The role of increasing synchronous telehealth use during the COVID-19 pandemic on disparities in access to healthcare: A systematic review

Abstract

Introduction

The COVID-19 public health emergency led to an unprecedented rapid increase in telehealth use, but the role of telehealth in reducing disparities in access to care has been questioned. The objective of this study was to conduct a systematic review to summarize the available evidence on how telehealth during the COVID-19 pandemic was associated with telehealth utilization for minority groups and its role in health disparities.

Methods

We conducted a systematic review focused on health equity and access to care by searching for interventional and observational studies using the following four search domains: telehealth, COVID-19, health equity, and access to care. We searched PubMed, Embase, Cochrane CENTRAL, CINAHL, telehealth.hhs.gov, and the Rural Health Research Gateway, and included any study that reported quantitative results with a control group.

Results

Our initial search yielded 1970 studies, and we included 48 in our final review. The most common dimensions of health equity studied were race/ethnicity, rurality, insurance status, language, and socioeconomic status, and the telehealth applications studied were diverse. Included studies had a moderate risk of bias. In aggregate, most studies reported increased telehealth use during the pandemic, with the greatest increase in non-minority populations, including White, younger, English-speaking people from urban areas.

Discussion

We found that despite rapid adoption and increased telehealth use during the public health emergency, telehealth did not reduce existing disparities in access to care. We recommend that future work measuring the impact of telehealth focus on equity so that features of telehealth innovation can reduce disparities in health outcomes.

Keywords

Telemedicine accessibility equity‌COVID-19 healthcare disparities ethnicity rural population systematic review

Introduction

The COVID-19 public health emergency led to an unprecedented increase in telehealth use as a way to maintain healthcare access while limiting the spread of communicable diseases.^1,2 In the US, both federal and commercial payors increased reimbursable telehealth services, and additional licensure and policy flexibilities, along with decreased in-person service volumes, making it easier for healthcare providers to provide telehealth.^3–7 Over 53 million medical visits were provided to fee-for-service Medicare beneficiaries using telehealth in 2020, which represented a 60-fold increase from 2019, and telehealth use in 2021 remained above pre-pandemic levels.^8,9 A systematic review from 2023 showed increased telehealth use, especially for those without complex clinical conditions and with good access to healthcare.¹⁰ Despite efforts to maintain healthcare access, however, 41% of US adults avoided receiving healthcare because of concerns related to COVID-19.¹¹

COVID-19 highlighted the importance of minority status in health outcomes, and a systematic review and meta-analysis published in 2021 reported higher COVID-19 positivity and disease severity among racial and ethnic minority groups and those in regions with a high area deprivation index.¹² Telehealth has long been hypothesized to be a method of improving access to healthcare that may reduce disparities for minority groups, who have long been afflicted by worse health outcomes.^13–15 Because telehealth reduces barriers of travel time, geographic constraints of healthcare access, and even language and cultural barriers, it may provide a more patient-centric way of providing healthcare. Minority groups are more represented in Medically Underserved Areas, highlighting the role that telehealth could play in leveling access between high-access and low-access regions—especially for specialty care. Medicare policy has enabled telehealth access for those in rural communities because of these recognized barriers, but rural disparities persist.^16,17 These data in aggregate highlight the importance of understanding how a shift to telehealth-enabled healthcare could affect disparities in health access and outcomes.

Unfortunately, a national survey conducted in 2021 and subsequently repeated suggested that significant disparities persist in the use of telehealth.^18,19 Prior work has highlighted the role of telehealth during the COVID-19 public health emergency in specific health conditions or care settings.^20–27 Other systematic reviews have focused on health equity, but they have used a narrower definition of sociodemographic characteristics to define disparities or they did not include a non-telehealth comparator control group.^28,29 The objective of this paper was to summarize the available evidence on how telehealth access and utilization changed for minority groups broadly across conditions and telehealth modalities during the COVID-19 public health emergency. We planned to complete this objective by conducting a systematic review, with a focus on health equity. Our secondary objective was to understand which dimensions of minority status were frequently measured in telehealth studies during the COVID-19 pandemic, and how variation in the experiences of these groups contributed to health equity.

Methods

We conducted a systematic review focused on how telehealth access and its use were associated with health equity during the COVID-19 public health emergency. We planned to conduct a meta-analysis if clinical and statistical heterogeneity was low, but we decided a priori to perform and report the systematic review alone if heterogeneity was high. Our review protocol was registered in PROSPERO (CRD42023392678),³⁰ and we reported our paper using the Preferred Reporting Items in Systematic Reviews and Meta-Analysis (PRISMA) guidelines.³¹

Data sources, search strategy, and selection criteria

In conjunction with a health sciences librarian trained in systematic review methodology (HH), we developed our search strategy using four domains: telehealth, COVID-19, health equity, and access to care. Each of those domains was expanded using a combination of subject headings and keywords, and we searched PubMed, Embase (Elsevier), Cochrane Central Register of Controlled Trials (Wiley), and CINAHL (EBSCO) with no publication date or language limits. Duplicate references were removed through automated and manual methods. We additionally conducted a gray literature search at telehealth.hhs.gov and the Rural Health Research Gateway, looking for relevant research products published after the beginning of the COVID-19 pandemic (i.e. 2020–2022).^32,33 All searches were conducted on 9 December 2022. The full search strategies are detailed in Supplemental Appendix A.

We included studies of interventional or observational designs that included an estimate of either telehealth access or utilization, stratified by socioeconomic, racial or ethnic, geographic, or other minority status. We included strata of insurance status as a minority status because of the myriad ways that insurance status affects healthcare use and availability, but we did not include disability status. We excluded case studies, editorials, narrative reviews, qualitative studies, or any study design that had no control group. The control group, however, could be a pre-pandemic control group or a concurrent control with different telehealth access, but studies estimating control group behavior without empirical, quantitative data were excluded. We included references in all languages, we included grey literature as it was identified in these databases, and we removed duplicate references using an automated algorithm.

For this review, we included telehealth studies in which the telehealth intervention included synchronous communication between a patient or care team and a telehealth provider to deliver healthcare. Those interventions could include video, audio-only, or real-time text communication for either inpatient or outpatient care, but they did not include store-and-forward, e-mail, or artificial intelligence-based interventions. Our outcomes included access to care and utilization, and we included papers with any specific measure of access or utilization (e.g. telehealth use, telehealth availability), as adjudicated by the independent reviewers. Our full search strategy is detailed in Supplemental Appendix A.

Study selection and data abstraction

After the database search was complete, two authors (LL and ST) performed title and abstract screening and independently determined whether the studies met our inclusion criteria. Then, all remaining references not excluded underwent a full-text review conducted independently by the same two authors, and final inclusion decisions were made. All disagreements were discussed and resolved either by consensus or by the determination of a third independent reviewer (JPV). After studies were selected, data from included references were manually abstracted by both independent reviewers (LL and ST) using a structured data collection form and disagreements were resolved by consensus.

Risk of bias assessment was performed by both reviewers using the Downs and Black assessment because that tool is applicable for both clinical trials and observational studies. This validated tool assessed the transparency, characteristics, and reporting of the study design, divided into sub-scores for reporting characteristics, external validity, and two separate internal validity domains.³⁴ Elements that were not present in a study design, including those that were not applicable, were scored as zero for being not present.

Meta-analysis

After the steering committee (NMM, JPV, and MMW) reviewed the results of the systematic review, they concluded that too much clinical heterogeneity (e.g. populations, settings, intervention, and context) existed and no statistical pooling or meta-analysis could be performed.

Results

Our search identified an initial yield of 1970 studies (Figure 1). The primary reasons for exclusion were the wrong study design or publication type, no clinical telehealth or underserved population, and the lack of an adequate comparator population. After applying the exclusion criteria, 48 studies were included in the systematic review.

Figure 1.

Preferred reporting items for systematic reviews and meta-analyses (PRISMA) 2020 flow diagram of included studies.

Overall study characteristics

All included papers were observational studies reporting the results from direct-to-consumer synchronous telehealth applications, and many (n = 16) considered audio-only and video telehealth separately. Clinical applications included cancer (n = 3), orthopedics (n = 2), gastroenterology (n = 4), surgical specialties (n = 2), ambulatory/outpatient conditions (n = 4), primary care (n = 3), mental health disorders (n = 4), HIV (n = 1), rheumatology (n = 2), headaches (n = 1), dermatology (n = 2), diabetes (n = 2), hypertensive pregnancy disorders (n = 1), pain (n = 1), infertility (n = 1), otolaryngology (n = 1), cardiology (n = 1), and hepatology (n = 2). Eleven studies did not specify a clinical condition of interest. All included studies reported on telehealth utilization, with other availability or clinical outcomes not frequently measured. All studies reported differential use by race/ethnicity, age, sex, language, insurance status, rurality, or socioeconomic status (Table 1).

Table 1.

Table of evidence.

Author, year	Study design	Setting	Time period	Conditions	Population	Exposure characteristics	Outcomes	Key findings
Ackroyd et al., 2021³⁵	Quasi-experimental study (pre/post)	Outpatient gynecologic oncology clinic	15 March 2019 to 15 June 2019; 15 March 2020 to 15 June 2020	Gynecologic cancers	Patients are seen at the outpatient gynecologic oncology center	Telemedicine (video and telephone)	Telemedicine utilization	Race and insurance status did not affect telemedicine utilization. When stratified by type of telemedicine utilized, disproportionate use of video videos by race was observed.
Annapragada et al., 2022³⁶	Quasi-experimental study (pre/post)	Academic orthopedic surgery department of a tertiary care academic center	Pre-pandemic control: 16 March 2019 to 30 May 2019; immediately preceding COVID-19 control: 1 January 2020 to 15 March 2020; pandemic period: 16 March 2020 to 13 May 2021	Orthopedic surgery	Patients are seen at the orthopedic surgery department	Telemedicine (video and telephone)	Telemedicine utilization (odds of being seen via telemedicine)	Patient race (Black vs. White) did not impact the odds of being seen through telemedicine during the pandemic. Among telemedicine appointments, Black patients were more likely to be seen by audio-only remote visit than White patients.
Bayudan et al., 2022³⁷	Quasi-experimental study (pre/post); single-center retrospective study	Ambulatory gastroenterology clinic	Pre-pandemic cohort: 1 January 2019 to 15 March 2020; pandemic cohort: 16 March 2020 to 1 June 2021	Ambulatory gastroenterology	Patients are seen at the ambulatory gastroenterology clinic	Telemedicine (video and telephone)	Telemedicine utilization (total clinical encounter visits)	Telemedicine led to significantly increased clinical encounters for English speakers, younger patients, and Latinx patients during the pandemic. Non-English speakers experienced a decrease in clinic visits.
Bharadwaj et al., 2022³⁸	Quasi-experimental study (pre/post)	Brigham and Women's Hospital	Five 3-month time periods in 2019; five 3-month time periods in 2020 (unspecified)	Surgical specialties	Patients with surgical specialty visits at Brigham and Women's Hospital	Telemedicine	Telemedicine utilization (proportion of virtual visits)	The usage of telehealth by Black patients and non-English speaking patients was lower than expected for the urology surgical specialty, specifically.
Bose et al., 2022³⁹	Quasi-experimental study (pre/post); retrospective study	Nationwide, Centers for Medicare and Medicaid Services	Pre-waiver: 1 January 2019 to 5 March 2020; post-waiver: 7 March 2020 to 31 March 2021	Outpatient conditions	Patients with at least one outpatient visit claim to Medicare	Telemedicine	Telemedicine utilization (proportion of outpatient visit claims)	People residing in the most disadvantaged neighborhoods were more likely to use telemedicine in the post-waiver period.
Cahan et al., 2022⁴⁰	Quasi-experimental study (pre/post); retrospective study	Stanford Children's Health (SCH)	March to June 2019; March to June 2020	Outpatient pediatric subspecialties (cardiology, nephrology, oncology, neurology, pulmonary, and endocrinology)	Outpatients scheduled to be seen by pediatric cardiology, nephrology, oncology, neurology, pulmonary, and endocrinology	Telehealth	Telehealth utilization (odds of completing a visit using telehealth)	Telehealth visit completion was not significantly different among those of differing insurance statuses and places of residence (high-income vs. low-income zip codes).
Cantor et al., 2021⁴¹	Quasi-experimental study (pre/post)	Nationwide, Castlight Health	Pre-COVID-19: 1 January 2019 to 13 March 2020; COVID-19: 14 March 2020 to 31 July 2020	None specified	Employer-based health plan beneficiaries	Telemedicine (video and telephone)	Incidence of telemedicine utilization	The study identified significant disparities in the use of telemedicine by patient age, county-level measures for poverty rate, and urbanicity.
Cao et al., 2021⁴²	Quasi-experimental study (pre/post)	Medicare Accountable Care Organization	Control cohort: April 2019 to September 2019; Study cohort: April 2020 to September 2020	Outpatient conditions	High-cost, high-need Medicare patients	Telehealth	Change in telehealth utilization	While high-cost high-need Medicare patients and those with disabilities were more likely to use telehealth, disparities in telehealth usage were identified among low-income, non-White, and rural Medicare beneficiaries.
Chakawa et al., 2021⁴³	Quasi-experimental study (pre/post)	Large, inner-city pediatric primary care clinic (medical home) within a large, regional children's hospital located in a moderate-sized metropolitan city in the Midwest U.S.	Pre-COVID-19: April 2019 to October 2019; COVID-19: April 2020 to October 2020	Pediatric integrated primary care	Children scheduled for in-person or telehealth-integrated primary care	Telehealth	Telehealth IPC consultation utilization	The study identified overall reduced attendance rates and reduced scheduling of telehealth IPC visits for Black children.
Connolly et al., 2022⁴⁴	Quasi-experimental study (pre/post)	Department of Veterans Affairs	Pre-COVID-19: 1 October 2017 to 10 March 2020; COVID-19: 11 March 2020 to 10 July 2020	Anxiety disorder, bipolar disorder, depression, posttraumatic stress disorder (PTSD), substance use disorder, or schizophrenia, and history of mental health hospitalization	Veterans seen at VA mental health outpatient clinics	Telemental health (video)	Telemental health utilization (yes/no)	Findings showed that older and lower-income patients were engaged with less telemental health care.
Cousins et al., 2022⁴⁵	Quasi-experimental study (pre/post); retrospective study	Large, academic medical center	Pre- and intra-pandemic: 1 July 2019 to 31 December 2020	Cancer	Patients seen for oncologic care at the academic medical center	Telemedicine	Telemedicine utilization (odds of video visit completion)	Patients from older age groups, those with minority backgrounds, and individuals from areas with less access to technology (high DDI) as well as those with Medicare or Medicaid insurance were less likely to use video visits.
Datta et al., 2022⁴⁶	Quasi-experimental study (pre/post); retrospective, cross-sectional study	Clinics owned and operated by the University of Nebraska Medical Center (UNMC) in Omaha, Nebraska	Pre-COVID-19 period: 16 March 2019 to 15 March 2020; COVID-19 period: 16 March 2020 to 15 March 2021	Primary and specialty care	Patients treated by primary and specialty care physicians in the UNMC clinics	Telehealth	Telehealth utilization (odds of having a telehealth visit)	Factors associated with lower odds of having a telehealth visit during the COVID-19 period for established patients included older age, self-pay or other insurance versus commercial insurance, Black or Asian versus White race, and non-English preferred languages.
Fischer et al., 2022⁴⁷	Survey study (pre/post)	American Life Panel Omnibus Survey	February 2019, May 2020, August 2020, March 2021	None specified	Probability-based sample of the US adult population ages 20 and older who were provided with internet-connected devices and were compensated for their participation in the survey	Telehealth (Audio and video)	Video telehealth utilization	During the study period, the use of video telehealth increased among all sub-groups with the largest increases seen among Black adults and adults with lower educational attainment.
Friedman et al., 2022⁴⁸	Quasi-experimental study (pre/post)	Infectious Diseases (ID) department Ryan White adult HIV clinic at the University of Chicago Medicine (UCM), a major provider of HIV care on the south side of Chicago	Pre-pandemic period: 15 March 2019 to 9 September 2019; pandemic period: 15 March 2020 to 9 September 2020	HIV	Patients with HIV who attended appointments in the infectious diseases (ID) department Ryan White adult HIV clinic	Telehealth	Telehealth utilization (odds of having a telehealth visit)	Older individuals were more likely to attend virtual visits compared to younger patients and Black patients and patients classified as ‘other’ race were less likely to use telehealth compared to White patients.
George et al., 2021⁴⁹	Quasi-experimental study (pre/post)	Columbus electronic health record (EHR) data warehouse of the American Arthritis and Rheumatology Associates (AARA) network, which represents ∼300 full-time practicing rheumatology clinicians across 27 states	Pre-COVID-19: 1 January 2020 to 22 March 2020; COVID-19 transition: 23 March 2020 to 3 May 2020; post-COVID-19 transition: 4 May 2020 to 1 September 2020	Rheumatology care	Patients enrolled in a community practice–based rheumatologist network	Telehealth (video and phone)	Telehealth utilization (odds of having a telehealth visit)	Factors associated with a lower likelihood of having a telehealth visit included older age, male sex, lower socioeconomic status, and rural residence. Greater driving distance from the rheumatologist’s office was associated with a greater likelihood of having a telehealth visit.
Grinberg et al., 2022⁵⁰	Quasi-experimental study (pre/post); mixed methods study	12 Veterans Health Administration facilities with a Headache Center of Excellence (HCoE)	Pre-pandemic: August 2019 to February 2020; Pandemic: March 2020 to September 2020	Headaches	Patients receiving care within one of 12 VHA facilities which contain a HCoE	Telehealth (VA Video Connect (VVC), Clinical Video Telehealth (CVT) and telephone)	Telehealth utilization (relative risk of visit type)	The study found differences in telehealth utilization based on patient age, race/ethnicity, and rurality.
Hogan et al., 2022⁵¹	Interrupted time-series	Nationwide, Veterans Health Administration	July 2019 to October 2020	Mental health	Veterans with a mental health outpatient visit	Telemental health (VA Video Connect (VVC))	Telemental health utilization (change in virtual encounters)	Prior to COVID-19, rates of VVC use (percentages of all mental health care) were higher among rural veterans. During the COVID-19 pandemic with restrictions in place, rural veteran VVC use continued to increase, but this increase was surpassed by that of urban veterans.
Jaffe et al., 2020⁵²	Retrospective cohort and survey study (pre/post)	U.S. National Health and Wellness Survey and Komodo Health	Baseline period: March 2019; COVID-19 period: March 2020	None specified	A nationally representative sample of adults ages 18 years or older with a Komodo payer-complete claim	Telehealth	Telehealth utilization (odds of having a telehealth visit)	Age, marital status, and geographic residence (rural/urban) were significant predictors of telehealth use compared to in-person use.
Jallow et al., 2022⁵³	Quasi-experimental study (pre/post)	MedStar Health System in Washington DC representing 3 outpatient dermatology clinics	Pre-quarantine: December 2019 to February 2020; During quarantine: April 2020 to June 2020; post-quarantine: January 2021 to March 2021	Dermatology	Patients with recorded dermatology visits in electronic medical records at a tertiary referral center in Washington, DC	Teledermatology	Teledermatology utilization (telehealth visit rates vs. office-based visit rates)	Telehealth visits rate was significantly different between quarantine and post-quarantine periods across all insurance groups, all racial/ethnic groups, both language groups and all age groups.
Judy et al., 2021⁵⁴	Quasi-experimental study (pre/post)	Nemours Children's Health Care System (NCHCS): Delaware Valley (DV) and Central Florida (CF)	2019 and 2020	Gastroenterology	Pediatric gastroenterology patients are seen in the Nemours Children Health Care System	Telehealth	Telehealth utilization (odds of having a telehealth visit)	DV: Significant racial, ethnic, and socioeconomic disparities were present for telehealth utilization. CF: Language barriers significantly affected telehealth utilization.
Khosla et al., 2022⁵⁵	Quasi-experimental study (pre/post); retrospective cohort study	University of Chicago, an urban tertiary care center predominantly serving a Black and publicly insured population	Pre-period: December 2019 to 14 February 2020; post-period: 15 March 2020 to June 2020	Hypertensive disorders of pregnancy (HDP)	Patients with HDP who were delivered between December 2019 and June 2020 at the University of Chicago	Telehealth	Telehealth utilization (proportion of visits completed via telehealth)	Transition to telehealth improved attendance at postpartum hypertension visits among non-Hispanic Black people. This led to significant decreases in the racial disparities in follow-up rates.
Larson et al., 2022⁵⁶	Quasi-experimental study (pre/post)	OCHIN, a non-profit healthcare innovation center providing a single instance of Epic to safety net clinics (SNC) in 16 states	Pre-pandemic: 1 March 2019 to 28 February 2020; pandemic: 1 April 2020 to 31 March 2021	None specified	Patients aged ≥18 years with at least 1 face-to-face or telemedicine visit at an eligible SNC during the study period	Telemedicine (video and telephone)	Telemedicine utilization (odds of having a telemedicine visit)	All rural patients had significantly lower odds of using TM for a visit during the pandemic period than patients residing in urban areas, with isolated rural patients showing the lowest odds.
Lattimore et al., 2021⁵⁷	Quasi-experimental study (pre/post)	Single academic tertiary care center	Pre COVID-19: 1 July 2019 to 17 March 2020; COVID-19: 18 March 2020 to 31 May 2020	Outpatient surgical encounters	Patients with an outpatient Department of Surgery encounter at a tertiary care center	Telemedicine	Telemedicine utilization (odds of having a telemedicine visit)	Telemedicine was more likely utilized by female patients and those without government or commercial insurance compared to patients who used in-person visits.
Lee et al., 2021⁵⁸	Quasi-experimental study (pre/post)	Large academic dermatology department	Pre-COVID: March 2019 to May 2019; COVID-19: March 2020 to May 2020	Acne	Patients with a visit for acne	Telemedicine (video and telephone)	Telemedicine utilization (proportion of virtual visits)	Non-White and non-English-speaking patients were less likely to use video visits for acne during the pandemic than White and English-speaking patients.
Leung et al., 2022⁵⁹	Quasi-experimental study (pre/post); retrospective cohort study	Nationwide, Veterans Health Administration	Before pandemic: 16 March 2019 to 15 15 March 2020; pandemic: 16 March 2020 to 16 December 2021	Primary care and mental health	Veterans who received primary care or mental health integration services	Telehealth (video and phone)	Telehealth utilization (rurality as a predictor for telehealth use)	The pandemic exacerbated the rural-urban telehealth divide across sites. Compared to urban VAs, telehealth expansion lagged for rural ones, especially in mental health integration services.
Lupez et al., 2022⁶⁰	Quasi-experimental study (pre/post); retrospective cohort study	Largest safety-net hospital in New England	Pre-pandemic: 15 March 2018 to 14 March 2020; pandemic: 15 March 2020 to 15 March 2021	Type II Diabetes	All established adult primary care patients with Type II diabetes	Telemedicine	Telemedicine utilization (odds of having a telemedicine visit)	Odds of engagement in telemedicine did not differ between patients of different races/ethnicities, languages, and insurance statuses. However, Black patients, older patients, and those who do not speak English are less likely to use video.
Mueller et al., 2022⁶¹	Quasi-experimental study (pre/post); retrospective cohort study	Mount Sinai Health System (MSHS), a large academic health care system, composed of 7 hospitals in NYC, uses a single electronic health record (EHR) system	Shutdown: 23 March 2020 to 23 May 2020; reopening: 24 May 2020 to 23 September 2020	Pain	Patients with pain receiving care at a large academic institution in New York City	Telehealth (phone and video)	Telehealth utilization	Patients who were older, publicly insured, and identified as Black or Hispanic were overrepresented in the telephone visit group during the shutdown and the in-person group during reopening.
Patel et al., 2021⁶²	Quasi-experimental study (pre/post); retrospective cohort study	Nationwide; OptumLabs® Data Warehouse (OLDW); The OLDW includes medical claims and enrollment records for commercial and Medicare Advantage enrollees.	Pre-COVID-19: 1 January 2020 to 17 March 2020; COVID-19: 18 March 2020 to 16 June 2020	None specified	Commercially insured and Medicare Advantage enrollees	Telemedicine	Telemedicine utilization (percentage of total visits)	Enrollees in counties with the lowest quartile of median household income and proportion White race had a greater percentage of total visits delivered via telemedicine in the COVID-19 period and in rural counties, a lower proportion of care was via telemedicine than in urban counties.
Pritchard et al., 2023⁶³	Quasi-experimental study (pre/post); retrospective cohort study	Large, outpatient department of an urban, East Coast academic medical center	July 2019 to December 2021	Attention-Deficit/Hyperactivity Disorder (ADHD)	Pediatric patients seen for psychological evaluation and diagnosed with ADHD	Telehealth	Telehealth utilization	Children seen via telehealth were significantly more likely to be older, White, have fewer comorbid conditions, and live farther from the clinic than those seen in person.
Pritchett et al., 2022⁶⁴	Quasi-experimental study (pre/post); cross-sectional, multi-site, retrospective analysis	Mayo Clinic Cancer Practice (MCCP), is a multisite, multiregional cancer practice with tertiary referral campuses in Minnesota, Florida, and Arizona, as well as rural, community-based hospitals and clinics throughout the Upper Midwest.	July 2019 to August 2019; July 2020 to August 2020; July 2021 to August 2021	None specified	Patients with visits at MCCP.	Telehealth	Telehealth utilization (rate)	Rural residence was significantly associated with lower telehealth utilization as compared with urban residents.
Qian et al., 2022⁶⁵	Quasi-experimental study (pre/post); retrospective cohort study	University of California San Diego Health System; Moores Cancer Center, a National Cancer Institute (NCI) designated Comprehensive Cancer Center.	Pre-expansion: 1 January 2020 to 15 March 2020; Expansion: 16 March 2020 to 30 September 2020	Cancer	All cancer patients over 18 years of age who received outpatient oncology care at UC San Diego Health	Telemedicine	Telemedicine utilization (odds of a telemedicine visit)	Several groups of patients were less likely to use telemedicine, including Hispanic, Asian, Spanish-speaking, low-income, and those with Medicaid.
Qian et al., 2021⁶⁶	Quasi-experimental study (pre/post); retrospective cohort study	Kaiser Permanente Southern California (KPSC), an integrated health care system that provides comprehensive health care to over 4.7 million racially, ethnically, and socioeconomically diverse members at its 15 hospitals and 234 medical offices	Pre-pandemic period: 5 January 2020 to 7 March 2020; early pandemic period: 22 March 2020 to 25 April 2020; later pandemic period: 4 October 2020 to 31 October 2020; corresponding periods in 2019	None specified	Individuals of all ages who were KPSC members from January 5, 2020, to October 31, 2020 (week 1 to week 43 in 2020) and the corresponding period in 2019.	Telemedicine	Telehealth utilization (ratio of the visit rate)	The Hispanic group and low-income group had the largest percentage increase in telehealth utilization in response to the COVID-19 pandemic.
Rodriguez et al., 2021⁶⁷	Quasi-experimental study (pre/post); retrospective study	Tertiary care center	Control: 1 April 2019 to 15 May 2019; Study: 1 April 2020 to 15 May 2020	Gastroenterology	Patients with GI telemedicine visit at a tertiary care center	Telemedicine (video and telephone)	Telemedicine utilization (odds of having a telemedicine visit)	Black/Latinx, low SES, Medicare, and older patients were independently associated with lower odds of engaging in a video visit compared to an in-person visit or telemedicine visit.
Ruberto et al., 2022⁶⁸	Quasi-experimental study (pre/post); retrospective review	Department of Orthopedic Surgery at a large academic orthopedic practice	Pre-COVID-19: 1 January 2019, to 23 December 2019; peri-COVID-19: 1 January 2020 to 23 December 2020	Orthopedic surgery	Patients seen in the Department of Orthopedic Surgery	Telemedicine	Telemedicine utilization (odds of having a telemedicine visit)	Non-White race, non-commercial insurance plans, and male sex were associated with decreased telemedicine utilization.
Sachs et al., 2021⁶⁹	Quasi-experimental study (pre/post); repeated cross-sectional study	Ambulatory clinics at Oregon Health & Science University	Reference period: 1 June 2019 to 30 September 2019; study period: 1 June 2020 to 30 September 2020	Ambulatory conditions	Unique patient encounters from ambulatory provider-led visits	Telemedicine	Telemedicine utilization (odds of having a telemedicine visit)	Racial minorities, seniors, and non-English speakers were not engaging fully with telehealth services and internet-based video engagement was less likely for those who were male, Black, American Indian, have Medicaid, prefer a non-English language, or in older age groups.
Sanaka et al., 2022⁷⁰	Quasi-experimental study (pre/post); retrospective review	Cleveland Clinic Gastroenterology Department	Pre-COVID: 9 March 2019 to 18 June 2019; lock-down: 9 March 2020 to 18 June 2020; flattening: 9 March 2021 to 18 June 2021	Gastroenterology	Patients receiving outpatient care in the Cleveland Clinic Gastroenterology department	Telehealth	Telehealth (factors associated with telehealth visits)	Reduced utilization of telehealth was noted in older patients, those of the Black or Hispanic race, higher education levels, those with Medicaid or other public insurance, unemployed individuals, and non-English/Spanish speakers.
Sen et al., 2022⁷¹	Quasi-experimental study (pre/post)	Alabama's Children's Health Insurance Program, ALL Kids	Control period: March 2018 and 2019 to December 2018 and 2019: study period: March 2020 to December 2020	None specified	Children with enrollment and claims data in the ALL Kids program.	Telehealth	Telehealth utilization (odds of telehealth use)	Black and Hispanic children had lower odds of telehealth use than White non-Hispanic children and rural residents had lower odds of telehealth use than urban residents. Children in the highest income-based fee group had higher odds of telehealth use.
Shehan et al., 2021⁷²	Quasi-experimental study (pre/post); retrospective case series	OHNS Department of a single academic tertiary institution	Pre-COVID-19: 1 October 2019 to 31 October 2019; COVID-19: 16 March 2020 to 10 April 2020	Otolaryngology	Scheduled outpatient appointments in the OHNS Department with surgeons and advanced practice providers	Telemedicine	Telemedicine utilization (odds of having a telemedicine visit)	There was a higher proportion of Hispanic/Latino patients who received telemedicine care.
Stevens et al., 2021⁷³	Quasi-experimental study (pre/post); retrospective cohort study	Outpatient clinics associated with Beth Israel Deaconess Medical Center	Control period: 2 March 2019 to 10 June 2019; study period: 2 March 2020 to 10 June 2020	None specified	Patients aged ≥18 years	Telemedicine	Telemedicine utilization	Black and White patients accessed telehealth care more than Hispanic and Asian patients. Patients with an “unknown” racial or ethnic designation upon registration had the least access to care. Older patients used telehealth more often than younger patients. Among telehealth users, patients over 65 years of age were less likely to use video technology. Similarly, Black, Asian, and Hispanic patients were less likely to use video technology than White patients.
Tewari et al., 2022⁷⁴	Quasi-experimental study (pre/post); retrospective cohort study	Not specified	Pre-cohort: 1 January 2019 to 28 February 2020; post-cohort: 1 March 2020 to 1 June 2021	Infertility	Patients presenting for an initial infertility consultation	Telehealth	Telehealth utilization (percentage of telehealth visits)	In comparison to all other race patients, African American patients in the Post cohort were less likely to have a telehealth visit.
Thomason et al., 2021⁷⁵	Quasi-experimental study (pre/post)	Urban County Hospital Rheumatology Clinic	Pre-COVID-19 period: 1 March 2019 to 28 February 2020; COVID-19 period: 1 April 2020 to 31 March 2021	Rheumatology	All patients completing visits at the rheumatology clinic	Telemedicine	Telemedicine utilization (odds of completion of telemedicine visit)	The study observed significant age, race, sex, and language-related inequities in telemedicine use. The strongest single predictor was English language preference.
Tilden et al., 2021⁷⁶	Quasi-experimental study (pre/post); retrospective cohort study	Vanderbilt University Medical Center's clinical data systems	Pre-COVID-19: 1 January 2018 to 16 March 2020; COVID-19: 17 March 2020 to 30 June 2020	Type I Diabetes	Patients who completed at least one clinic visit at the adult or pediatric clinic	Telemedicine	Telemedicine utilization (odds of completion of telemedicine visit)	The odds of completing a visit via telemedicine were lower among non-English-speaking and Medicaid-insured pediatric patients. No clinically significant differences were observed for other demographic factors.
Tisdale et al., 2021⁷⁷	Quasi-experimental study (pre/post); retrospective cohort analysis	Nationwide, Veterans Health Administration	Pre-pandemic: 1 January 2019 to 10 March 2020; pandemic: 11 March 2020 to 25 November 2020	Cardiology	Veterans with cardiology encounters	Telemedicine (video and telephone)	Telemedicine utilization (likelihood of a virtual visit (hazard ratios))	Black and rural patients were less likely to have video visits than other races of patients and those living in urban locations and men were less likely than women to have video visits.
Wegermann et al., 2020⁷⁸	Quasi-experimental study (pre/post); single-center retrospective cohort study	Hepatology clinic	Pre-COVID-19: 1 January 2020 to 29 February 2020; COVID-19: 1 April 2020 to 30 May 2020; outside study: After 30 May 2020	Hepatology	All adult patients referred to a Hepatology clinic	Telehealth (video and phone)	Telehealth utilization (odds of a completed visit)	Black race, age, unmarried status, and Medicaid were associated with increased odds of completing a video over a phone visit.
Wegermann et al., 2022⁷⁹	Quasi-experimental study (pre/post); retrospective cohort study	Duke University Health System	Pre-COVID-19 baseline period: 1 January 2020 to 29 February 2020; COVID-19 period: 1 April 2020 to 30 May 2020	Liver disease	All visit attempts in adult hepatology clinics (general and transplant) at Duke University Health System	Telemedicine	Telemedicine utilization (odds of a completed visit)	Increasing age was associated with higher odds of a phone visit and non-Hispanic Black race was associated with nearly twice the odds of completing a phone visit instead of a video visit, compared to non-Hispanic White patients. Compared to private insurance, Medicaid and Medicare were associated with increased odds of completing a telephone visit, and Medicaid was associated with increased odds of incomplete visits.
Whaley et al., 2020⁸⁰	Quasi-experimental study (pre/post); cross-sectional study	Nationwide, Castlight Health. Castlight Health aggregates medical and pharmaceutical claims from self-insured employers and health plans that purchase access to their transparency tools and benefits platform.	Control period: March 2018 and 2019 to April 2018 and 2019; Study period: March 2020 to April 2020	None specified	Commercially insured individuals in the United States	Telemedicine	Telemedicine utilization (rate change)	The study identified lower rates of telemedicine use among patients residing in zip codes with lower-income or predominately racial/ethnic minority populations.
White-Williams et al., 2023⁸¹	Quasi-experimental study (pre/post); retrospective study	Nationwide, COVID-19 Research Database Consortium	Control period: March 2019 to December 2019; Study period: March 2020 to December 2020	None specified	Privately insured patients in the Healthjump database, provided by the COVID-19 Research Database Consortium	Telehealth	Telehealth utilization (odds of using telehealth)	The likelihood of using telehealth was lower among Hispanic patients than among non-Hispanic White and non-Hispanic Black patients during the pandemic.
Xu et al., 2022⁸²	Quasi-experimental study (pre/post); retrospective study	Alabama Medicaid Database	Pre-pandemic period: 1 March 2019 to 28 February 2020; pandemic period: 1 March 2020 to 28 February 2021; pandemic period (mass vaccination): 1 March 2021 to 30 June 2021	None specified	Medicaid recipients in Alabama	Telemedicine	Telemedicine utilization (rate of adoption)	As a population, females experienced a higher increase in telehealth utilization compared to males. All races experienced a uniform increase in telehealth utilization, but the Black/African American community experienced the least in terms of percentage of increase. In terms of rurality, a uniform increase in telehealth utilization was observed across highly rural, moderately rural, and urban counties, with moderately rural counties reaching the highest overall utilization rate.

Race/ethnicity

Forty studies (84%) included at least one stratified analysis of race and/or ethnicity. Among these studies, most (n = 27, 68%) reported lower telehealth utilization^{38,40,43–46,48–50,53,54,61–63,65,67–69,71,73–75,80–84} among Black/African American participants and other racial minorities compared to White participants, but six studies (15%) observed higher telehealth utilization in minority groups. Ten studies (25%) that screened for differences in telehealth modality, racial/ethnic minority groups were more likely to use audio-only telehealth, compared with White telehealth users.

Rurality/location

We included 22 studies (46%) that examined geographical factors in telehealth use. Most of these studies (n = 14, 64%) reported that rural participants were less likely to use telehealth than urban participants.^{39,41,44,49,51,52,59,62,64,71,77,83,85} Two studies looked at differences by geographic region, and both showed that participants living in the Northeast had higher telehealth utilization than those in the South and the West.^47,52

Age

Twenty-one studies (44%) reported age-stratified analyses, of which 18 (86%) reported that older patients were less likely to use telehealth compared to younger patients.^{37,39,44–46,48–50,52,53,61,66,67,69,75,78,81,84} Among the two studies comparing audio-only to video telehealth, both showed that older patients were more likely to use audio-only instead of video telehealth.^61,79

Insurance status

Twenty studies (42%) reported telehealth utilization outcomes stratified by insurance status during this time period, and one-third (n = 7, 35%) reported that telehealth usage was similar in different strata of insurance coverage.^{35,38,40,43,48,54,60} Five studies (25% of those that included insurance status) showed that participants with public insurance were less likely to utilize telehealth,^{53,61,65,68,84} and three studies (15%) showed that self-pay or other insurance was associated with less telehealth use than commercial insurance.^46,75,76 Three studies (15%) indicated that participants with Medicare or Medicaid were less likely to utilize video telehealth compared to audio only.^45,67,85

Language

We identified 15 studies (31%) that examined telehealth utilization by language preference. Of these studies, 10 (67%) showed that English speakers had higher utilization.^{37,38,46,54,65,69,75,76,84,86}

Socioeconomic status, income, and social vulnerability

Of the included studies, 14 (29%) reported the association between social vulnerability and telehealth utilization, either by examining individual socioeconomic status (SES) or income (n = 11), the area deprivation index (n = 2), or county-level characteristics (n = 1). Most studies (n = 11, 79%) reported that telehealth use was the lowest in counties with high poverty levels, low income, low SES, or low education levels.^{41,44,49,54,57,62,65,67,71,80,83,84}

Sex

Of the 12 studies (25%) that examined telehealth utilization by sex, seven (58%) reported increased utilization among females, but differences by sex were small.^{47,57,68,75,77,81,82}

Risk of bias assessment

Total scores from the Downs and Black risk of bias assessment (Figure 2) ranged between 10 and 19 (out of 27), indicating a moderate risk of bias in the included studies (and no studies at low risk of bias). The mean score was 16.2, and sub-domain means were as follows: reporting bias (6.3 out of ten), external validity (2.7 out of three), internal validity—bias (3.7 out of seven), and internal validity—confounding (3.5 out of seven).

Figure 2.

Summary of methodological quality of included studies using the Downs and Black risk of bias assessment.

Discussion

In this systematic review of studies examining health equity in telehealth access and use during the COVID-19 pandemic, we identified papers that reported the association between telehealth use and racial/ethnic minority status, rurality, native language, age, and other sociodemographic factors. In aggregate, most of these studies reported that although telehealth use increased during the pandemic, the increase was most pronounced in largely non-minority populations, including White, younger, English-speaking people from urban areas. This finding is relevant because it suggests that many telehealth applications were not effective in reducing health inequity during the pandemic, despite being a technology that was widely adopted across a number of social and demographic groups.

Some have highlighted the role that the digital divide plays in exacerbating health inequality related to telehealth use. In a survey of primary care practices in 2020, social vulnerability was a factor significantly associated with decreased use of telehealth.⁸⁷ Factors associated with social vulnerability are also associated with reduced availability of broadband internet, decreased access to communication technology, and lower technology literacy, and these factors may become even more consequential with the rapid adoption of new telehealth solutions. A working group of the International Medical Informatics Association highlighted that the COVID-19 experience uncovered concerns about telehealth exacerbating health inequity, with access to technology, financing, equipment, and governance capacity driving improved equitable use.⁸⁸ Shaw and colleagues extended this work to highlight three factors that could potentially improve equitable delivery of telehealth-enabled care: simplifying complex interfaces and workflows, using supportive intermediaries, and creating mechanisms through which marginalized community members can provide immediate input into the planning and delivery of virtual care.⁸⁷ These recommendations were an important contribution because they lean heavily on principles of active community and end-user engagement in designing new systems of care, attempting to address longstanding systematic structural attributes that contribute to unequal access, unequal care, and unequal outcomes. They also supplement other work suggesting that interventions to reduce the digital divide require a multi-stakeholder approach, appropriate use of interpreters, and a multifaceted policy approach to reducing disparities in access.^89–91

However, ameliorating disparities in telehealth access and use is only one step on the pathway to improving health outcomes. Existing features of the health system perpetuate ongoing disparities in traditional healthcare.⁹² Minority patients have been shown to experience poor healthcare communication, including information-giving, patient participation, and participatory decision-making. Disadvantaged populations are more likely to live in regions with inadequate access to physicians and other healthcare providers.^93,94 Even access to healthy groceries, bike lanes, and high-speed internet are lower in communities with more racial/ethnic minority residents, which further contribute to underlying differences in health literacy, chronic health diagnoses,^95–97 and ability to access healthcare. Telehealth policy changes allowing non-rural patients access to telehealth services from home—even in urban areas—may have further widened disparities.⁵ For telehealth to reduce disparities in healthcare, it does not only need to be available and used equally—it needs to specifically benefit those least likely to have adequate existing pathways to care.

There is one bright spot in the pandemic's highlighting of care disparities, however. COVID-19 outcomes were so different in disadvantaged populations that researchers, educators, and policymakers have had renewed focus on ways to track and reduce disparities. For instance, inequalities in COVID-19 test availability may have contributed to differences in COVID-19 clinical outcomes by community racial/ethnic status,⁹⁸ but that inequality lessened through the course of the pandemic. Inpatient COVID-19 medical care may have been different for disadvantaged populations early in the pandemic.⁹⁹ For instance, it was only after recognizing discrepancies between blood gas results and pulse oximetry that researchers identified the role of skin color in contributing to inadequate oxygen supplementation in COVID-19 patients.¹⁰⁰ With telehealth availability specifically, telehealth interventions targeted to reduce disparities showed early evidence of effectiveness.¹⁰¹ Many disparities reduced as the pandemic progressed, and highlighting differences in care and outcomes was one powerful tool to address underlying health system imbalances that lead to disparities in access and outcomes.

Our study has several limitations. First, the studies that comprised this analysis had significant clinical heterogeneity, precluding our statistical pooling of the findings. Second, many of these studies used data from programs that were implemented very quickly in the context of the COVID-19 pandemic. Those characteristics of included telehealth interventions may have evolved later in the pandemic as lessons learned from early implementation were used to improve later telehealth-facilitated care. Finally, in a study of health equity, pre-pandemic control groups used in some of the studies may not have fully incorporated the ways in which non-telehealth care changed during 2020 and 2021, which could lead to spurious conclusions in some of the included studies.

In conclusion, many telehealth studies reported measures of health equity during the early phase of the COVID-19 pandemic, and the dimensions of equity most commonly reported focused on differences in telehealth use based on race/ethnicity, rurality, language, and age. We recommend that future telehealth studies examine characteristics of program implementation that improve equity so that those features and lessons can be used to improve aggregate telehealth care across conditions and contexts.

Supplemental Material

sj-docx-1-jtt-10.1177_1357633X241245459 - Supplemental material for The role of increasing synchronous telehealth use during the COVID-19 pandemic on disparities in access to healthcare: A systematic review

Supplemental material, sj-docx-1-jtt-10.1177_1357633X241245459 for The role of increasing synchronous telehealth use during the COVID-19 pandemic on disparities in access to healthcare: A systematic review by Sara Ternes, Lauren Lavin, J Priyanka Vakkalanka, Heather S Healy, Kimberly AS Merchant, Marcia M Ward, and Nicholas M Mohr in Journal of Telemedicine and Telecare

Footnotes

Acknowledgements

The authors acknowledge Tera Shea, BS (University of Iowa Carver College of Medicine) for her editorial assistance in the preparation of this manuscript.

Declaration of conflicting interests

The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Funding

The author(s) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: This work was supported by funding from the Rural Telehealth Research Center, which is supported by the Office for the Advancement of Telehealth, Health Resources and Services Administration (HRSA, U3GRH40003). Dr Mohr is additionally supported by a grant from the Agency for Healthcare Research and Quality (AHRQ, K08 HS025753). The views expressed in this publication are solely those of the authors and do not reflect the official views of AHRQ, HRSA, or the U.S. Government.

ORCID iDs

Lauren Lavin

J Priyanka Vakkalanka

Kimberly AS Merchant

Nicholas M Mohr

Data availability statement

All data generated or analyzed during this study are included in this published article.

Supplemental material

Supplemental material for this article is available online.

References

Doraiswamy

Abraham

Mamtani

, et al. Use of telehealth during the COVID-19 pandemic: scoping review. J Med Internet Res 2020; 22: e24087.

Koonin

Hoots

Tsang

, et al. Trends in the use of telehealth during the emergence of the COVID-19 pandemic – United States, January-March 2020. MMWR Morb Mortal Wkly Rep 2020; 69: 1595–1599.

Khera

Knoedler

Meier

, et al.

Payment and coverage parity for virtual care and in-person care: How do we get there?

Telemed Rep 2023; 4: 100–108.

Centers for Medicare & Medicaid Services. Coronavirus waivers & flexibilities, https://www.cms.gov/coronavirus-waivers (accessed 25 October 2023).

Telehealth policy changes after the COVID-19 public health emergency, https://telehealth.hhs.gov/providers/telehealth-policy/policy-changes-after-the-covid-19-public-health-emergency.

Telehealth policy update: 2023 consolidated appropriations act extends select telehealth flexibilities, https://www.mcdermottplus.com/wp-content/uploads/2023/02/2023-Consolidated-Appropriations-Act-Extends-Select-Telehealth-Flexibilities.pdf.

National Academy for State Health Policy. Expanding services during COVID-19, https://nashp.org/expanding-services-during-covid-19/.

Centers for Medicare & Medicaid Service. Medicare telehealth trends report, https://data.cms.gov/sites/default/files/2023-09/Medicare%20Telehealth%20Trends%20Snapshot%2020230821_508.pdf.

Samson

Tarazi

Turrini

, et al. Medicare beneficiaries’ use of telehealth in 2020: trends by beneficiary characteristics and location. Office of the Assistant Secretary for Planning and Evaluation, Washington, DC, 2021.

10.

Hatef

Wilson

Hannum

, et al. Use of telehealth during the COVID-19 era. Rockville, MD: Agency for Healthcare Research and Quality (US), 2023.

11.

Czeisler

Marynak

Clarke

KEN

, et al. Delay or avoidance of medical care because of COVID-19-related concerns - United States, June 2020. MMWR Morb Mortal Wkly Rep 2020; 69: 1250–1257.

12.

Magesh

John

, et al. Disparities in COVID-19 outcomes by race, ethnicity, and socioeconomic status: a systematic review and meta-analysis. JAMA Netw Open 2021; 4: e2134147–e2134147.

13.

Association of American Medical Colleges. Telehealth helps close health care disparity gap in rural areas, https://www.aamc.org/news/telehealth-helps-close-health-care-disparity-gap-rural-areas (accessed 11 July 2023).

14.

Garling

Cho

Vogt

. Reducing health inequities through telehealth. US Pharm: Pharma Resour Clin Excellence 2022; 47: 28–32.

15.

Lau

Knudsen

. Reducing disparities in telemedicine: an equity-focused, public health approach. Health Aff (Millwood) 2022; 41: 647–650.

16.

Assistant Secretary for Planning and Evaluation: Office of Healthy Policy. Medicare beneficiaries’ use of telehealth in 2020: trends by beneficiary characteristics and location .

17.

Alonso

Crouch

Thorell

. National Rural Health Association policy paper: telehealth in rural America . 2019.

18.

Karimi

Lee

Couture

, et al. National survey trends in telehealth use in 2021: disparities in utilization and audio vs. video services. Research report no. HP-2022-04, 2022.

19.

Lee

Grigorescu

Enogieru

, et al. Updated national survey trends in telehealth utilization and modality (2021-2022). Research report no. HP-2023-09. Assistant Secretary for Planning and Evaluation, US Department of Health and Human Services, Washington DC, 2023.

20.

Vakkalanka

Gadag

Lavin

, et al. Telehealth use and health equity for mental health and substance use disorder during the COVID-19 pandemic: a systematic review. Telemed J E Health 2024. DOI: https://doi.org/10.1089/tmj.2023.0588.

21.

Tierney

Mosqueda

Cesena

, et al. Telemedicine implementation for safety net populations: a systematic review. Telemed e-Health 2024; 30: 622–641.

22.

Zou

Harvard

Qian

, et al. A systematic review of digital health technologies for the care of older adults during COVID-19 pandemic. Digit Health 2023; 9: 20552076231191050.

23.

Cunha

Pedro

Cordeiro

. Facilitators of and barriers to accessing hospital medical specialty telemedicine consultations during the COVID-19 pandemic: systematic review. J Med Internet Res 2023; 25: e44188.

24.

Jackson

Sreedhara

Bostic

, et al. Telehealth use to address cardiovascular disease and hypertension in the United States: a systematic review and meta-analysis, 2011-2021. Telemed Rep 2023; 4: 67–86.

25.

Bedi

Vyas

Chung

, et al. Telemedicine in international cleft care: a systematic review. Cleft Palate Craniofac J 2021; 58: 1547–1555.

26.

Mistry

Shaw

Raffan

, et al. Inequity in access and delivery of virtual care interventions: a scoping review. Int J Environ Res Public Health 2022; 19: 9411.

27.

Choukou

Sanchez-Ramirez

Pol

, et al. COVID-19 infodemic and digital health literacy in vulnerable populations: a scoping review. Digit Health 2022; 8: 20552076221076927.

28.

Colburn

. The impact of telehealth expansion on health care utilization, access, and outcomes during the pandemic: a systematic review. Telemed e-Health 2023. EPub ahead of print. DOI: https://doi.org/10.1089/tmj.2023.0440.

29.

Truong

Yeganeh

Cook

, et al. Using telehealth consultations for healthcare provision to patients from non-Indigenous racial/ethnic minorities: a systematic review. J Am Med Inform Assoc 2022; 29: 970–982.

30.

Vakkalanka

Mohr

Ward

, et al. Evaluation of telehealth access and utilization for health care during the COVID-19 pandemic, https://www.crd.york.ac.uk/prospero/display_record.php?RecordID=392678 (2023).

31.

Page

McKenzie

Bossuyt

, et al. The PRISMA 2020 statement: an updated guideline for reporting systematic reviews. Br Med J 2021; 372: n71.

32.

Telehealth.HHS.gov. Research articles and papers, https://telehealth.hhs.gov/research-articles (2023, accessed 02 February 2024).

33.

Moulton

Wakefield

Sande

, et al. Rural health research gateway: national audience impact study report, https://www.ruralhealthinfo.org/assets/1129-4567/national-audience-impact-study-report.pdf (2007).

34.

Downs

Black

. The feasibility of creating a checklist for the assessment of the methodological quality both of randomised and non-randomised studies of health care interventions. J Epidemiol Community Health 1998; 52: 377–384.

35.

Ackroyd

Kim

Lee

. Telemedicine utilization in gynecologic cancers: understanding the digital divide. Gynecol Oncol 2021; 162: S286–S287.

36.

Annapragada

Meshram

Jenkins

, et al. Age and racial disparities in telemedicine utilization in an academic orthopedic surgery department. Telemed J E Health 2022; 28: 970–975.

37.

Bayudan

Kamal

Dai

, et al. Telemedicine and healthcare access in ambulatory gastroenterology visits during the COVID-19 pandemic: a single-center retrospective analysis. Gastroenterology 2022; 162: S-475–S-476.

38.

Bharadwaj

Labban

Langbein

, et al. Patterns of tele-health usage after the COVID-19 pandemic among surgical specialties and urology. J Urol 2022; 207: e221.

39.

Bose

Dun

Zhang

, et al. Medicare beneficiaries in disadvantaged neighborhoods increased telemedicine use during the COVID-19 pandemic. Health Aff (Millwood) 2022; 41: 635–642.

40.

Cahan

Maturi

Bailey

, et al. The impact of telehealth adoption during COVID-19 pandemic on patterns of pediatric subspecialty care utilization. Acad Pediatr 2022; 22: 1375–1383.

41.

Cantor

McBain

Pera

, et al. Who is (and is not) receiving telemedicine care during the COVID-19 pandemic. Am J Prev Med 2021; 61: 434–438.

42.

Cao

Chen

Liu

, et al. Academyhealth Annual Research Meeting (ARM): a selection of abstracts accepted for oral presentation, 2021. Health Serv Res 2021; 56: 5–91.

43.

Chakawa

Belzer

Perez-Crawford

, et al. COVID-19, telehealth, and pediatric integrated primary care: disparities in service use. J Pediatr Psychol 2021; 46: 1063–1075.

44.

Connolly

Stolzmann

Heyworth

, et al. Patient and provider predictors of telemental health use prior to and during the COVID-19 pandemic within the Department of Veterans Affairs. Am Psychol 2022; 77: 249–261.

45.

Cousins

Van Til

Steppe

, et al. Age, race, insurance type, and digital divide index are associated with video visit completion for patients seen for oncologic care in a large hospital system during the COVID-19 pandemic. PLoS One 2022; 17: e0277617.

46.

Datta

Eiland

Samson

, et al. Telemedicine and health access inequalities during the COVID-19 pandemic. J Glob Health 2022; 12: 05051.

47.

Fischer

Predmore

Roth

, et al. Use of and willingness to use video telehealth through the COVID-19 pandemic. Health Aff 2022; 41: 1645–1651.

48.

Friedman

Devlin

Gilson

, et al. Age and racial disparities in telehealth use among people with HIV during the COVID-19 pandemic. AIDS Behav 2022; 26: 2686–2691.

49.

George

Danila

Watrous

, et al. Disruptions in rheumatology care and the rise of telehealth in response to the COVID-19 pandemic in a community practice-based network. Arthritis Care Res (Hoboken) 2021; 73: 1153–1161.

50.

Grinberg

Fenton

Wang

, et al. Telehealth perceptions and utilization for the delivery of headache care before and during the COVID-19 pandemic: a mixed-methods study. Headache 2022; 62: 613–623.

51.

Hogan

Amspoker

Walder

, et al. Differential impact of COVID-19 on the use of tele-mental health among veterans living in urban or rural areas. Psychiatr Serv 2022; 73: 1393–1396.

52.

Jaffe

Lee

Huynh

, et al. Health inequalities in the use of telehealth in the United States in the lens of COVID-19. Popul Health Manag 2020; 23: 368–377.

53.

Jallow

Ewulu

Ajilore

, et al. Analyzing disparities in access to teledermatology compared with dermatology clinic visits before, during, and after COVID-19 quarantine. Clin Dermatol 2023; 41: 207–214.

54.

Judy

Mougey

Venkatesh

, et al. Pediatric gastroenterology telehealth during the COVID-19 public health emergency: access to care, socioeconomic disparities and geo-mapping. JPGN 2021; 73: S362–S363.

55.

Khosla

Suresh

Mueller

, et al. Elimination of racial disparities in postpartum hypertension follow-up after incorporation of telehealth into a quality bundle. Am J of Obstet Gynecology MFM 2022; 4: 100580.

56.

Larson

Zahnd

Davis

, et al. Before and during pandemic telemedicine use: an analysis of rural and urban safety-net clinics. Am J Prev Med 2022; 63: 1031–1036.

57.

Lattimore

Kane

Fleming

2nd , et al. Disparities in telemedicine utilization among surgical patients during COVID-19. PLoS One 2021; 16: e0258452..

58.

Lee

Guo

Wang

, et al. Differences in utilization of nonvideo telemedicine visits for dermatologic concerns in underserved populations during the COVID-19 pandemic. J Telemed Telecare 2021; 27: 827–834.

59.

Leung

Yoo

Chu

. Widening rural-urban divide in telehealth use during the COVID-19 pandemic: a national observational study of primary care delivery in the veterans’ health administration. J Gen Intern Med 2022; 37: S346–S347.

60.

Lupez

Bayly

Xuan

, et al. Primary care and telemedicine utilization in patients with type 2 diabetes at a safety-net hospital before and after onset of the COVID-19 pandemic. J Gen Intern Med 2022; 37: S160–S161.

61.

Mueller

Lawrence

Benn

, et al. Disparities in telehealth utilization in patients with pain during COVID-19. Pain Rep 2022; 7: e1001.

62.

Patel

Mehrotra

Huskamp

, et al. Variation in telemedicine use and outpatient care during the COVID-19 pandemic in the United States. Health Aff (Millwood) 2021; 40: 349–358.

63.

Pritchard

Northrup

Peterson

, et al. Can we expand the pool of youth who receive telehealth assessments for ADHD? Covariates of service utilization. J Atten Disord 2023; 27: 159–168.

64.

Pritchett

Borah

Dholakia

, et al. Patient- and provider-level factors associated with telehealth utilization across a multisite, multiregional cancer practice. J Clin Oncol 2022; 40: 1512–1512.

65.

Qian

Schiaffino

Nalawade

, et al. Disparities in telemedicine during COVID-19. Cancer Med 2022; 11: 1192–1201.

66.

Qian

Hong

, et al. Disparities in outpatient and telehealth visits during the COVID-19 pandemic in a large integrated health care organization: retrospective cohort study. J Med Internet Res 2021; 23: e29959.

67.

Rodriguez

Okwara

Shen

, et al. Telemedicine in the COVID-19 era: impact on disparities in access to ambulatory care. Gastroenterology 2021; 160: S-29.

68.

Ruberto

Schweppe

Ahmed

, et al. Disparities in telemedicine utilization during COVID-19 pandemic analysis of demographic data from a large academic orthopaedic practice. JBJS Open Access 2022; 7. DOI: https://doi.org/10.2106/JBJS.OA.21.00116.

69.

Sachs

Graven

Gold

, et al. Disparities in telephone and video telehealth engagement during the COVID-19 pandemic. JAMIA Open 2021; 4. DOI: https://doi.org/10.1093/jamiaopen/ooab056.

70.

Sanaka

Garg

Patel

, et al. Impact of COVID-19 pandemic and social determinants of health on utilization of telehealth services. Gastroenterology 2022; 162: S-472–S-473.

71.

Sen

Sharma

Brisendine

, et al. Disparities in telehealth utilization in a population of publicly insured children during the COVID-19 pandemic. Popul Health Manag 2022; 25: 178–185.

72.

Shehan

Agarwal

O'Neil Danis

, et al. Effects of COVID-19 on telemedicine practice patterns in outpatient otolaryngology. Am J Otolaryngol 2021; 42: 103044.

73.

Stevens

Mechanic

Markson

, et al. Telehealth use by age and race at a single academic medical center during the COVID-19 pandemic: retrospective cohort study. J Med Internet Res 2021; 23: e23905.

74.

Tewari

Coyne

Weinerman

, et al. Racial disparities in presentation to infertility consultations and telehealth use during the COVID-19 pandemic. Fertil Steril 2022; 118: e201.

75.

Thomason

Mantilla

Bays

, et al. Socioeconomic characteristics associated with electronic health care utilization in an urban rheumatology clinic during the COVID-19 pandemic. Arthritis Rheumatol 2021; 73: 1252–1255.

76.

Tilden

Datye

Moore

, et al. The rapid transition to telemedicine and its effect on access to care for patients with type 1 diabetes during the COVID-19 pandemic. Diabetes Care 2021; 44: 1447–1450.

77.

Tisdale

Ferguson

Van Campen

, et al. Disparities in virtual cardiology visits among veterans’ health administration patients during the COVID-19 pandemic. J Gen Intern Med 2021; 36: S168.

78.

Wegermann

Wilder

Parish

, et al. Black, older, unmarried, and Medicaid patients were less likely to complete hepatology video visits during COVID-19. Hepatology 2020; 72: 382A–383A.

79.

Wegermann

Wilder

Parish

, et al. Racial and socioeconomic disparities in utilization of telehealth in patients with liver disease during COVID-19. Dig Dis Sci 2022; 67: 93–99.

80.

Whaley

Pera

Cantor

, et al. Changes in health services use among commercially insured US populations during the COVID-19 pandemic. JAMA Netw Open 2020; 3: e2024984–e2024984.

81.

White-Williams

Liu

Shang

, et al. Use of telehealth among racial and ethnic minority groups in the United States before and during the COVID-19 pandemic. Public Health Rep 2023; 138: 149–156.

82.

Hudnall

Zhao

, et al. Pandemic-triggered adoption of telehealth in underserved communities: Descriptive study of pre- and postshutdown trends. J Med Internet Res 2022; 24: e38602.

83.

Cao

Chen

Liu

, et al. Disparities in the use of in-person and telehealth outpatient visits among medicare beneficiaries in an accountable care organization during COVID-19. Health Serv Res 2021; 56: 5.

84.

Sanaka

Garg

Patel

, et al. Temporal trends and disparities in gastroenterology care use before, during, and after COVID-19 lockdown. J Investig Med 2022; 70: 1704–1712.

85.

Wegermann

Patel

Wilder

. Health equity and telemedicine in gastroenterology and hepatology. Clin Gastroenterol Hepatol 2021; 19: 1516–1519.

86.

Lee

Kassamali

Shah

, et al. 281 Racial and language disparities in teledermatology visits for acne during the COVID-19 pandemic. J Investig Dermatol 2021; 141: S50.

87.

Chang

Lai

Gupta

, et al. Rapid transition to telehealth and the digital divide: implications for primary care access and equity in a post-COVID era. Milbank Q 2021; 99: 340–368.

88.

Kuziemsky

Hunter

Udayasankaran

, et al. Telehealth as a means of enabling health equity. Yearb Med Inform 2022; 31: 60–66.

89.

Gallegos-Rejas

Thomas

Kelly

, et al. A multi-stakeholder approach is needed to reduce the digital divide and encourage equitable access to telehealth. J Telemed Telecare 2022; 29: 73–78.

90.

Gallegos-Rejas

Kelly

Snoswell

, et al. Does the requirement for an interpreter impact experience with telehealth modalities, acceptability and trust in telehealth? Results from a national survey including people requiring interpreter services. J Telemed Telecare 2023; 29: 24S–29S.

91.

Smith

Thomas

Snoswell

, et al. Telehealth for global emergencies: implications for coronavirus disease 2019 (COVID-19). J Telemed Telecare 2020; 26: 309–313.

92.

Hill

Artiga

Damico

. Health coverage by race and ethnicity, 2010-2021. The independent source for health policy and research, polling, and news. 2022.

93.

Kim

Peterson

Warnecke

, et al. The uneven distribution of medically underserved areas in Chicago. Health Equity 2020; 4: 556–564.

94.

Grumbach

Hart

Mertz

, et al. Who is caring for the underserved? A comparison of primary care physicians and nonphysician clinicians in California and Washington. Ann of Fam Med 2003; 1: 97–104.

95.

Bower

Thorpe

Jr Rohde

, et al. The intersection of neighborhood racial segregation, poverty, and urbanicity and its impact on food store availability in the United States. Prev Med 2014; 58: 33–39.

96.

Barajas

. Biking where Black: connecting transportation planning and infrastructure to disproportionate policing. Transp Res D 2021; 99: 103027.

97.

Asher-Schapiro

Sherfinski

. Digital divide in the US: nearly 40% of rural Black Americans have no Internet at home, https://www.globalcitizen.org/en/content/digital-divide-black-americans/ (2021).

98.

Dalva-Baird

Alobuia

Bendavid

, et al. Racial and ethnic inequities in the early distribution of U.S. COVID-19 testing sites and mortality. Eur J Clin Invest 2021; 51: e13669.

99.

Althouse

Baker

Smits

, et al. Racial inequality in COVID-treatment and in-hospital length of stay in the US over time. Front Public Health 2022; 10: 1074775.

100.

Gottlieb

Ziegler

Morley

, et al. Assessment of racial and ethnic differences in oxygen supplementation among patients in the intensive care unit. JAMA Intern Med 2022; 182: 849–858.

101.

Bressman

Werner

Childs

, et al. Association of telemedicine with primary care appointment access after hospital discharge. J Gen Intern Med 2022; 37: 2879–2881.

Supplementary Material

Please find the following supplemental material available below.

For Open Access articles published under a Creative Commons License, all supplemental material carries the same license as the article it is associated with.

For non-Open Access articles published, all supplemental material carries a non-exclusive license, and permission requests for re-use of supplemental material or any part of supplemental material shall be sent directly to the copyright owner as specified in the copyright notice associated with the article.

0.00 MB

0.04 MB