On March 17, 2020, the Department of Health and Human Services expanded telemedicine access for the coronavirus disease 2019 (COVID-19) pandemic by adopting payment parity for video telemedicine, authorizing reimbursement for telemedicine visits received in a patient’s home and in any area of the country, waiving requirements for health insurance portability and accountability act-compliant communication platforms, and allowing providers to reduce or waive cost-sharing for telemedicine.1–3 These policies were both designed to mitigate the spread of COVID-19 and ensure continued access to outpatient, ambulatory health care during the pandemic. On March 30, 2020, Medicare expanded payment parity to audio-only telemedicine (visits conducted via telephone with no visual component) to ensure that beneficiaries without access to camera-enabled devices (ie, smartphones, tablets, computers with web-cameras) and adequate internet would have access to telemedicine services during the pandemic.4
In the early months of the pandemic, there was a tremendous increase in the use of telemedicine among Medicare beneficiaries. Approximately 40% of primary care visits received by Medicare beneficiaries in April 2020 were provided via telemedicine (either through video-conferencing or audio-only) as compared with 0.1% in February 2020.5 A significant increase also occurred in audio-only telemedicine. Thirty percent of telemedicine visits provided to Medicare beneficiaries during the first 4 months of the pandemic were audio-only.6
While audio-only telemedicine may be key to ensuring that patients receive safe access to health care during the pandemic, there is a dearth of literature comparing audio-only telemedicine to video telemedicine or in-person care for primary care. While one trial found no difference between audio-only and video telemedicine in regards to physician communication behaviors and shared decision making, providers may miss visual clues and have increased difficulty developing rapport, especially with new patients, when telemedicine is audio-only.7–11 Audio-only visits have been found to be 7 minutes shorter and result in 1.2 less visit diagnoses than video telemedicine visits.12 Patients have reported lower satisfaction rates and comprehension rates with audio-only.13
The high rate of audio-only telemedicine use during the pandemic may be reflective of disparities in access to technology in the United States, frequently referred to as the digital divide. Although 73% of US residents have home broadband internet, there is a disparity in access with only 66% of Black, 63% of rural, and 61% of Hispanics.14 Twenty-five percent of Hispanics and 23% of Black adults are smartphone-dependent (ie, do not have home internet and use their smartphones to access the internet), compared with 12% of White adults.15 Studies examining patterns in audio-only telemedicine use in the early months of the pandemic found higher rates of audio-only among racial and ethnic minorities, lower income patients, and patients who require translation services. However, these studies used claims data and could not measure the contribution of personal access to technology.12,16–22
The high rate of audio-only telemedicine may also be related to provider capacity and adoption factors. Health care providers, particularly those caring for low-income patients and operating on slim margins, may have insufficient financial and administrative resources to expand their video telehealth capabilities.23 Leaders at New York City Health+Hospitals, the largest safety net provider in the United States, have relied heavily on audio-only telemedicine during the pandemic as patients often require significant assistance to use video telemedicine platforms.24 Between March and August 2020, only 3.4% of primary care appointments at California federally qualified health centers occurred via video. 48.1% of primary care visits were conducted in-person and 48.5% were conducted via telephone.25
This study aims to use a nationally representative sample of Medicare beneficiaries to investigate whether the high rate of audio-only telemedicine use during the COVID-19 pandemic is related to patient access to technology or provider behavior. This paper also aims to explore the characteristics of patients who were more likely to have been offered audio-only telemedicine, as opposed to video telemedicine, by their usual care providers.
METHODS
Sample and Dataset
We used the Medicare Current Beneficiary Survey (MCBS) COVID-19 Summer (March−June) and Fall (July−November) 2020 Supplement Public Use File (PUF).26 The 2 COVID-19 supplements were 15-minute phone surveys administered to beneficiaries already enrolled in the MCBS. The MCBS uses a 3-stage cluster sample design and utilizes survey weights to obtain a national representative sample of Medicare beneficiaries and account for nonresponse bias.27
The goal of the COVID-19 supplement was to begin to understand the impact of the COVID-19 pandemic on Medicare beneficiaries. While there is overlap between the participants in the 2 surveys, participants received different identification numbers in the 2 PUFs and cannot be linked. There were 11,114 participants in the summer survey and 9686 participants in the fall survey. This analysis is limited to beneficiaries with usual care providers (Summer=10,604, Fall=9686).
This study focuses on beneficiaries who were offered a telemedicine appointment by their usual care provider to replace a regularly scheduled appointment during the pandemic (Summer=3484, Fall=2720). In 3375 (96.9%) summer surveys and 2633 (96.8%) fall surveys, participants knew whether the telemedicine appointment offered was to be video, audio-only, or both. An additional 2 surveys were excluded from the fall round analytic sample due to unknown demographic data, hence the final analytic sample was 3375 in the summer and 2631 in the fall.
Variables
Dependent Variable
In the summer supplement, participants were asked if offered a telephone or video appointment to replace a regularly scheduled appointment by their usual care provider during the coronavirus outbreak. In the fall supplement, participants were asked if offered a telephone or video appointment as of July 1, 2020. If the participant responded affirmatively, they were asked if they were offered a telephone/audio-only visit, a video visit, or both. In this analysis, we compared participants who were exclusively offered audio-only visits to those offered a video visit and those offered both.
Independent Variables
Patient characteristics included age, sex, race/ethnicity, primary English speaker, Medicare-Medicaid dual-eligibility, income <$25,000, metro status (population ≥50,000), region, a categorical variable of number of chronic conditions (0−1, 2−3, 4 or more), and a broad categorization of usual care provider type [physician office/medical clinic, managed care clinic, Veterans Administration (VA), or urgent care/emergency department].
Survey participants were asked about access to the following 4 technologies: (1) internet; (2) a smartphone; (3) a tablet; and (4) a desktop or laptop computer. The survey did not ask if the device was camera-enabled. We categorized beneficiaries into 4 technology groups listed from greatest to lowest ability to participate in video telemedicine: (1) smartphone or tablet owners with home internet access (may also have computer); (2) “smartphone dependent”—smartphone owners but no internet access (will need to use data or public Wi-Fi to receive in health services); (3) computer owners with home internet access but no smartphone or tablet (may not have a camera-enabled device); and (4) no home internet and no smartphone.
Data Analysis
As the survey was administered 2 times to roughly the same group of Medicare beneficiaries, we examined the data from each survey round separately. We used descriptive statistics, χ2 tests, and multivariable logistic regression and accounted for complex survey design to examine the characteristics of Medicare beneficiaries that were exclusively offered audio-only telemedicine by their usual care provider during the COVID-19 pandemic. Primary English speaker was excluded from the primary models due to its correlation with race/ethnicity and income was excluding due to its correlation with dual-eligibility. Models substituting race/ethnicity for language and income for dual-eligibility are available in the supplement. To disaggregate race/ethnicity from socioeconomic status (SES), we display models interacting race with dual-eligibility and race with metro status. We considered all P values <0.05 to be significant. All analyses were conducted in STATA/IC 15.1.
RESULTS
Access to Technology
In the fall survey (Fig. 1, Supplementary Table 1, Supplemental Digital Content 1, https://links.lww.com/MLR/C326), 71.5% of Medicare beneficiaries with usual care providers reported having access to the technologies necessary to participate in video telemedicine from their homes (internet and smartphone/tablet). An additional 11.3% reported having access to technologies that may allow for participation in video telemedicine from their homes (smartphone-dependence or access to a desktop/laptop computer with internet). Seventeen percent reported not having access to any technologies needed for telemedicine (no smartphone or no internet).
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FIGURE 1: Access to digital technologies by race/ethnicity among Medicare beneficiaries with usual care providers during the coronavirus disease 2019 pandemic, July−November 2020.
1,2 1: This figure includes all beneficiaries with usual care providers during the Fall survey round. This group of 9216 survey participants represents 52,663,158 beneficiaries. 2: See Supplementary Table 1 (Supplemental Digital Content 1,
https://links.lww.com/MLR/C326) for distribution during summer survey. There was a small increase (
P<0.01) in the percentage of beneficiaries who reported having a smartphone/tablet and internet access in the fall survey (71.5% vs. 70.0%) as compared with the summer survey.
Black (28%) and Hispanic (30%) beneficiaries were more likely to report no access to technologies required for telemedicine as compared with White beneficiaries (14%). Among beneficiaries with any access to technologies, Black (10.8%) and Hispanic (12.3%) beneficiaries were more likely to be smartphone-dependent (3.6% of White beneficiaries). In addition, beneficiaries who were over 75 years of age, chronically ill, dually eligible, low-income, not primary English speakers, nonmetro, and residents of the South and the Midwest were more likely to report not having access to any technologies (Supplementary Table 2, Supplemental Digital Content 1, https://links.lww.com/MLR/C326). Among those with access to any technologies, beneficiaries who were under 65 years of age, dually eligible, low-income, not primary English speakers, and residents of the Northeast and the South were more likely to be smartphone-dependent.
Access to Telemedicine
Among beneficiaries with usual care providers (Supplementary Fig. 1, Supplemental Digital Content 1, https://links.lww.com/MLR/C326), rates of being offered a telemedicine visit to replace a scheduled in-person visit were significantly higher (P<0.001) during the March−June period (34.13%) than the July−November period (30.92%).
The characteristics of the beneficiaries offered a telemedicine appointment to replace a scheduled in-person visit were significantly different from the population at large. Black (33.8%) and Hispanic (38.2%) beneficiaries were significantly more likely to be offered a telemedicine appointment to replace a scheduled in-person appointment as compared with White beneficiaries (29.3%) (Fig. 2, Supplementary Fig. 2, Supplemental Digital Content 1, https://links.lww.com/MLR/C326). They were also more likely to be young, chronically ill, dually eligible, low-income, not primary English speakers, VA care recipients, metro residents, west coast residents, and smartphone/tablet owners with internet access (Supplementary Table 3, Supplemental Digital Content 1, https://links.lww.com/MLR/C326).
FIGURE 2: Offers of telemedicine to Medicare beneficiaries by usual care providers during the COVID-19 pandemic, July−November 2020.
1 1: This figure includes all beneficiaries with usual care providers and telemedicine information in the fall survey. The sample for the fall survey was 9214 representing 52,652,319 beneficiaries. Data from the summer survey is available in Supplementary Figure 2 (Supplemental Digital Content 1,
https://links.lww.com/MLR/C326).
Audio-only Telemedicine
Among beneficiaries offered a telemedicine visit to replace a scheduled in-person visit, there was no difference (P=0.937) in the rate of those solely offered audio-only visits during the March to June period (35.2%) as compared with the July to August period (35.1%).
Among beneficiaries offered a telemedicine appointment to replace a scheduled in-person appointment between July and November (Table 1), the rate of audio-only telemedicine offers was higher among Medicare beneficiaries who were older (75 and over=40.0% vs. 65−74=32.4%, P=0.033), racial/ethnic minorities (Black=41.2%, Hispanic=52.9%, White=32.0%, P<0.001), dually eligible (48.8% vs. 32.3%, P<0.001), low-income (43.3% vs. 31.1%, P<0.001), nonprimary English speakers (48.3% vs. 33.1%, P<0.001), and nonmetro residents (45.0% vs. 33.3%, P=0.0027). Offers of audio-only telemedicine were higher among beneficiaries without access to telemedicine technologies. There were similar findings between March and June except for a higher rate of offers of audio-only telemedicine among VA (48.2%) and managed health care users (43.7% ) than doctor office/clinic users (34.1%, P=0.005) and greater differences between Black (50.1%) and White beneficiaries (35.1%, P<0.001).
TABLE 1 -
Exclusive Offers of Audio-only Telemedicine Among Medicare Beneficiaries Across Beneficiary Characteristics (March−November 2020)
|
|
March−June (n=3375; N=17,694,827) |
July−November (n=2631; N=15,769,800) |
| Variables |
Category |
% Offered Audio-only |
P
|
% Offered Audio-only |
P
|
| Age (y) |
<65 |
35.69 |
<0.001*** |
34.58 |
0.033* |
|
65−74 |
32.09 |
|
32.42 |
|
|
75+ |
40.55 |
|
40.01 |
|
| Sex |
Male |
36.94 |
0.076 |
35.67 |
0.636 |
|
Female |
33.72 |
|
34.55 |
|
| Race/ethnicity |
Non-Hispanic White |
31.88 |
<0.001*** |
31.95 |
<0.001*** |
|
Non-Hispanic Black |
50.07 |
|
41.23 |
|
|
Hispanic |
45.53 |
|
52.94 |
|
|
Other/unknown |
35.07 |
|
30.77 |
|
| No. chronic conditions†
|
0 or 1 conditions |
32.38 |
0.170 |
34.25 |
0.459 |
|
2 or 3 conditions |
35.78 |
|
34.30 |
|
|
>3 conditions |
37.10 |
|
37.48 |
|
| Dual eligible |
Not dual eligible |
33.57 |
<0.001*** |
32.32 |
<0.001*** |
|
Dual eligible |
44.13 |
|
48.84 |
|
| Income‡
|
$25,000 or more |
31.34 |
<0.001*** |
31.08 |
<0.001*** |
|
<$25,000 |
44.99 |
|
43.44 |
|
| English speaker |
Primary English speaker |
34.11 |
0.005** |
33.12 |
<0.001*** |
|
Not primary speaker |
42.60 |
|
48.27 |
|
| Usual care provider |
Medical office/clinic |
34.06 |
0.005** |
34.33 |
0.400 |
|
HMO/managed care clinic |
43.67 |
|
38.04 |
|
|
Urgent care/ER |
37.38 |
|
35.65 |
|
|
Veterans Administration Facility |
48.24 |
|
41.76 |
|
|
Other/unknown |
23.47 |
|
47.07 |
|
| Area type |
Metro |
33.55 |
0.003** |
33.27 |
0.007** |
|
Nonmetro |
43.24 |
|
44.99 |
|
| Region |
Northeast |
29.90 |
0.158 |
32.90 |
0.322 |
|
Midwest |
34.49 |
|
33.67 |
|
|
South |
38.12 |
|
38.14 |
|
|
West |
35.53 |
|
33.02 |
|
| Technology access |
Smartphone+internet |
29.78 |
<0.001*** |
30.00 |
<0.001*** |
|
Smartphone+no internet |
47.91 |
|
46.96 |
|
|
Computer only+internet |
44.00 |
|
42.77 |
|
|
No smartphone+no internet |
57.48 |
|
57.01 |
|
|
Unknown |
62.54 |
|
66.51 |
|
†Conditions list included hypertension, congestive heart failure, acute myocardial infarction, stroke, cancer, Alzheimer disease/dementia, depression, chronic obstructive pulmonary disease, and arthritis.
‡Income had a higher rate of missingness than the rest of the variables. The number of observations for income is 3253 in the summer round and 2528 in the fall round. Sample size is uniform for the rest of the variables.
ER indicates emergency room; HMO, health maintenance organization.
*P<0.05.
**P<0.01.
***P<0.001.
Findings remained significant in multivariable analysis (Table 2). Beneficiaries who are age 75 and older [adjusted odds ratio (AOR)=1.48, P=0.029], Hispanic (AOR=2.09, P<0.001), dual-eligible (AOR=1.63, P=0.002), and nonmetro residents (AOR=1.71, P=0.003) had significantly greater odds of being offer audio-only telemedicine between July and November. Beneficiaries with desktop or laptop computers only (AOR=1.66, P=0.004) and no access to the internet (AOR=2.35, P<0.001) also had significantly higher odds of being offered audio-only. Findings were similar between March and June except for a significantly higher odds of offers of audio-only telemedicine for Black beneficiaries (AOR=1.94, P<0.001) and VA users (AOR=1.69, P=0.014).
TABLE 2 -
Multivariable Logistic Regression Models Examining Exclusive Offers of Audio-only Telemedicine During the Coronavirus Disease 2019 Pandemic (March−November 2020)
|
|
March−June 2020 (n=3375; N=17,694,827) |
July−November 2020 (n=2631; N=15,769,800) |
| Variables |
Category |
OR (SE) |
P
|
OR (SE) |
P
|
| Age (y) |
<65 |
Reference |
Reference |
|
65−74 |
1.01 (0.13) |
0.968 |
1.20 (0.21) |
0.304 |
|
75+ |
1.21 (0.17) |
0.170 |
1.48 (0.26) |
0.029* |
| Sex |
Male |
Reference |
Reference |
|
Female |
0.89 (0.08) |
0.186 |
0.94 (0.11) |
0.581 |
| Race/ethnicity |
Non-Hispanic White |
Reference |
Reference |
|
Non-Hispanic Black |
1.94 (0.35) |
<0.001*** |
1.29 (0.26) |
0.209 |
|
Hispanic |
1.63 (0.25) |
0.002** |
2.09 (0.34) |
<0.001*** |
|
Other/unknown |
1.16 (0.24) |
0.472 |
0.94 (0.20) |
0.783 |
| No. chronic conditions |
0 or 1 conditions |
Reference |
Reference |
|
2 or 3 conditions |
1.11 (0.12) |
0.362 |
0.93 (0.11) |
0.521 |
|
>3 conditions |
1.02 (0.12) |
0.871 |
0.92 (0.13) |
0.586 |
| Dual eligible |
Not dual eligible |
Reference |
Reference |
|
Dual eligible |
1.14 (0.17) |
0.367 |
1.63 (0.25) |
0.002** |
| Usual care provider |
Medical office/clinic |
Reference |
Reference |
|
Managed care/HMO clinic |
1.47 (0.28) |
0.050 |
1.19 (0.26) |
0.446 |
|
Urgent care/ER |
1.17 (0.29) |
0.523 |
1.11 (0.27) |
0.677 |
|
Veterans Administration Facility |
1.69 (0.36) |
0.014* |
1.23 (0.24) |
0.305 |
|
Other/unknown |
0.53 (0.27) |
0.207 |
1.72 (0.80) |
0.246 |
| Area type |
Metro |
Reference |
Reference |
|
Nonmetro |
1.51 (0.21) |
0.003** |
1.71 (0.30) |
0.003** |
| Region |
Northeast |
Reference |
Reference |
|
Midwest |
1.17 (0.19) |
0.357 |
1.12 (0.22) |
0.555 |
|
South |
1.28 (0.21) |
0.135 |
1.27 (0.23) |
0.182 |
|
West |
1.26 (0.23) |
0.222 |
1.00 (0.17) |
0.978 |
| Digital access |
Smartphone/tablet+internet |
Reference |
Reference |
Reference |
|
Smartphone only |
1.70 (0.49) |
0.071 |
1.61 (0.45) |
0.089 |
|
Computer only+internet |
1.77 (0.26) |
<0.001*** |
1.66 (0.29) |
0.004** |
|
No smartphone+no internet |
2.69 (0.34) |
<0.001*** |
2.35 (0.32) |
<0.001*** |
|
Unknown |
3.33 (2.10) |
0.057 |
3.14 (0.82) |
0.082 |
| Constant |
|
0.27 (0.05) |
<0.001 |
0.26 (0.05) |
<0.001*** |
ER indicates emergency room; HMO, health maintenance organization.
*P<0.05.
**P<0.01.
***P<0.001.
Primary language was not included in the primary model due to its correlation with race: 62.5% of nonprimary English speakers were identified as Hispanic (Supplementary Table 4, Supplemental Digital Content 1, https://links.lww.com/MLR/C326). When substituting primary language for race (Supplementary Table 5, Supplemental Digital Content 1, https://links.lww.com/MLR/C326), nonprimary English speakers had significantly higher odds of audio-only telemedicine offers (AOR=1.85, P<0.001). Income was also not included in the primary model due to its correlation with dual-eligibility: 95% of dual-eligible had a household income of <$25,000. When substituting income for dual-eligibility, income was not significant (Supplementary Table 6, Supplemental Digital Content 1, https://links.lww.com/MLR/C326). When interacting race and dual-eligibility (Table 3, Supplementary Table 7, Supplementary Digital Content 1, https://links.lww.com/MLR/C326), the interaction term between Hispanic and dual-eligible was significant (P=0.024); the predictive probability of Hispanic dual-eligibles being offered audio-only telemedicine was 69% as compared with 34% for White non−dual-eligibles. When interacting race and metro-status (Table 3, Supplemental Table 8, Supplementary Digital Content 1, https://links.lww.com/MLR/C326), the interaction term between Black and metro status was also significant (P=0.025); the predictive probability of Black nonmetro residents being offered audio-only telemedicine was 73% as compared with 33% for White metro residents and 36% for Black metro residents.
TABLE 3 -
Multivariable Models Interacting Race/Ethnicity With Dual-eligibility and Metro Status (Fall Survey; n=2631; N=15,769,800)
†
| Model |
Variables |
Category |
OR (SE) |
P
|
Predictive Margins |
| Model interacting race/ethnicity with dual-eligibility |
Dual eligible |
Not dual eligible |
Reference |
35.12% (1.54%) |
|
|
Dual eligible |
1.32 (0.28) |
0.197 |
43.18% (37.70%) |
|
Race/ethnicity |
Non-Hispanic White |
Reference |
33.73% (1.66%) |
|
|
Non-Hispanic Black |
1.39 (0.32) |
0.146 |
41.04% (4.91%) |
|
|
Hispanic |
1.58 (0.32) |
0.024* |
43.97% (4.47%) |
|
|
Other/unknown |
0.86 (0.24) |
0.593 |
30.69% (5.56%) |
|
Dual eligible×race/ethnicity |
Non-Hispanic White×dual |
Reference |
|
39.85% (4.65%) |
|
|
Non-Hispanic Black×dual |
0.90 (0.32) |
0.765 |
45.05% (5.45%) |
|
|
Hispanic×dual |
2.25 (0.56) |
0.018* |
68.82% (4.51%) |
|
|
Other/unknown×dual |
1.54 (0.83) |
0.429 |
46.37% (9.52%) |
| Model interacting race/ethnicity with metro status |
Area type |
Metro |
Reference |
34.40% (1.50%) |
|
|
Nonmetro |
1.64 (0.29) |
0.007** |
45.38% (3.66%) |
|
Race/ethnicity |
Non-Hispanic White |
Reference |
43.64% (3.73%) |
|
|
Non-Hispanic Black |
1.18 (0.26) |
0.449 |
73.01% (9.52%) |
|
|
Hispanic |
2.11 (0.35) |
<0.001*** |
36.01% (1.65%) |
|
|
Other/unknown |
0.97 (0.21) |
0.878 |
38.57% (1.22%) |
|
Area type×race/ethnicity |
Non-Hispanic White×metro |
Reference |
32.66% (1.74%) |
|
|
Non-Hispanic Black×metro |
3.14 (1.58) |
0.025 |
36.22% (4.41%) |
|
|
Hispanic×metro |
0.34 (0.26) |
0.168 |
49.62% (3.70%) |
|
|
Other/unknown×metro |
0.83 (0.48) |
0.746 |
31.95% (4.41%) |
†Model controls for covariates, including access to technology. Full models shown in Supplementary Tables 7 and 8 (Supplemental Digital Content 1,
https://links.lww.com/MLR/C326).
*P<0.05.
**P<0.01.
***P<0.001.
DISCUSSION
Among patients who were offered telemedicine to replace scheduled in-person visits during the COVID-19 pandemic, ~35% were exclusively offered audio-only telemedicine options. The rate of exclusive provision of audio-only telemedicine did not decrease as the pandemic ensued and general comfort with teleconferencing technologies grew. This study also found that Black, Hispanic, dual-eligible, nonprimary English speaking, and nonmetro Medicare beneficiaries were more likely to be offered audio-only appointments during the pandemic. Beneficiaries at the intersections of these groups (Hispanic dual-eligible and Black nonmetro) were found to have even higher odds of being exclusively offered audio-only telemedicine.
Previous studies have shown that low-income, non-White, limited english proficiency (LEP), and rural patients have been less likely to receive video telemedicine during the pandemic.12,16–22 This study adds to the literature by highlighting that it is not just that disparity populations are opting to receive audio-only telemedicine due to lack of access to technologies or discomfort with telemedicine software,12,16–20 but that disparity populations are more likely to be exclusive offered audio-only telemedicine by their usual care providers. Currently, the effectiveness of audio-only telemedicine is unknown, so it is unclear if the disproportionate use of audio-only telemedicine will contribute to disparities in care outcomes.28 However, minority groups are often more difficult to engage in care and the use of audio-only telemedicine may exacerbate these difficulties.29 Patients may not seek services from their primary care physicians if they know that the appointment will be audio-only and the provider will not be able to see their problem. They might instead bring primary care concerns to the emergency room where providers will be available in-person or choose to delay health care services.30,31
While audio-only telemedicine is critical to ensuring that patients without personal access to technology maintain access to health care during the pandemic, 65.8% of Medicare beneficiaries who were exclusively offered audio-only telemedicine have access to smartphones/tablets and internet. This indicates that the use of audio-only telemedicine during the pandemic is only partially driven by patient access to technologies. Provider behavior and organizational factors likely play a large role in this phenomenon as well.32
Many providers may feel that they do not have the technological savvy to provide care via video telemedicine. However, numerous case reports have highlighted that practices are able to widely implement video telemedicine in a matter of days if they have the appropriate resources and institutional commitment.33,34 Alternatively, practices may feel that video telemedicine leads to wasted time; with video-conferencing, the provider needs to wait for the patient to show up in the conference room, while providers have the flexibility to call patients when using audio-only telemedicine. Patients who have access to necessary technologies may still lack the technological proficiency needed for many telehealth platforms. VA providers reported experiencing technical issues with 35% of their video visits and with only 11% of their phone visits during Spring 2020.11
As has been found in studies of other health information technologies, small private practices, rural practices, and predominantly Medicaid practices may not have the organizational resources to adopt the technologies necessary for video telemedicine and are opting to exclusively use audio-only.35,36 Providers that care for low SES patients or practice in low SES and rural communities may also have felt that investing in telemedicine technologies (including web-cameras, subscription to telemedicine platforms, telemedicine integration with other health information technologies) is not worth the costs due to lower rates of device ownership and high-speed internet in their patient panels as well as uncertainty around the amount of time that telemedicine would be reimbursed by insurance companies and would be recommended for COVID-19 mitigation.15 A Dallas-based obstetrics clinic that cares predominantly for a medically indigent population reported choosing to only implement audio-only telemedicine during the first wave of the pandemic based on an estimation that the majority of their “patients would not have access to high-speed internet” as well as the “lack of hardware infrastructure for video-conferencing within the clinics.”37 Research is needed to identify the organizational factors contributing to exclusive use of audio-only telemedicine during COVID-19 to support adoption of video telemedicine before the next public health disaster.
The high rates of audio-only telemedicine offers among Hispanics and nonprimary English speakers may reflect the difficulty of using video telemedicine technologies with LEP populations. At the beginning of the pandemic, not all telemedicine platforms had multilingual user interfaces.24,38 Many still lack interfaces for commonly spoken languages in the United States. It was also difficult to use remote interpretation call services, like LanguageLine, through video-telemedicine platforms.39,40 These barriers may also explain why LEP patients were significantly less likely to receive any type of telemedicine before the pandemic.41 In October 2020, telemedicine platform doxy.me announced a partnership with LanguageLine to allow for integrated medical interpretation through the platform.42 Other remote interpreting services are working to ensure their translators can be integrated into all telemedicine platforms.38 Video telemedicine technologies for patients with LEP has progressed markedly during the pandemic and providers should re-evaluate their practice patterns in response to those advances.
There are still many Medicare beneficiaries without access to the technologies needed for video telemedicine. As these technologies have become increasingly intertwined with health care services, providers should include screening for internet access, camera-enabled personal devices, and digital literacy as part of routine social needs assessments. Health care providers should be aware of public programs that provide low-cost internet and smartphones, including the Lifeline program run by the Federal Communications Commission, to low-income Americans and be able to refer their patients to these programs when indicated.43,44
Policy Implications
Reimbursement for audio-only telemedicine was implemented with the plan that reimbursement for this service would cease at the end of the COVID-19 public health emergency. Legislation has been proposed to continue reimbursement parity for audio-only telemedicine after the COVID-19 emergency period.45 While maintaining reimbursement for audio-telemedicine may substantially increase access to health care services, especially in health care provider shortage areas, it is important to ensure that expanding this access does not reduce health quality and widen disparities in care. Policies aimed at maintain reimbursement for audio-only telemedicine must be pursued in tandem with policies to expand access to low-cost broadband internet and smartphones as well as policies designed to promote provider uptake of video telemedicine technologies, including ongoing funding of the COVID-19 Telehealth Program.46 Audio-only telemedicine should only be used when a patient truly does not have access to the technologies necessary for video telemedicine, not because a provider is not able to offer video telemedicine options.
There is concern that continued reimbursement for audio-only telemedicine could lead to an increase in Medicare expenditures; patients may need 2 visits (when a complete examination could not be conducted during the audio-only visit) to manage conditions that were previously treated by one in-person visit or providers may bill for telephone-delivered services that they formerly provided gratis (prescription refills, referrals).47,48 If providers do not waive cost-sharing requirements or cost-sharing waivers are not continued, patients may experience higher annual out-of-pocket costs. It is important that continued reimbursement for audio-only telemedicine should be limited to conditions that can be addressed appropriately via audio-only telemedicine and are truly substitutes for in-person visits. Currently, there is little evidence to support the use of audio-only telemedicine outside of mental health services for depression and anxiety.49,50 There is an urgent need for high quality research to identify the conditions that can be managed cost-effectively via audio-only telemedicine as audio-only may be an effective way to expand access to care for certain populations.
Limitations
The MCBS is a patient-reported survey and questions about telemedicine were not validated with providers. This study focused on whether a beneficiary was offered an audio-only telemedicine appointment and does not answer whether the beneficiary actually received an audio-only appointment. The MCBS COVID-19 supplement does not have any information about the reason for visit, which could influence the recommendation for audio-only. The geographic specificity of MCBS PUF is limited to region and metro versus. nonmetro, which prevents an exploration of community-level characteristics, like internet speed, health provider shortages, and SES. The MCBS also has very limited information on practice characteristics (size, ownership model, academic affiliation), which would contribute to the understand of provider-level factors that contributed to the use of audio-only telemedicine during the pandemic. This study is also limited to beneficiaries who have a usual source of care and reflects experiences with usual care providers. It does not reflect experiences with specialists, unless viewed by the patient as their usual source of care.
CONCLUSIONS
Telemedicine has been a key part of strategy to halt the spread of COVID-19 and prevent patients from delaying health services during the pandemic. However, not all Medicare beneficiaries currently have been able to access telemedicine during the pandemic. Policymakers ensure that all providers, especially those who serve low-income, minority, and rural populations, have the resources to adopt video telemedicine, while expanding programs that provide smartphones and internet to low-income Americans.
REFERENCES
1. Centers for Medicare and Medicaid Services. Medicare telemedicine health care provider fact sheet. Centers of Medicare and Medicaid Services. 2020. Available at:
www.cms.gov/newsroom/fact-sheets/medicare-telemedicine-health-care-provider-fact-sheet. Accessed January 17, 2021.
2. HHS Press Office. OCR Announces Notification of Enforcement Discretion for Telehealth Remote Communications During the COVID-19 Nationwide Public Health Emergency. Department of Health and Human Services. 2020. Available at:
www.hhs.gov/about/news/2020/03/17/ocr-announces-notification-of-enforcement-discretion-for-telehealth-remote-communications-during-the-covid-19.html. Accessed January 17, 2021.
3. HHS Office of Inspector General. HHS OIG Policy Statement on Practitioners That Reduce, Waive Amounts Owed by Beneficiaries for Telehealth Services During the COVID-19 Outbreak. Department of Health and Human Services. 2020. Available at:
www.oig.hhs.gov/fraud/docs/alertsandbulletins/2020/factsheet-telehealth-2020.pdf. Accessed March 6, 2021.
4. Center for Medicare and Medicaid Services. Trump Administration Issues Second Round of Sweeping Changes to Support U.S. Healthcare System During COVID-19 Pandemic. Center for Medicare and Medicaid Services. 2020. Available at:
www.cms.gov/newsroom/press-releases/trump-administration-issues-second-round-sweeping-changes-support-us-healthcare-system-during-covid. Accessed January 15, 2021.
5. HHS Press Office. HHS Issues New Report Highlighting Dramatic Trends in Medicare Beneficiary Telehealth Utilization amid COVID-19. U.S. Department of Health and Human Services. 2020. Available at:
www.hhs.gov/about/news/2020/07/28/hhs-issues-new-report-highlighting-dramatic-trends-in-medicare-beneficiary-telehealth-utilization-amid-covid-19.html. Accessed February 2, 2021.
6. Verma S. Early impact of CMS expansion of medicare telehealth during COVID-19. 2020. Available at:
https://www.healthaffairs.org/do/10.1377/hblog20200715.454789/full/. Accessed August 16, 2021.
7. Hammersley V, Donaghy E, Parker R, et al. Comparing the content and quality of video, telephone, and face-to-face consultations: a non-randomised, quasi-experimental, exploratory study in UK primary care. Br J Gen Pract. 2019;69:e595–e604.
8. Clay-Williams R, Baysari M, Taylor N, et al. Service provider perceptions of transitioning from audio to video capability in a telehealth system: a qualitative evaluation. BMC Health Serv Res. 2017;17:558.
9. Donaghy E, Atherton H, Hammersley V, et al. Acceptability, benefits, and challenges of video consulting: a qualitative study in primary care. Br J Gen Pract. 2019;69:e586–e594.
10. McKinstry B, Watson P, Pinnock H, et al. Telephone consulting in primary care: a triangulated qualitative study of patients and providers. Br J Gen Pract. 2009;59:e209–e218.
11. Connolly SL, Gifford AL, Miller CJ, et al. Provider perceptions of virtual care during the coronavirus disease 2019 pandemic. Med Care. 2021;59:646–652.
12. Schifeling CH, Shanbhag P, Johnson A, et al. Disparities in video and telephone visits among older adults during the COVID-19 pandemic: cross-sectional analysis. JMIR Aging. 2020;3:e23176.
13. Voils CI, Venne VL, Weidenbacher H, et al. Comparison of telephone and televideo modes for delivery of genetic counseling: a randomized trial. J Genet Couns. 2018;27:339–348.
14. Anderson M. Mobile Technology and Home Broadband 2019. Pew Research Center: Internet, Science & Tech. 2019. Available at:
www.pewresearch.org/internet/2019/06/13/mobile-technology-and-home-broadband-2019/. Accessed March 10, 2021.
15. Pew Research Center. Demographics of Mobile Device Ownership and Adoption in the United States. Pew Research Center: Internet, Science & Tech. 2019. Available at:
www.pewresearch.org/internet/fact-sheet/mobile/. Accessed April 21, 2020.
16. Pierce RP, Stevermer JJ. Disparities in use of telehealth at the onset of the COVID-19 public health emergency. J Telemed Telecare. [published online ahead of print October 21, 2020]. doi: 10.1177/1357633X20963893.
17. Rametta SC, Fridinger SE, Gonzalez AK, et al. Analyzing 2,589 child neurology telehealth encounters necessitated by the COVID-19 pandemic. Neurology. 2020;95:e1257–e1266.
18. Rodriguez J, Betancourt J, Sequist T, et al. Differences in the use of telephone and video telemedicine visits during the COVID-19 pandemic. Am J Manag Care. 2021;27:21–26.
19. Eberly LA, Kallan MJ, Julien HM, et al. Patient characteristics associated with telemedicine access for primary and specialty ambulatory care during the COVID-19 pandemic. JAMA Netw Open. 2020;3:e2031640.
20. Gilson SF, Umscheid CA, Laiteerapong N, et al. Growth of ambulatory virtual visits and differential use by patient sociodemographics at one urban academic medical center during the COVID-19 pandemic: retrospective analysis. JMIR Med Inform. 2020;8:e24544.
21. Drake C, Lian T, Cameron B, et al. Understanding telemedicine’s “new normal”: variations in telemedicine use by specialty line and patient demographics. Telemed J E Health. [published online ahead of print March 25, 2021]. doi: 10.1089/tmj.2021.0041.
22. Hsiao V, Chandereng T, Lankton RL, et al. Disparities in telemedicine access: a cross-sectional study of a newly established infrastructure during the COVID-19 pandemic. Appl Clin Inform. 2021;12:445–458.
23. Scott Kruse C, Karem P, Shifflett K, et al. Evaluating barriers to adopting telemedicine worldwide: a systematic review. J Telemed Telecare. 2018;24:4–12.
24. Lau J, Knudsen J, Jackson H, et al. Staying connected in the COVID-19 pandemic: telehealth at the largest safety-net system in the United States. Health Aff. 2020;39:1437–1442.
25. Uscher-Pines L, Sousa J, Jones M, et al. Telehealth use among safety-net organizations in california during the COVID-19 pandemic. JAMA. 2021;325:1106–1107.
26. Centers for Medicare and Medicaid Services. MCBS Public Use File. Centers for Medicare and Medicaid Services. 2021. Available at:
www.cms.gov/Research-Statistics-Data-and-Systems/Downloadable-Public-Use-Files/MCBS-Public-Use-File. Accessed January 17, 2021.
27. Medicare Current Beneficiary Survey. MCBS 2018 Methodology Report. Centers for Medicare and Medicaid Services. Available at:
www.cms.gov/files/document/2018-mcbs-methodology-report.pdf. Accessed February 18, 2021.
28. Keddem S, Agha AZ, Long JA, et al. Creating a toolkit to reduce disparities in patient engagement. Med Care. 2017;55(suppl 2):S59–S69.
29. Chan KS, Parikh MA, Thorpe RJ, et al. Health care disparities in race-ethnic minority communities and populations: does the availability of health care providers play a role? J Racial Ethn Health Disparities. 2020;7:539–549.
30. Bentler SE, Morgan RO, Virnig BA, et al. The association of longitudinal and interpersonal continuity of care with emergency department use, hospitalization, and mortality among medicare beneficiaries. PLoS One. 2014;9:e115088.
31. Findling MG, Blendon RJ, Benson JM. Delayed care with harmful health consequences—reported experiences from national surveys during coronavirus disease 2019. JAMA Health Forum. 2020;1:e201463.
32. Uscher-Pines L, Jones M, Sousa J, et al. The doctor will call me maybe: the uncertain future of audio-only visits and why we need them to address disparities. Health Affairs Blog. 2021. Available at:
https://www.healthaffairs.org/do/10.1377/hblog20210225.26462/full/. Accessed August 16, 2021.
33. Loeb AE, Rao SS, Ficke JR, et al. Departmental experience and lessons learned with accelerated introduction of telemedicine during the COVID-19 crisis. J Am Acad Orthop Surg. 2020;28:e469–e476.
34. Smith WR, Atala AJ, Terlecki RP, et al. Implementation guide for rapid integration of an outpatient telemedicine program during the COVID-19 pandemic. J Am Coll Surg. 2020;231:216.e1–222.e2.
35. Mack D, Zhang S, Douglas M, et al. Disparities in primary care EHR adoption rates. J Health Care Poor Underserved. 2016;27:327–338.
36. Rittenhouse DR, Ramsay PP, Casalino LP, et al. Increased health information technology adoption and use among small primary care physician practices over time: a national cohort study. Ann Fam Med. 2017;15:56–62.
37. Holcomb D, Faucher MA, Bouzid J, et al. Patient perspectives on audio-only virtual prenatal visits amidst the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) pandemic. Obstet Gynecol. 2020;136:317–322.
38. Wetsman N. Telehealth wasn’t designed for non-English speakers. The Verge. 2020. Available at:
www.theverge.com/21277936/telehealth-english-systems-disparities-interpreters-online-doctor-appointments. Accessed March 10, 2021.
39. Diamond LC, Jacobs EA, Karliner L. Providing equitable care to patients with limited dominant language proficiency amid the COVID-19 pandemic. Patient Educ Couns. 2020;103:1451–1452.
40. Linggonegoro DW, Sanchez-Flores X, Huang JT. How telemedicine may exacerbate disparities in patients with limited English proficiency. J Am Acad Dermatol. 2021;84:E289–E290.
41. Rodriguez JA, Saadi A, Schwamm LH, et al. Disparities in telehealth use among California patients with limited english proficiency. Health Aff. 2021;40:487–495.
42. Brown S. LanguageLine, doxy.me Integration Delivers Telehealth Interpretation. LanguageLine Solutions. 2020. Available at:
www.languageline.com/news/languageline-doxyme-integration-delivers-telehealth-interpretation. Accessed March 10, 2021.
43. Lifeline Program for Low-Income Consumers. Federal Communications Commission. 2012. Available at:
www.fcc.gov/general/lifeline-program-low-income-consumers Accessed December 21, 2020.
44. Garg A, Byhoff E, Wexler MG. Implementation considerations for social determinants of health screening and referral interventions. JAMA Netw Open. 2020;3:e200693.
45. Smith J, Cardenas T. Permanency for Audio-Only Telehealth Act. Vol H.R. 9035. 2020. Available at:
www.congress.gov/bill/116th-congress/house-bill/9035/text?r=4&s=1. Accessed January 17, 2020.
46. Federal Communications Commission. COVID-19 Telehealth Program. Federal Communications Commission. 2020. Available at:
www.fcc.gov/covid-19-telehealth-program. Accessed March 10, 2021.
47. Chernew M, Ginsburg P, Casalino LP, et al. Medicare Payment Advisory Commission. Public meeting, 2020. Available at:
http://www.medpac.gov/docs/default-source/meeting-materials/nov2020_medpac_transcript_sec.pdf?sfvrsn=0.
48. Thomson AJ, Chapman CB, Lang H, et al. Outpatient virtual visits and the “right” amount of telehealth going forward. Telemed J E Health. [published online ahead of print March 31, 2021]. doi: 10.1089/tmj.2020.0468.
49. Castro A, Gili M, Ricci-Cabello I, et al. Effectiveness and adherence of telephone-administered psychotherapy for depression: a systematic review and meta-analysis. J Affect Disord. 2020;260:514–526.
50. California Health Benefits Review Program (CHBRP). Background Brief: Telehealth-Current State of the Evidence. CHBRP. 2021. Available at:
https://chbrp.org/Telehealth%20Background%20Brief-%20FINAL.pdf. Accessed May 21, 2021.
