Pre-COVID-19 Disparities in Telemedicine Use Among Louisiana Medicaid Beneficiaries
Background
The COVID-19 pandemic led to a rapid expansion of telemedicine service delivery in the United States.1,2 Before the pandemic, telemedicine use among Medicaid beneficiaries was uncommon, although limited data suggest that its use was increasing in some states.3–5 Telemedicine presents a potential means to reduce disparities in care access.1,2 However, studies have documented lower use rates for racial and ethnic minorities, rural residents, and older populations.1,5–7
Louisiana provides a setting well suited for studying disparities in telemedicine use in Medicaid. Louisiana ranks 49th among states in real median household income, and as a rare southern state to expand Medicaid under the Affordable Care Act, more than a third of its nonelderly population is covered by Medicaid.8,9 Although Louisiana Medicaid did not reimburse for telemedicine services at parity with in-person visits before the pandemic, laws and policies on telemedicine use were in line with those in most other states.10
The first confirmed case of COVID-19 in Louisiana was reported on March 9, 2020.11 By late March, Louisiana was experiencing the fastest growth rate of COVID-19 infections in the world. On March 18, 2020, the Louisiana Department of Health (LDH) directed providers to postpone, as medically reasonable, any care for 30 days.12 LDH then encouraged providers to deliver services using telemedicine when appropriate and eased Medicaid billing restrictions on the provision of telemedicine services.13–15
In this study, we contribute to the limited evidence base on pre-COVID disparities in telemedicine use by examining trends in telemedicine use by race (Black vs. White), geography (rural vs. urban), and age among Medicaid beneficiaries in Louisiana. Our goal is to provide a descriptive analysis of pre-COVID disparities in telemedicine use so that we can begin to understand the impacts of COVID-19 and the widespread transition to telemedicine service provision on access to care for vulnerable populations. To our knowledge, this represents the first analysis of race, age, and geographic disparities in telemedicine use among a Medicaid population in the immediate run-up to the COVID-19 pandemic.
Methods
Our data come from the complete Medicaid claims for the state of Louisiana from January 2018 through February 2020. The data allow us to identify claims for services rendered through telemedicine and to compare telemedicine claim volume by race, age, and urban versus rural county of residence. Our sample included fee-for-service and managed care Medicaid beneficiaries. We used rural–urban continuum codes from the Area Health Resources Files to distinguish beneficiaries residing in big metropolitan, small metropolitan, and nonmetropolitan (rural) areas. Beneficiaries self-identified their age and race at the time of enrollment.
We selected the telehealth visits using the place of service code that indicated a telehealth visit (02) and/or procedure code modifiers (GT, GQ, and 95). The evaluation and management (E&M) services were selected using the Current Procedural Terminology (CPT) codes: 99201-99205, 90211-99215, and 99241-99245. We restricted our sample to claims for E&M services to focus our analysis on services with a high degree of substitution between in-person and telemedicine modalities. We also restricted our sample to those <65 years of age and with Medicaid as a primary payer to omit dual-eligible.
We aggregated claims to the weekly level, divided the number of weekly telemedicine claims by total weekly claims, and multiplied this ratio by 1,000. When comparing telemedicine use across subgroups, we calculated a relative ratio of telemedicine use as the share of telemedicine claims for one group divided by the share of telemedicine claims for the other group. We then conducted two-sample t-tests to gauge the statistical significance of differences in mean use rates of telemedicine between subgroups. This analysis occurred in spring 2021. Our study was classified as exempt research by the Tulane Institutional Review Board.
Results
Figure 1 plots telemedicine use for evaluation and management (E&M) services for Louisiana Medicaid beneficiaries by race. On average, from January 2018 through February 2020, 3.40 of every 1,000 E&M claims represented a service delivered through telemedicine (Appendix Table A1). Figure 1 indicates that from January 2018 through December 2018, White beneficiaries used telemedicine at a rate of 3.43 claims per 1,000 E&M claims compared with 1.78 telemedicine claims per 1,000 E&M claims for Black beneficiaries and 1.70 telemedicine claims per 1,000 E&M claims for Hispanic beneficiaries; relative ratios of 1.92 (t-stat = 14.90, p-value <0.001) and 2.02 (t-stat = 14.52, p-value <0.001), respectively.
By 2019, the gap had narrowed with the relative ratio between White and Black telemedicine use at 1.58 (t-stat = 11.27, p-value <0.001) and the relative ratio between White and Hispanic telemedicine use at 1.80 (t-stat = 13.44, p-value <0.001). The gap continued to narrow through the first 2 months of 2020 to 1.36 (t-stat = 4.93 p-value = 0.002) for White compared with Black beneficiaries and 1.53 (t-stat = 5.16, p-value = 0.001) for White compared with Hispanic beneficiaries.
Figure 2 plots telemedicine use for Louisiana Medicaid beneficiaries living in rural and urban counties. On average, rural beneficiaries used telemedicine services at a rate of 2.94 claims per 1,000 E&M claims in 2018 compared with urban beneficiaries use rate of 2.32 telemedicine claims per 1,000 E&M claims; a relative ratio of 1.27 (t-stat = 5.40, p-value <0.001). By early 2020, the relative ratio between rural and urban was 0.88 (t-stat = 2.01, p-value = 0.06), indicating similar telemedicine use rates between the two groups.
Figures 3 and 4 plot telemedicine use rates by age for Medicaid beneficiaries in Louisiana. We divided age ranges into two categories for children (aged 0–5 years and 6–17 years) and two categories for adults (aged 18–49 years and 50–64 years). Before the COVID-19 pandemic, Medicaid beneficiaries aged 0–5 years had the lowest telemedicine use rates at 0.64 telemedicine claims per 1,000 E&M claims from January 2018 through February 2020. Alternatively, children and adolescents aged 6–17 had the highest telemedicine use rates of any age group at 5.07 telemedicine claims per 1,000 E&M claims. Both age groups exhibited substantial growth in telemedicine use over the prepandemic sample period.
Figure 4 indicates that adults between the ages of 18 and 49 years and 50 and 64 years had similar telemedicine use rates from January 2018 through mid-2019. In mid-2019 use rates by age group began to diverge. From January 2018 through June 2019, the relative ratio between adults under age 50 years and adults between the ages of 50 and 64 years was 0.92 (t-stat = 2.22, p-value = 0.03). However, from July 2019 through February 2020, the gap in telemedicine use between younger and older adults had grown to 1.16 (t-stat = 2.83, p-value = 0.006).
Discussion
We found that telemedicine use among Louisiana Medicaid beneficiaries for E&M services was low before the pandemic; but in most cases, we documented growth in telemedicine use rates over time. The findings are similar to a recent study that found lower use among commercially insured patients who were older, had more comorbidities, lived in rural areas, and had lower median household incomes.13 Our study is the first, to our knowledge, to assess disparities among a Medicaid population and by race and ethnicity in telemedicine use leading up to the weeks before most states implemented shelter-in-place orders.14
White Medicaid beneficiaries were nearly twice as likely to use telemedicine services in 2018 compared with Black beneficiaries and, although this gap narrowed somewhat over time, the disparity persisted through the first 2 months of 2020. Generally, racial disparities in health care use and access have been linked to structural racism (e.g., social segregation).15,16
Children under the age of 5 years were the least likely age group to use telemedicine services before the pandemic and exhibited little growth in their use over our sample period. Among adult Medicaid beneficiaries, we saw similar telemedicine use rates by age through 2018 and into 2019, but by mid-2019 a disparity in use emerged between adults under age 50 years and those between the ages of 50 and 64 years. We also found children and adolescents between the ages of 6 and 17 years used telemedicine at a higher rate than any other age group, although all age groups experienced growth in telemedicine use over the sample period.
Finally, although telemedicine use was higher among beneficiaries living in rural compared with urban areas through 2018 and into 2019, we found convergence in telemedicine use between Louisiana Medicaid beneficiaries living in rural and urban counties, such that by early 2020, there was no statistical difference in rates of telemedicine use by rural and urban status. A recent study that assessed the impact of the pandemic in rural and remote settings found similar findings.17
Conclusions
The pandemic led to major disruptions in E&M care that may have disproportionately impacted subgroups of patients, which could exacerbate existing disparities in disease burden.18 Moving forward, our study provides a baseline from which to assess the impacts of the widespread expansion of telemedicine use due to COVID-19 on disparities in care access for vulnerable populations. Although our analysis is limited in scope and examines pre-COVID telemedicine use among Medicaid beneficiaries in a single state, we believe our findings will prove valuable to policymakers and stakeholders concerned with equity in access to care.
Disclosure Statement
B.W. is also employed by ConcertAI for unrelated work. There are no other potential conflict of interest to report.
Funding Information
This research was funded by The Commonwealth Fund (grant no. 20202883d).
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Appendix
E&M CLAIMS | E&M TELEMEDICINE CLAIMS | BENEFICIARIES | RATIO PER 1,000 CLAIMS | p-VALUE OF DIFFERENCE | |
---|---|---|---|---|---|
Average weekly claims | 104,135.80 | 353.98 | 1,330,845 | 3.40 | — |
Race/ethnicity | |||||
Black | 47,259.49 | 124.55 | 673,805 | 2.64 | <0.001 |
Hispanic | 9,285.77 | 22.10 | 128,245 | 2.38 | <0.001 |
White | 47,590.52 | 207.33 | 528,796 | 4.36 | — |
Geography | |||||
Rural | 35,352.45 | 128.15 | 405,806 | 3.62 | 0.024 |
Urban | 68,783.33 | 225.83 | 925,039 | 3.28 | — |
Age | |||||
0–5 | 18,180.73 | 11.68 | 218,119 | 0.64 | <0.001 |
6–17 | 28,798.38 | 146.12 | 433,379 | 5.07 | <0.001 |
18–49 | 41,007.41 | 141.11 | 529,389 | 3.44 | — |
50–64 | 16,149.26 | 55.08 | 149,959 | 3.41 | 0.80 |