Disparities in the Use of Teledermatology During the COVID-19 Pandemic Lockdown in a Pediatric Dermatology Practice
Introduction
The COVID-19 pandemic emerged abruptly in early 2020, prompting a global lockdown. Within New York City (NYC), all public schools closed March 16, 2020, and on March 22, 2020, lockdown for all nonessential services in New York State began with the NYS on PAUSE Executive Order, persisting until Phase 1 reopening on June 8, 2020. Between March and May 2020, tens of thousands of individuals contracted COVID-19, with the number of deaths reaching 18,679 within NYC. Estimates suggest that prevalence within the NYC pediatric population reached 6,016 cases (348 per 100,000). Increased case prevalence was directly correlated with minority groups and high neighborhood poverty, with the highest case burdens in the boroughs of the Bronx, Queens, and Staten Island.1 Variability in COVID-19 case burden within the initial wave was largely attributable to residents’ socioeconomic status.2
The burden placed on hospitals led to a rapid shuttering of nonessential health care services, including calls to terminate nonemergent dermatology visits.3–5 Despite this pause, health care needs aside from direct COVID-19 treatment remained prevalent. These included care for dermatologic conditions secondary to infection prevention measures, dermatologic manifestations of COVID-19 infection, and management of existing dermatologic conditions and associated therapies.6–9 Centers for Medicare and Medicaid Services ultimately allowed for the use of telehealth services to deliver care. These waivers resulted in wider flexibility for digital platforms, increased coverage of telehealth delivery, and reciprocal licensure (1,135 waiver authority and Coronavirus Preparedness Response Supplemental Appropriations Act, March 27, 2020 [H.R.6074]).10
The pandemic specifically precipitated a wide-scale adoption of teledermatology.11,12 The utility of pediatric teledermatology had been discussed before the pandemic, with reviews citing potentially improved access to care of underserved populations and lower-cost visits as potential benefits. However, technology costs, language barriers, low reimbursement rates, and technological complexity were considered major barriers to widespread adoption.13,14 A recent randomized clinical trial demonstrated an 83% concordance between photograph-based and in-person diagnosis, highlighting the utility of pediatric teledermatology.15
Further studies demonstrate decreased time-to-consult and improved parent satisfaction, improved access to pediatric dermatologic care, decreased need for in-person referrals and decreased no-show rate.16,17 A recent review acknowledged improved triage capability and a comparable concordance seen in pediatric teledermatology visits compared with concordance between independent in-person clinicians. However, it was maintained that several aforementioned barriers remain, and further research and optimization of pediatric teledermatology are still required to support underserved populations.18
Although further research of telehealth utility in pediatric teledermatology is required, it provided crucial access to care for patients at the onset of the pandemic. Although aforementioned studies theorize pediatric teledermatology may improve access to care in underserved populations, it was recently shown socioeconomic disparities, including age, sex, and household income influence participation in telehealth.19 Furthermore, the socioeconomic inequities, which the pandemic has exacerbated, are evident within pediatric dermatology.20–23 Given these inequities and discrepancies in participation in telehealth, we aimed to characterize the demographic profiles of patients seen at a dedicated New York pediatric dermatology practice with a strong skin of color population before and during the COVID-19 lockdown of 2020.
Methods
An Institutional Review Board-approved retrospective chart review of pediatric patients seen in an exclusively pediatric dermatology practice with skin-of-color focus in NYC on matching days, 4 practice weeks pre-COVID-19 pandemic lockdown and 4 practice weeks in May 2020 during the pandemic lockdown was conducted. We collected data on age, gender, race, zip code (as a proxy for median household income), insurance type, and presenting condition. We performed χ2 analyses to determine differences in demographic characteristics between patients seen before and during the lockdown with respect to race, gender, and patient insurance status.
To determine differences in proportions of patients that belonged to individual races, genders, insurance statuses, and no-show status pre- and post-pandemic, we performed two-tailed t-tests of proportions. We performed a two-tailed t-test of means to determine differences in patient age and a one-tailed t-test of means to determine whether median household income was greater for patients seen during the pandemic. U.S. Census Data were used to determine median household income by zip code. Median household incomes that varied from the mean by greater than two standard deviations were excluded from the analysis. In addition, we performed subgroup analyses to calculate adjusted odds ratios (ORs) with 95% confidence intervals (CIs) for race and insurance status.
Results
Demographic data (Table 1) demonstrate a nearly significant difference in the distribution of race pre-pandemic compared with during the pandemic. We noted a significant increase in White patients and a significant reduction in Asian patients seen during the pandemic lockdown. Compared with White patients, Black patients were less likely to have visits during the pandemic OR: 0.82 (95% CI: 0.34–1.97) (Fig. 1). Compared with White patients, Hispanic and Asian patients were also less likely to have telemedicine visits during the pandemic OR: 0.68 (95% CI: 0.25–1.86) and OR: 0.18 (95% CI: 0.06–0.56) (Fig. 1), respectively. Median household income of patients seen during the pandemic was significantly greater than before the pandemic (Fig. 2).
Fig. 1. Forest plot of odds ratios for telemedicine visit during pandemic. Patients had greater odds of being female, less likely to have HMO insurance coverage, less likely to be Hispanic, significantly less likely to be Asian, and less likely to be Black during the start of the pandemic versus pre-pandemic. CI, confidence interval; HMO, health maintenance organization; PPO, preferred provider organizations.
Fig. 2. Box-and-whisker plot of median household income pre-pandemic versus during-pandemic. The left box and whisker plot represent the pre-pandemic distribution of income, whereas the right plot represents the post-pandemic distribution. The X represents the mean.
| PRE-COVID-19 LOCKDOWN (N = 94), N (%) | DURING THE COVID-19 LOCKDOWN (N = 67), N (%) | P | |
|---|---|---|---|
| Race | 0.05211 | ||
| Black | 15 (16.0) | 12 (17.9) | 0.7414 |
| Hispanic | 12 (12.8) | 8 (11.9) | 0.87288 |
| Asian | 23 (24.5) | 4 (6.0) | 0.00194* |
| White | 41 (43.6) | 40 (59.7) | 0.04444* |
| Unknown | 1 (1.0) | 2 (3.0) | 0.37346 |
| Other | 2 (2.1) | 1 (1.5) | 0.77182 |
| Total | 94 | 67 | |
| Age, mean (SD) | 8.38 (5.32) | 7.43 (6.18) | 0.2983 |
| Gender | 0.4721 | ||
| Male | 43 (45.2) | 27 (40.3) | 0.4902 |
| Female | 51 (52.2) | 40 (59.7) | 0.4902 |
| Insurance status | 0.06010 | ||
| PPO | 74 (77.7) | 63 (94.0) | 0.00714* |
| HMO | 11 (11.7) | 2 (3.0) | 0.0455* |
| Self-pay | 3 (3.2) | 2 (3.0) | 0.9442 |
| Unknown | 5 (5.3) | 0 (0) | 0.05486 |
| Public | 1 (1.1) | 0 (0) | 0.8469 |
| No-shows | 16.1% (18 of 112) | 4.3% (3 of 70) | 0.01552* |
| Median household income, mean (SD) | $85,968.35 (38,149.37) | $97,408.59 (33,890.05) | 0.026697* |
Patients during the pandemic were more likely to be female, although this was not significant OR: 1.25 (95% CI: 0.66–2.36) (Fig. 1). There was a nearly significant statistical difference in the distribution of insurance status for patients seen before the pandemic compared with patients seen during the pandemic. Compared with before the pandemic, patients were significantly less likely to have health maintenance organization (HMO) insurance coverage OR: 0.21 (95% CI: 0.05–0.99) (Fig. 1), and significantly more likely to have insurance with preferred provider organizations (PPO). Most conditions were similarly represented before and during the lockdown, except for a reduction in warts and contact dermatitis during the lockdown. There were significantly fewer no-shows during the lockdown than pre-pandemic.
Discussion
The COVID-19 pandemic has created significant socioeconomic disparities for marginalized populations,24 disproportionately impacting people of color. This study aimed to identify differences in patient demographics at a skin of color pediatric dermatology practice in NYC before and during the pandemic.
We noted a nearly significant difference in racial and ethnicity distribution of patients who completed appointments before the pandemic compared with during the pandemic. We did not note large differences in the proportion of Black and Hispanic patients seen at the practice before and during the pandemic (16% vs. 17.9% for Black patients and 12.8% vs. 11.9% for Hispanic patients). Although some studies suggest that Black and Hispanic patients are less likely to utilize telemedicine,25,26 other studies found that Black race and Latinx ethnicity were associated with increased telemedicine visits.27 Our specialty practice has a high minority patient volume, potentially accounting for similar proportions of Black and Hispanic patients that were seen before and during the pandemic.
In addition, factors such as ease of access, lack of transportation issues, and fewer lost hours from school and work may have countered effects such as language barriers, cost of technology, and travel distance that have been found to discourage telemedicine use in Black and Hispanic populations.28–30 Despite lower rates of Black and Hispanic patients seen during the pandemic in other clinics, our experience may further attest to the advantage of specialty skin of color care in helping patients develop trusting relationships that persist even despite logistical challenges.
We also noted a statistically significant decrease in Asian patients seen before the pandemic compared with during the pandemic (24.5% vs. 6.0%). This finding aligns with other studies that have found lower use of telemedicine among Asian populations.27 Adusumalli et al suggest challenges in access to care, patient-perceived provider biases, language barriers, and poor doctor–patient relationships may all contribute to lower telemedicine utilization among Asian patients. Furthermore, another potential contributing factor to lower rates of telemedicine utilization among Asian patients includes the anti-Asian sentiment and racism that emerged after the COVID-19 pandemic, which may have distanced made Asian patients feel isolated.31–33
We noted a significantly greater proportion of White patients seen during the pandemic compared with before the pandemic (59.7% vs. 43.6%). This aligns with findings from other studies that have found greater uptake of telemedicine in White populations.25,26
There was a significantly greater proportion of patients with private/PPO insurance coverage seen during the pandemic compared with before the pandemic (94% vs. 77.7%) and a significantly smaller proportion of patients using HMO insurance during the pandemic compared with before the pandemic (3.0% compared with 11.7%). This is in line with other studies that have found lower rates of telemedicine utilization in public compared with commercial insurance.19,27,34 There is also much evidence that better insurance coverage is associated with increased health care utilization.35,36 In addition, the need for referrals may have inhibited telehealth delivery.
We also noted a significantly higher median household income by zip code for patients seen during the pandemic compared with patients before the pandemic ($85,968.35 vs. $97,408.59). This finding is also in line with several other studies that have found greater telemedicine utilization among those residing in higher-income areas.19,26,27
We found there were six times fewer no-shows during the pandemic compared with before the pandemic. This may speak to the convenience of telehealth for families. Logistical challenges that were exacerbated for in-person appointments may have been overcome by the ease of access to an online platform. This finding was recapitulated in other studies that found lower rates of missed appointments when using telehealth compared with in-person visits.37 Regarding differences in presenting conditions, we found that most conditions were similarly represented before and during the lockdown, except for a reduction in warts and contact dermatitis during the pandemic (Table 2). These deviations may relate to a lack of ability to provide in-person cryotherapy and patch testing, respectively. Furthermore, we found no statistically significant differences in the distribution of conditions presented during these 2 months, suggesting stability of presentations despite both the COVID-19 pandemic and shift to telehealth.
| NAME OF CONDITION | PRE-COVID-19 LOCKDOWN (% OF TOTAL CONDITIONS), N (%) | DURING COVID-19 LOCKDOWN (% OF TOTAL CONDITIONS), N (%) |
|---|---|---|
| Acne | 14 (11.7) | 8 (9.1) |
| Alopecia | 4 (3.3) | 3 (3.4) |
| Atopic dermatitis | 25 (20.8) | 21 (24.1) |
| Café au lait | 1 (0.8) | 0 (0) |
| Contact dermatitis | 9 (7.5) | 4 (4.6) |
| Diaper dermatitis | 1 (0.8) | 1 (1.1) |
| Eczema herpeticum | 0 (0) | 1 (1.1) |
| Hyperpigmentation | 0 (0) | 1 (1.1) |
| ILVEN | 1 (0.8) | 0 (0) |
| Infantile hemangioma | 8 (6.7) | 6 (6.9) |
| Interface dermatitis | 0 (0) | 1 (1.1) |
| Juvenile plantar dermatosis | 1 (0.8) | 0 (0) |
| KP | 0 (0) | 3 (3.4) |
| Lichen striatus | 2 (1.7) | 0 (0) |
| Melanocytic nevi | 5 (4.2) | 2 (2.3) |
| Molluscum | 8 (6.7) | 7 (8.0) |
| Molluscum dermatitis | 4 (3.3) | 5 (5.7) |
| Nevus sebaceus | 0 (0) | 1 (1.1) |
| Perineal infective dermatosis | 1 (0.8) | 0 (0) |
| Periorificial dermatitis | 1 (0.8) | 2 (2.3) |
| PG | 0 (0) | 1 (1.1) |
| Pigmentary mosaicism | 2 (1.7) | 0 (0) |
| Pilomatricoma | 1 (0.8) | 0 (0) |
| Pityriasis alba | 1 (0.8) | 0 (0) |
| Pityrosporum folliculitis | 0 (0) | 2 (2.3) |
| PRP | 0 (0) | 1 (1.1) |
| Psoriasis | 2 (1.7) | 2 (2.2) |
| Seborrheic dermatitis | 7 (5.8) | 7 (8.0) |
| T capitis/corporis/pedis | 4 (3.3) | 2 (2.3) |
| Tinea versicolor | 1 (0.8) | 0 (0) |
| Trichotillomania | 1 (0.8) | 0 (0) |
| Urticaria | 0 (0) | 1 (1.1) |
| Viral exanthema | 1 (0.8) | 0 (0) |
| Vitiligo | 4 (3.3) | 1 (1.1) |
| Warts | 11 (9.2) | 3 (3.4) |
| Xerosis | 0 (0) | 1 (1.1) |
This study has several important limitations. First, our clinic focuses on skin of color in a major urban city and may not reflect the demographic shifts of pediatric dermatology clinics nationwide. Furthermore, our clinic typically sees privately insured patients, and this may not reflect the disparities and challenges with regards to access to care that may occur for pediatric dermatology patients who receive public assistance or who may not have the technology or connectivity to execute telehealth visits successfully.
The COVID-19 pandemic has underscored long-standing disparities in access to specialty care. In our clinic, we have found that certain discrepancies in demographics have aligned with findings documented in other studies. A greater representation of White individuals, patients with private insurance, and trends toward those with higher household incomes highlight potential roles for racial and socioeconomic disparities. The barriers to access to care for Asian patients during the pandemic need to be further explored.
As a group we believe there are steps that should be taken to ensure more inclusivity. In particular, we think that qualitative exploration of attitudes of patient subpopulations and their referring doctors through individual survey may delineate reasons for differences in telehealth participation. We recommend a sixfold plan of improving access to teledermatology for all children:
| 1. |
Training referring providers and community organizations on the availability of telehealth services. This would help underserved populations gain knowledge of telehealth availability as a new technology. |
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| 2. |
Offering services that are friendly to all races and ethnicities, including translation of documents and visits, and educational information in multiple languages. |
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| 3. |
Availability of tablets and other devices for telehealth at community centers could help underserved populations access devices. |
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| 4. |
Greater availability of training resources for physicians in pictorial diagnosis of patients of many races and ethnicities. Although disparity in images in dermatology has been reported, the Pediatric Dermatology Research Alliance has recommended specific curriculum for educating students, including currently available resources for information and pictures.38,39,40 |
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| 5. |
The inclusion of telehealth services as an integrated part of daily practice may create a greater level of comfort for patients during times of true crisis. |
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| 6. |
Accumulation of inexpensive online resources to help patients access medications, including pharmacies that ship and articles written at an average reading level. |
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In addition, we believe inclusive advertisement of available services using a multicultural approach with photographs of individuals of different races and ethnicities as well as translation of advertisements into other languages (e.g., Spanish and Mandarin) may enhance participation by populations who may not have English proficiency.
Overall, we believe that the COVID-19 pandemic highlighted the disparity underserved patients have in accessing newer technology in health care and the need to explore attitudes of different racial and ethnic groups toward telehealth versus in-person care, which is a barrier not yet explored.
Disclosure Statement
No competing financial interests exist.
Funding Information
No funding was received for this article.
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