In the previous session, we learned about the ways in which Telehealth technologies have strong potential to promote health equity. However, it is important to have awareness of the fact that the benefits achieved from use of telehealth might not be received equitably across diverse populations. We must recognize and evaluate the possibility that our technological interventions are effective at improving care and health outcomes. That they work better for those individuals who are already better off than their counterparts. This concept is referred to as intervention generated inequality. In this session, we'll discuss the potential unintended repercussions of use of telehealth, especially as it relates to vulnerable populations. Our objectives for this session are to understand that telehealth technologies have potential to promote health equity. To recognize telehealth limitations and equitably benefiting diverse populations and to recognize telehealth possible unintended consequences of exacerbating existing disparities. So why are we talking about telehealth equity? Why does it matter? We must first acknowledge that telehealth use is not a health outcome rather it's a tool. But as health providers, policymakers, researchers or consumers, it is important to ensure that diverse groups can equitably access and utilize telehealth. So that all can have equal opportunity to benefit from this health resource. As technological tools have increasingly become incorporated into our everyday lives. We have seen differences in how technology is transforming experiences for various populations differently. The term digital divide was conceived in the 1999 report by the National Telecommunications and Information Administration. That report highlighted that individuals living in rural areas were 50% less likely than their urban counterparts to have internet access. Black and Hispanic households were 60% less likely than non Hispanic white households to have internet access. And the level of education and internet usage were highly correlated. Only 6% of those with an elementary school education or less used the internet, while over 60% of those with four year college degrees used the internet. Decades later, recent data support that the digital divide persists. Individuals are increasingly using the internet to communicate with health professionals, to access their health records to research health information and to use electronic health monitoring services. However, this transformation of healthcare with increased internet use for health related activities is not rising equally for everyone. The National Technology Information Agency report on 2019 data found that those who use the internet for health-related activities tended to have higher incomes. More education and live in metropolitan areas, households with annual family incomes of $100,000 or more were more likely to use the internet for health related activities. Compared to those with lower annual family incomes. There was higher internet use to access medical records among households in metropolitan areas. And usage among different racial or ethnic groups showed that non Hispanic white households. And Asian households had substantially higher rates of internet use for health related activities relative to black. Hispanic and American Indian or Alaskan native households. Telehealth usage is on the rise and experts have raised concerns that the expanded use of healthcare related technology can exacerbate health care disparities for vulnerable populations. Research on telehealth equity has rapidly grown in the recent year and it has described aspects of telehealth that may limit the use in specific populations. Various recent research studies have described differences in telehealth access by different factors, including but not limited to age, race, ethnicity, language and insurance. Well, next share some examples with you and want to emphasize that these are just a few research studies among an ever expanding body of literature. Let's look at age. National claims data among Medicaid and children's health insurance program. Beneficiaries from 2020 suggests that telehealth services are highest among working age adults. Children follow that age group and last, the group that uses telehealth the least are the older adults. This pattern is shown in this figure here with the dark blue bars representing children. The medium blue representing ages 19 through 64 and the light blue representing age 65 and older. This figure comes from a study that used data from a large health system in New York city. This study describes characteristics of patients seeking Covid related care via telehealth. The emergency department or the office. The study found that race and ethnicity were significantly predictive of telehealth use in this figure. The blue line represents telehealth visits and data are represented by race and ethnicity categories. This figure shows that after controlling for age, language and comorbidities, White and Asian patients had higher predicted probabilities of using telehealth. Instead of the emergency department or the office. While black and Hispanic patients were most likely to use the emergency department than either telehealth or office visits. Similar patterns by race and ethnicity have been demonstrated in numerous other studies. For example, these forest plots come from a retrospective cohort study from March to May of 2020. At a large health system with six major referral centers and a catchment area encompassing parts of Pennsylvania and New Jersey. If you focus on the data within the red box, you can see that compared with white race, black race and Latin X ethnicity were associated with less telehealth use. And you can also see the difference in telehealth use by language, having non English language as the preferred language was independently associated with less telehealth use. And having public insurance compared with having commercial insurance was also independently associated with less telehealth use. Finally, lower household incomes were associated with less telehealth use compared with higher household incomes. While more and more research is conducted that examines differential uptake of telehealth. We should try to measure this differential uptake using additional variables such as those on the slide. There are numerous other social determinants of health that should be investigated, some of which include racial segregation, educational attainment. Sexual orientation, gender identity, lived gender income, occupation, employment status, food insecurity, housing, immigration status, social support and cultural preference. It's another variable to examine, patients should retain the right to choose their preferred mode of service delivery. And if we are providing patient center care, we need to provide care that is respectful of and responsive to individual preferences, needs and values and last trust. Trust is another variable to examine is trust or mistrust in technology associated with differential uptake of telehealth. And what about trust or mistrust in the health care industry, and thus telehealth by extension.