There are interesting differences in the ways patients of varying ethnicities and races engage with technology.
Data released by the U.S. Department of Health and Human Services shows massive boosts in the use of telehealth during the COVID-19 pandemic.[i] Our digital health company, Pack Health, also saw a surge in the use of our telehealth options over the last two years, including one-to-one health coaching.
Research has found that these services enhanced the ability to provide safe and timely care to high-risk and marginalized populations during the pandemic.[ii] Yet, certain data reported interesting differences in the ways patients of varying ethnicities and races engage with technology.
As an example, one study found that certain individuals were less likely to use telehealth services during the pandemic due to a digital divide (a gap between demographics with access to technology and those without it[iii]), with Black patients 35% less likely to use it and Hispanic patients 51% less likely when compared to their White counterparts.[iv] With so many differing reports available, we were eager to obtain more information.
Specifically, we were after answers to one important question with far-reaching healthcare impacts: how do members of varying groups engage, and how does the different methods they use impact their care?
Taking a closer look at the ways racial and ethnic groups engage
At Pack Health, our members receive digital coaching services from one of our Health Advisors, who support each patient in accomplishing their health goals over a 12-week period. Pack Health members and their Health Advisors communicate weekly via emails, text messages or phone calls on goal setting, condition-specific resources and to provide support.
To uncover discrepancies in the ways members of differing races and ethnicities interact with health coaches and digital technologies, over 19,000 individuals participating in a Pack Health program were examined for similarities and differences in how they engaged with our programming. These behaviors were also compared to their post-intervention health outcomes, including patient-reported outcome data.
Patients were asked to self-identify their race and ethnicity. In recent guidance, the American Medical Association acknowledges these concepts are social constructs with important sensitivities that must be considered when used in medical and health research, education and practice,[v] something we were careful to consider when examining our results. Our research revealed several interesting findings.
First, Black or African American members, who made up 31% of our sample size, seemed to prefer to engage in different methods than other groups. While these members spent less time on their weekly call with their Health Advisor than others, they had the highest overall number of touchpoints, and indicated a preference for digital check-in methods.
Notably, one of the main differences in the Black member population when compared to others was a wage disparity, which was substantially lower in this group. Differing circumstances related to work and employment may have necessitated more flexibility, and thus a preference for a certain communication type. As a result of these frequent touchpoints, Black or African American members saw the highest improvement (an 11% increase) in medication adherence scores.
Overall, members of two or more races (2% of the sample size) had the greatest engagement across mediums and saw the largest improvement in their physical health scores, shifting them categorically from ‘fair’ to ‘good’ over the course of the 12-week period. Additionally, this highly engaged population also saw a substantially better improvement in their stress scores (27%) when compared to other populations (11% for White members, 11% for Black members and 18% for Asian members). It is possible these results are due to the methods with which Pack Health delivers resources and motivational tools, which are disseminated primarily via digital channels.
Another overall finding indicated that White members spent the most time on the phone with their Health Advisor and saw the highest improvement in their mental health scores. Data shows these patients moved their mental health score from 46.9 to 49.9, nearly reaching the average for a typical U.S. adult (50, according to PROMIS Global 10 scoring), and categorically shifting from ‘good’ to ‘very good.’ One explanation for these scores may be the large amounts of time this population spent on the phone with their Health Advisors, who provided a listening ear for any thoughts weighing heavily on their minds.
Leveraging data to broaden access and engage patients
Understanding and embracing the ways different patient groups engage is vital to providing the best care. Additionally, by considering the differences that may exist between varying groups, we can ensure access to digital and telehealth services are more equitable and available. Examining the preferences and outcomes among different member identities is vital to ensuring members are consistently engaged in ways that align with their preferences, keeping them on track to meet their health goals.
We know that keeping patients engaged in their healthcare is important. Studies have shown that patients who are more engaged with their providers are more proactive, meaning they may be more likely to schedule check-ups, stay up to date on their health care and have testing done on schedule, likely leading to better health outcomes.[vi]
By identifying potential disparities to access, programs like ours can tailor outreach and services to meet members where they are. This way, unique needs are addressed, and participants are more likely to continue the path to better health. Additionally, by offering education and training that teaches patients the digital skills needed to access these resources, digital literacy and other barriers to resources can be overcome, though programs should also consider the benefits to providing resources like telephone calls and touchpoints that can be accessed via any device – no smartphone necessary.
Finally, we must all consider policy changes that can enable increased access for patients regardless of their social determinants of health, including things like the expansion of low-cost or free internet access and the development of digital infrastructure for federally qualified community health centers.[vii]
As the path to traditional healthcare continues to evolve while the world grapples with the ever-present threat of COVID-19, digital technologies will remain a large part of patient care. By combining insights into virtual visits with engagement data, we can ensure patients receive the tailored approach that will make managing their chronic conditions easier.
Mazi Rasulnia, PhD, MPH, MBA, is the founder of Pack Health, which was acquired by Quest Diagnostics in 2022. In his current role as Vice President, Mazi furthers Pack Health’s mission of helping clinicians and healthcare organizations efficiently and effectively empower patients to become better managers of their own diseases. Mazi obtained his MPH and MBA in Health Care Policy and Management, as well as his PhD of Health Administration and Health Services Research at the University of Alabama at Birmingham.
[ii] Campos-Castillo C, Anthony D. Racial and ethnic differences in self-reported telehealth use during the COVID-19 pandemic: a secondary analysis of a US survey of internet users from late March. J Am Med Inform Assoc. 2021 Jan 15;28(1):119-125. doi: 10.1093/jamia/ocaa221. PMID: 32894772; PMCID: PMC7499625.
[iv]Adepoju, O.E., Chae, M., Ojinnaka, C.O. et al. Utilization Gaps During the COVID-19 Pandemic: Racial and Ethnic Disparities in Telemedicine Uptake in Federally Qualified Health Center Clinics. J GEN INTERN MED 37, 1191–1197 (2022). https://doi.org/10.1007/s11606-021-07304-4
[v] Flanagin A, Frey T, Christiansen SL, AMA Manual of Style Committee. Updated Guidance on the Reporting of Race and Ethnicity in Medical and Science Journals. JAMA. 2021;326(7):621–627. doi:10.1001/jama.2021.13304
[vi] Hibbard, J. H., & Greene, J. (2013). What the evidence shows about patient activation: Better health outcomes and care experiences; fewer data on costs. Health Affairs, 32(2), 207–214. https://doi.org/10.1377/hlthaff.2012.1061