Racial and Ethnic Disparities in Outpatient Treatment of COVID-19 ― United States, January–July 2022

In December 2021 and early 2022, four medications received emergency use authorization (EUA) by the Food and Drug Administration for outpatient treatment of mild-to-moderate COVID-19 in patients who are at high risk for progressing to severe disease; these included nirmatrelvir/ritonavir (Paxlovid) and molnupiravir (Lagevrio) (both oral antivirals), expanded use of remdesivir (Veklury; an intraveneous antiviral), and bebtelovimab (a monoclonal antibody [mAb]).* Reports have documented disparities in mAb treatment by race and ethnicity (1) and in oral antiviral treatment by zip code–level social vulnerability (2); however, limited data are available on racial and ethnic disparities in oral antiviral treatment.^† Using electronic health record (EHR) data from 692,570 COVID-19 patients aged ≥20 years who sought medical care during January–July 2022, treatment with Paxlovid, Lagevrio, Veklury, and mAbs was assessed by race and ethnicity, overall and among high-risk patient groups. During 2022, the percentage of COVID-19 patients seeking medical care who were treated with Paxlovid increased from 0.6% in January to 20.2% in April and 34.3% in July; the other three medications were used less frequently (0.7%–5.0% in July). During April–July 2022, when Paxlovid use was highest, compared with White patients, Black or African American (Black) patients were prescribed Paxlovid 35.8% less often, multiple or other race patients 24.9% less often, American Indian or Alaska Native and Native Hawaiian or other Pacific Islander (AIAN/NHOPI) patients 23.1% less often, and Asian patients 19.4% less often; Hispanic patients were prescribed Paxlovid 29.9% less often than non-Hispanic patients. Racial and ethnic disparities in Paxlovid treatment were generally somewhat higher among patients at high risk for severe COVID-19, including those aged ≥50 years and those who were immunocompromised. The expansion of programs focused on equitable awareness of and access to outpatient COVID-19 treatments, as well as COVID-19 vaccination, including updated bivalent booster doses, can help protect persons most at risk for severe illness and facilitate equitable health outcomes.

This study used EHR data from 30 sites (each representing one or more health care systems) participating in PCORnet, the National Patient-Centered Clinical Research Network (PCORnet).^§ The PCORnet distributed data infrastructure was queried^¶ and returned aggregate demographic and clinical data for all COVID-19 patients and those treated with Paxlovid, Lagevrio, Veklury,** or mAbs^†† during January–July 2022. COVID-19 patients were persons aged ≥20 years who sought medical care and had EHR documentation of a positive SARS-CoV-2 viral test result, an International Classification of Diseases, Tenth Revision, Clinical Modification (ICD-10-CM) diagnostic code for COVID-19 (U07.1 and U07.2), or treatment with an assessed COVID-19 medication.^§§ Treated COVID-19 patients had EHR documentation of a Paxlovid or Lagevrio prescription or Veklury or mAb administration.^¶¶ High-risk patient groups were defined based on age (50–64, 65–79, and ≥80 years) and immunocompromise (previous organ transplant, active cancer treatment, corticosteroid use, and immunosuppressive medication use).***

The percentage of COVID-19 patients treated with each medication was calculated by age group, sex (male and female), race (White, Black, Asian, AIAN/NHOPI, multiple or other race, and missing), ethnicity (Hispanic, non-Hispanic, and other or missing),^††† immunocompromise, and underlying medical conditions.^§§§ Disparities were assessed using absolute differences (percentage treated in the racial or ethnic minority group minus the percentage treated in the majority group [i.e., White race and non-Hispanic ethnicity, respectively]) and relative differences (absolute difference divided by the percentage treated in the majority group). Statistical differences in the percentage treated by race and ethnicity were quantified using Pearson’s chi-square tests comparing patients in the minority groups with those in the majority group. Disparities in percentage treated overall and by age group were assessed during April–July 2022, when Paxlovid use was highest; disparities by immunocompromise could only be assessed during January–July 2022 because of restrictions in the PCORnet distributed data infrastructure. P-values <0.05 were considered statistically significant. This activity was reviewed by CDC and conducted consistent with applicable federal law and CDC policy.^¶¶¶

During January–July 2022, a total of 692,570 COVID-19 patients aged ≥20 years were identified.**** Among these, 22.2% were aged ≥65 years, 60.5% were female, 68.2% were White, and 79.6% were non-Hispanic (Table 1). Overall, 11.7% of COVID-19 patients were treated with Paxlovid, 2.7% with mAbs, 1.0% with Lagevrio, and 0.7% with Veklury. The percentage treated with Paxlovid exceeded the overall average of 11.7% for the following patient groups: aged ≥50 years, White, non-Hispanic,^†††† active cancer treatment, corticosteroid use, immunosuppressive medication use, and presence of underlying medical conditions (except chronic kidney disease, cirrhosis, congestive heart failure, and dementia). mAb treatment was more common than Paxlovid treatment among patients with a previous organ transplant.

During 2022, the percentage of COVID-19 patients treated with Paxlovid increased from 0.6% in January to 20.2% in April and 34.0% in July (Supplementary Figure, https://stacks.cdc.gov/view/cdc/121864). Treatment with other medications occurred less frequently and varied less during the study period (mAbs [monthly range = 1.2%–5.0%], Lagevrio [0.4%–2.5%], and Veklury [0.6%–0.9%]). Racial and ethnic differences in monthly Paxlovid treatment were observed (Figure).

During April–July 2022, Paxlovid treatment among adults aged ≥20 years was 35.8% lower among Black patients (20.5% treated) than it was among White patients (31.9% treated) (Table 2). Paxlovid treatment was 24.9%, 23.1%, and 19.4% lower among multiple or other race, AIAN/NHOPI, and Asian patients, respectively, than among White patients, and 29.9% lower among Hispanic than among non-Hispanic patients. In age-stratified analyses, the percentage of patients aged 20–49, 50–64, 65–79, and ≥80 years who were prescribed Paxlovid was 20.9%, 34.3%, 39.9%, and 30.7%, respectively. Disparities for Black, multiple or other race, and Hispanic patients were present across all age strata; the largest relative difference (44.0%) was between Black and White patients aged 65–79 years.

Racial and ethnic disparities existed for treatment with other medications, but absolute differences were small, given the low treatment percentages. Racial and ethnic minority patients were treated with mAbs and Lagevrio less often than were White and non-Hispanic patients (Supplementary Table 1, https://stacks.cdc.gov/view/cdc/121865). AIAN/NHOPI, Asian, and Hispanic patients received Veklury less often than did White and non-Hispanic patients; Black patients received Veklury more often than White patients.

During January–July 2022, racial and ethnic disparities also existed for the four immunocompromised patient groups. In general, immunocompromised Black, multiple or other race, and Hispanic patients were treated with Paxlovid and mAbs less often than were immunocompromised White and non-Hispanic patients. Treatment differences between immunocompromised White and both AIAN/NHOPI and Asian patients were small or not statistically significant (Supplementary Table 2, https://stacks.cdc.gov/view/cdc/121865).

¹CDC COVID-19 Emergency Response Team; ²Department of Pediatrics, University of North Carolina School of Medicine, Chapel Hill, North Carolina; ³Louisiana Public Health Institute, New Orleans, Louisiana; ⁴Booz Allen Hamilton, Inc., McLean, Virginia; ⁵Office of Minority Health and Health Equity, CDC; ⁶Section of Pulmonary Diseases, Critical Care, and Environmental Medicine, Tulane University School of Medicine, New Orleans, Louisiana; ⁷Department of Population Medicine, Harvard Pilgrim Health Care Institute, Harvard Medical School, Boston, Massachusetts; ⁸Department of Medicine, Lewis Katz School of Medicine at Temple University, Philadelphia, Pennsylvania; ⁹OCHIN, Inc., Portland, Oregon; ¹⁰Center for Health Equity and Innovation, Cook County Health, Chicago, Illinois; ¹¹National Center for Immunization and Respiratory Diseases, CDC.

References

1. Wiltz JL, Feehan AK, Molinari NM, et al. Racial and ethnic disparities in receipt of medications for treatment of COVID-19—United States, March 2020–August 2021. MMWR Morb Mortal Wkly Rep 2022;71:96–102. https://doi.org/10.15585/mmwr.mm7103e1 PMID:35051133
2. Gold JAW, Kelleher J, Magid J, et al. Dispensing of oral antiviral drugs for treatment of COVID-19 by zip code–level social vulnerability—United States, December 23, 2021–May 21, 2022. MMWR Morb Mortal Wkly Rep 2022;71:825–9. https://doi.org/10.15585/mmwr.mm7125e1 PMID:35737571
3. Sullivan M, Perrine CG, Kelleher J, et al. Notes from the field: dispensing of oral antiviral drugs for treatment of COVID-19 and zip code-level social vulnerability—United States, December 23, 2021–August 28, 2022. MMWR Morb Mortal Wkly Rep 2022;71:1384–5.
4. Shepherd SM, Willis-Esqueda C, Paradies Y, Sivasubramaniam D, Sherwood J, Brockie T. Racial and cultural minority experiences and perceptions of health care provision in a mid-western region. Int J Equity Health 2018;17:33. https://doi.org/10.1186/s12939-018-0744-x PMID:29548328
5. FitzGerald C, Hurst S. Implicit bias in healthcare professionals: a systematic review. BMC Med Ethics 2017;18:19. https://doi.org/10.1186/s12910-017-0179-8 PMID:28249596
6. Rivera V, Aldridge MD, Ornstein K, Moody KA, Chun A. Racial and socioeconomic disparities in access to telehealth. J Am Geriatr Soc 2021;69:44–5. https://doi.org/10.1111/jgs.16904 PMID:33075143
7. Wu EL, Kumar RN, Moore WJ, et al. Disparities in COVID-19 monoclonal antibody delivery: a retrospective cohort study. J Gen Intern Med 2022;37:2505–13. https://doi.org/10.1007/s11606-022-07603-4 PMID:35469360
8. Chhibber A, Kharat A, Duong K, et al. Strategies to minimize inequity in COVID-19 vaccine access in the US: implications for future vaccine rollouts. Lancet Reg Health Am 2022;7:100138. https://doi.org/10.1016/j.lana.2021.100138 PMID:34901919
9. Mayfield CA, Sparling A, Hardeman G, et al. Development, implementation, and results from a COVID-19 messaging campaign to promote health care seeking behaviors among community clinic patients. J Community Health 2021;46:728–39. https://doi.org/10.1007/s10900-020-00939-0 PMID:33128160
10. Massetti GM, Jackson BR, Brooks JT, et al. Summary of guidance for minimizing the impact of COVID-19 on individual persons, communities, and health care systems—United States, August 2022. MMWR Morb Mortal Wkly Rep 2022;71:1057–64. https://doi.org/10.15585/mmwr.mm7133e1 PMID:35980866

Abbreviations: AIAN/NHOPI = American Indian or Alaska Native and Native Hawaiian or other Pacific Islander; BMI = body mass index; ICD-10-CM = International Classification of Diseases, Tenth Revision, Clinical Modification; mAbs = monoclonal antibodies; NC = not calculated.
* COVID-19 patients were identified by a positive SARS-CoV-2 viral test result, an ICD-10-CM diagnostic code for COVID-19 (U07.1 and U07.2), or treatment with a COVID-19 medication (Paxlovid, Lagevrio, mAbs, or Veklury).
^† Patients were considered treated if they were prescribed Paxlovid or Lagevrio or administered Veklury or mAbs.
^§ Receipt of any outpatient treatment was not calculated but can be estimated by summing the percentage of COVID-19 patients treated across the four medication types. This will overestimate receipt of any outpatient treatment because treatment groups were not mutually exclusive. For example, among 81,373 patients prescribed Paxlovid, 579 (0.7%) were also treated with mAbs (491 bebtelovimab), 619 (0.8%) with Lagevrio, and 203 (0.2%) with Veklury.
^¶ Among 7,631 patients of AIAN/NHOPI race, 67% were AIAN and 33% were NHOPI.
**Among 38,447 patients of multiple or other race, 19% were multiple race and 81% were other race. Approximately 58% of multiple and other race patients were of Hispanic ethnicity.
^†† Patients with immunocompromise were identified as follows: previous organ transplant (one or more ICD-10-CM codes at any time preceding COVID-19); active cancer treatment (three or more ICD-10-CM codes for cancer during the 6 months preceding COVID-19); corticosteroid use (two or more prescriptions during the year preceding COVID-19); and immunosuppressive medication use (one or more prescriptions for or administrations of a noncorticosteroid immunosuppressive medication during the year preceding COVID-19).
^§§ Some conditions can result in a contraindication to Paxlovid use or require treatment with medications that have drug-drug interactions resulting in inability to use Paxlovid. https://www.covid19treatmentguidelines.nih.gov/therapies/antiviral-therapy/ritonavir-boosted-nirmatrelvir–paxlovid-/paxlovid-drug-drug-interactions/
^¶¶ Presence of an underlying medical condition required the presence of at least two ICD-10-CM codes for that condition during the 3 years preceding COVID-19. A subset of underlying medical conditions that increase risk for severe COVID-19 outcomes was assessed. https://www.cdc.gov/coronavirus/2019-ncov/hcp/clinical-care/underlyingconditions.html

FIGURE. Monthly percentage of COVID-19 patients aged ≥20 years prescribed Paxlovid,* by race and ethnicity^† — PCORnet, the National Patient-Centered Clinical Research Network, 30 U.S. sites, January–July 2022

Abbreviations: AIAN/NHOPI = American Indian or Alaska Native and Native Hawaiian or other Pacific Islander; ICD-10-CM = International Classification of Diseases, Tenth Revision, Clinical Modification; PCORnet = PCORnet, the National Patient-Centered Clinical Research Network.

* COVID-19 patients were identified by a positive SARS-CoV-2 viral test result, an ICD-10-CM diagnostic code for COVID-19 (U07.1 and U07.2), or treatment with a COVID-19 medication (Paxlovid, Lagevrio, monoclonal antibodies, or Veklury). Patients were considered treated if they were prescribed Paxlovid.

^† Race and ethnicity were assessed as separate variables because the PCORnet distributed query statistical program does not allow for assessment of combined race and ethnicity by month. Among 7,631 patients of AIAN/NHOPI race, 67% were AIAN and 33% were NHOPI. Among 38,447 patients of multiple or other race, 19% were multiple race and 81% were other race; 58% of multiple and other race patients were of Hispanic ethnicity.

Abbreviations: AIAN/NHOPI = American Indian or Alaska Native and Native Hawaiian or other Pacific Islander; ICD-10-CM = International Classification of Diseases, Tenth Revision, Clinical Modification; NC = not calculated; PCORnet = PCORnet, the National Patient-Centered Clinical Research Network; Ref = referent group.
* COVID-19 patients were identified by a positive SARS-CoV-2 viral test result, an ICD-10-CM diagnostic code for COVID-19 (U07.1 and U07.2), or treatment with a COVID-19 medication (Paxlovid, Lagevrio, monoclonal antibodies, or Veklury). Patients were considered treated if they were prescribed Paxlovid.
^† Race and ethnicity were assessed as separate variables because the PCORnet distributed query statistical program does not allow for assessment of combined race and ethnicity by month or for shorter periods (April–July 2022). Approximately 58% of multiple and other race patients were of Hispanic ethnicity.
^§ Number of patients with missing race and missing ethnicity are not shown, but can be calculated by subtracting the number of patients with known race or ethnicity from the total number of patients.
^¶ Pearson’s chi-square tests comparing percentage treated in the minority racial and ethnic groups with percentage treated in the majority or referent group (i.e., White race and non-Hispanic ethnicity).
** Absolute difference was calculated as the percentage treated in the minority racial and ethnic group minus the percentage treated in the majority or referent group (i.e., percentage point difference). Relative difference was calculated as the absolute difference divided by the percentage treated in the majority or referent group.