armbrecht ES, Shin Y, et al. . Pediatric access to dermatologists: Medicaid versus private insurance. J Am Acad Dermatol. 2013;68(5):738-748. doi: 10.1016/j.jaad.2012.10.034 [DOI] [PubMed] [Google Scholar]
- 32.Prevost N, English JC. Isotretinoin: update on controversial issues. J Pediatr Adolesc Gynecol. 2013;26(5):290-293. doi: 10.1016/j.jpag.2013.05.007 [DOI] [PubMed] [Google Scholar]
- 33.Charrow A, Xia FD, Lu J, Waul M, Joyce C, Mostaghimi A. Differences in isotretinoin start, interruption, and early termination across race and sex in the iPLEDGE era. PLoS One. 2019;14(3):e0210445. doi: 10.1371/journal.pone.0210445 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 34.Barbieri JS, Frieden IJ, Nagler AR. Isotretinoin, patient safety, and patient-centered care-time to reform iPLEDGE [published online October 30, 2019]. JAMA Dermatol. [DOI] [PubMed] [Google Scholar]
- 35.Adamson AS, Zhou L, Baggett CD, Thomas NE, Meyer A-M. Association of delays in surgery for melanoma with insurance type. JAMA Dermatol. 2017;153(11):1106-1113. doi: 10.1001/jamadermatol.2017.3338 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 36.Resneck J Jr, Pletcher MJ, Lozano N. Medicare, Medicaid, and access to dermatologists: the effect of patient insurance on appointment access and wait times. J Am Acad Dermatol. 2004;50(1):85-92. doi: 10.1016/S0190-9622(03)02463-0 [DOI] [PubMed] [Google Scholar]
- 37.Zuckerman S, Goin D How much will Medicaid physician fees for primary care rise in 2013? evidence from a 2012 survey of Medicaid physician fees. Henry J Kaiser Family Foundation Issue Paper. December 2012. https://kaiserfamilyfoundation.files.wordpress.com/2013/01/8398.pdf. Accessed January 22, 2019.
- 38.Uscher-Pines L, Malsberger R, Burgette L, Mulcahy A, Mehrotra A. Effect of teledermatology on access to dermatology care among Medicaid enrollees. JAMA Dermatol. 2016;152(8):905-912. doi: 10.1001/jamadermatol.2016.0938 [DOI] [PubMed] [Google Scholar]
- 39.Anderson KL, Dothard EH, Huang KE, Feldman SR. Frequency of primary nonadherence to acne treatment. JAMA Dermatol. 2015;151(6):623-626. doi: 10.1001/jamadermatol.2014.5254 [DOI] [PubMed] [Google Scholar]
- 40.Bhate K, Williams HC. Epidemiology of acne vulgaris. Br J Dermatol. 2013;168(3):474-485. doi: 10.1111/bjd.12149 [DOI] [PubMed] [Google Scholar]
- 41.Tan JKL, Bhate K. A global perspective on the epidemiology of acne. Br J Dermatol. 2015;172(suppl 1):3-12. doi: 10.1111/bjd.13462 [DOI] [PubMed] [Google Scholar]
Associated Data
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Supplementary Materials
eTable. Prescribing Patterns Between Patients Seen by a Dermatologist at Least Once and Those Never Having Seen a Dermatologist