Sonia Sarkar

Recently, the Techquity for Health Coalition, a group of healthcare companies, policy experts, and researchers, launched an effort to highlight and address inequities in the health technology industry.¹ In theory, tech solutions such as disease management apps and wearable devices make users' and care providers' lives easier. In practice, these technologies can worsen inequities—and introduce new ones—particularly for marginalized communities already subject to harmful practices such as data surveillance.²

The announcement follows a report published last spring by Ipsos and the HLTH Foundation, the coalition's backbone organization.³ The report includes insights from interviews with industry stakeholders and outlines opportunities and risks inherent to the growing health technology industry, which received nearly $40 billion in investment in 2021.⁴ In it, the authors note technology's increasing influence on health outcomes, sharing that an individual's access to education, employment, or even food—all key determinants of health—is significantly reliant on their ability to use and access technology.

In the past decade, due to changing health policies and financial incentives, health systems are increasingly acknowledging patients' social needs and implementing technology platforms to address them. For example, when a patient comes into the doctor's office, they are screened for social needs such as food and housing insecurity and employment needs. If a need is found, the patient's care team integrates this information into their care plan. They might discuss the issue with the patient then use the technology platform to refer the patient to a food pantry or housing services, in the same way a referral to a specialist doctor takes place. Community‐based organizations providing these services receive these referrals, becoming part of a patient's care.

These new workflows, and the technologies to support them, represent an exciting advancement in healthcare. However, as healthcare institutions invest billions of dollars in those technologies, we have to look at the challenges presented by this shift. At the patient level, there are access and use barriers. A patient expected to view their community referral on a phone app might have limited internet or receive confusing guidance on how to use the app. Patients I've worked with have experienced unclear user interfaces, culturally insensitive information, or a lack of accessibility accommodations. Furthermore, having to interact with an app can create a sense of distrust and distance for patients, who may fear stigma or discrimination from their healthcare provider as they share sensitive information.

The Techquity for Health Coalition aims to address such barriers, particularly with regards to technology access and use and industry engagement. On the access front, for example, healthcare stakeholders could advocate for or directly finance broadband services and health technology devices. In terms of use, the report emphasizes human‐centric product development, including bringing members of underserved communities directly into product design and deployment. Ideas for industry engagement include diversifying the technology workforce, effective and transparent communication with patients and communities, and dedication of long‐term healthcare and technology dollars to achieving equity.

Systemic Risks Associated with Healthcare Technology

While improving technology adoption and workforce diversity are desired outcomes, there are three key ways that health technology can deepen inequities.

1. Data ethics. Healthcare institutions and private technology companies now store, own, and use sensitive individual data. What rights does a patient have to their own data and to understanding how it is being used or affecting their care?

   In the aftermath of the Supreme Court's decision to overturn Roe v. Wade, many advocates and patients I've worked with fear that data collected by cycle‐tracking apps, disease management platforms, and other healthcare data collection methods could be used to surveil and criminalize those seeking an abortion.

   Community leaders also point out the risk of technology companies aggregating and sharing data with their healthcare clients without any place‐based context or relationships. In previous roles where I've evaluated these companies and considered using them for local health initiatives, I've heard pitches promising population‐level data analytics that will supposedly enable healthcare stakeholders to figure out where to focus their community efforts. Most of the time, though, these programs do not consider that the variables that affect a community's health are complex and specific—in ways that numbers rarely capture. Beholden to business models that emphasize scale and fast quantitative analysis, health technology companies can end up reinforcing biases about marginalized communities.⁵

2. Algorithm bias. Related to data ownership is the concern that data will be used to inform automated workflows and “flag” systems that profile patients with certain demographic characteristics.⁶ Taking the example of a patient getting screened for food or housing needs, a health technology algorithm could automatically flag a low‐income BIPOC patient as a “high‐risk” patient, independent of the patient's specific situation. This alert might trigger several actions in the system, such as the development of treatment recommendations.

   Indeed, racial bias is prolific across algorithms, with particular implications in healthcare: a 2019 study found a biased hospital algorithm that recommended specific treatments for Black patients only if they were significantly sicker than White people with the same health issue.⁷ For communities of color, women, LGTBQ+ communities, people with disabilities, and many more, algorithmic discrimination creates further layers of harm.

3. Investment and ownership. Health technology companies typically aren't reflective of the patient populations they hope will use their products. A 2020 report by Rock Health found that, as with technology as a whole, white and Asian founders are overrepresented in the health technology industry, while Black and Latinx founders were underrepresented.⁸ This is true on both the investor and entrepreneur sides of the equation, with significant impacts on financing: 57% of the surveyed Black women who had founded health technology firms reported bootstrapping their businesses, compared to 10% of surveyed white men.

   Financing inequity can also be seen in the introduction of new private‐sector companies into a publicly and privately funded health system, raising questions about how investments and profits are distributed. For example, community organizations that provide food and housing services are often asked to invest time and training capacity in order to participate in social‐needs platforms. This can be a burden on entities with limited capacity and funding, particularly in under‐resourced communities. Although these organizations are a crucial part of the advertised solution, they may not be a part of product design and development, nor are they entitled to any profits generated.

Activism to Address the Harms of Health Technology

As industry leaders turn their attention to the double‐edged sword of health technology, it remains to be seen how they will interact with activists' efforts to address these issues at the global and local levels.

One of those efforts, the 2019 conference, “Political Origins of Health Inequities: Technology in the Digital Age,” brought together policy makers and practitioners from across the globe to look at the impact of digital technology on health inequities. A special issue of Global Policy authored by conference attendees highlighted the need for “better transparency and public deliberation about digital health technologies as part of the broader political determinants of health … these spaces for debate and governance are key to ensuring that we do not blindly enter into social contracts regarding new technologies.”⁹

Community leaders are stepping into conversations on technology governance, pushing healthcare institutions to share power by incorporating individuals with lived experience of healthcare inequity into technology and data decision‐making. In San Diego, an effort is under way to develop a community‐driven, antiracist community information exchange model.¹⁰ The group involved, composed of community organizations, healthcare stakeholders, the local county health department, and United Way's 211 program, defines a community information exchange as a “community‐led ecosystem” of partners who take a shared and integrated approach to delivering community care. Unlike the process of screening a patient for social needs and referring them to a service, which reactively addresses patients' social needs, the CIE is intended to be proactive, identifying such needs ahead of time and centering patients' proposed ideas for addressing them. To achieve this, the organization is engaging and collaborating with community members in system design, as well as proposing accountability mechanisms for technology vendors that participate in the model.

Models such as this point to a crucial element of any industry effort to address inequities in health technology. Individuals and communities who have long experienced health inequities should have a seat at the table and should shape not only technology design and development but also sector‐wide standards surrounding those processes.