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Dr. Cullen Truett

The Gambit: Is Techquity Possible?

A priori: Assuming a logical outcome without actually observing it to be true (1)

A priori: Assuming a logical outcome without actually observing it to be true (1)

The critique a priori is commonly applied in medical literature. While a priori assumptions facilitate hypotheses and potentially solve problems in healthcare, they also risk ignoring or directly harming patients caught in a hypothesis’ blindspot. 

Techquity has become the a priori underpinning of the health tech industry. It refers to the idea that healthcare tech is a driver of equitable care when designed appropriately (2). The COVID-19 pandemic amplified racial, ethnic, and socioeconomic disparities across the globe with people identifying as black, indigenous, and people of color dying at disproportionately high rates (3). In the US alone, health inequities contribute to the loss of over 200 million black life years due to lower life expectancy (4). Additionally, inequities contribute to a $42 billion loss in economic productivity per year (4).  The  Covid-19 pandemic drove demand for remote care combined with both the ethical and economic indictments of structural racism provided ample opportunity for health tech to market itself on the basis of health equity. 

From telemedicine/healthcare analytics targeting marginalized medicaid recipients to AI-supported platforms gamifying healthcare access for hard to reach populations, there is no shortage of tech arguing its place in the fight for health equity (5,6). However, there is a simplicity and optimism to the health tech gambit that obscures the risks and potential exacerbation of injustice health startups may inadvertently impose.These risks come in two broad forms: the nature of venture capital itself and the dangers of big data.

Cullen Techquity Application of Health Tech to Address health Disparities

Image 1: Summary of Techquity and health inequities it may arguably address (2,3,4)

Venture Capital

Health startups are built on the premise that good healthcare and good business are synonymous. Yet, good business means increased profit for investors or shareholders and requires funding dependent on the market whims (7,8). The very market that underwrites venture capital funding of startups also shapes the social inequalities that drive health disparities. Take for example the Great Recession of 2008, driven by housing speculation and reckless mortgage financing (9). Analyses of health outcomes resulting from the crisis noted globally worse morbidity, mortality, and mental health measures with low income and minority communities suffering the most (10,11). While a recession may be the most acute and obvious example, the disparities created in order to amass capital are globally repeated and insidious (11).

Some argue that with a committed mission, health startups provide counterbalance to the inequities of the current world economic system. However, from 2021-2022, the total value of digital health startups shrunk to $21 billion from a peak valuation of $30 billion (12,13). This contraction is driven by the gap between the measures of success in the startups and those in healthcare. Startups advance by fundraising and valuation accomplished on a relatively finite timeline. Financial benefit for venture capitalists is most significant when a startup is acquired by another company or made available for public trading. Conversely, health outcomes are nuanced and incremental, occurring on a scale beyond the patience of investors (14). Thus, innovation and reach for ambitious health outcomes are compromised by investors seeking their returns.

The Data Dilemma

All health tech companies rely on some form of collecting and interpreting data and using it to improve outcomes and access to care. Yet, even the most seemingly objective data has the potential for significant bias. This is especially true with the rising use of artificial intelligence (AI) in health tech (15).

While startups have collected massive repositories of health and personal data, AI relies on the algorithms we feed it to interpret and utilize that data, exposing them to the implicit bias and racism that already pervades our health systems (16). For example, an AI designed to assist physicians with assessment and plans was more likely to label physically agitated African American patients as violent compared to white patients and even recommended police involvement or jail (17,18). 

While startups often argue that better data collection mitigates such bias, this fails to recognize the historic weight and insidious nature of assumptions used to build treatment algorithms. Case in point, much of our knowledge base regarding risk management of cardiovascular disease is based on The Framingham Heart Study. Although it was one of the largest and longest studies of cardiovascular risk factors, its sample consisted of an 80% white population, performing poorly in assessing risk for African American patients(19). Consequently, efforts to only examine present data collection without considering historical data inequities risks continuing to amplify health injustice.

Just as concerning as the misinterpretation of data is the potential theft of data. In 2021 alone, 45 million patients had their protected health information accessed inappropriately and the Washington Post recently reported on an incident in which identifiable health data used in training AI was temporarily accessible to the public via Google search (20, 21). Exposure of personal data not only violates a patient’s right to privacy, but could incur a significant financial burden, further widening both financial and health inequities.


Health inequities are the result of centuries of injustices and deliberate exclusion of communities across the globe. The unequal distribution of capital and hyperaccumulation of wealth suggests that inequality may be an inherent characteristic of capitalism itself. It’s clear that our current healthcare practices are failing to meet the World Health Organization’s stated goals for health equity, and the excitement and rapid innovation of health tech offers hope in a stagnant present of healthcare delivery (22). While we must take pragmatic steps to further health equity, doing so necessitates a clear-eyed reckoning with the weight of history. This is not a call to reject health tech or the benefits reaped from startup innovation. Rather, it is a call to embrace innovation with an understanding of the economic and social forces that have afforded us this moment. It is imperative to regulate the industry to prioritize patients over profits and advocate the adoption of privacy protection and historically competent data collection (23).


  1. A priori. In: OED Online. Oxford University Press. Accessed June 10, 2023. https://www.oed.com/view/Entry/9943?redirectedFrom=a+priori#eid
  2. Rhee K, Dankway-Mullan I, Brennan V, Clark C. What is Techquity? Journal of Health Care for the Poor and Underserved 32. 2021;32(2). https://muse.jhu.edu/article/789652
  3. Vasquez Reyes M. The Disproportional Impact of COVID-19 on African Americans. Health Hum Rights. 2020;22(2):299-307.
  4. Joseph S. The “Techquity” Imperative: How Technology And Platforms Can Help Improve Health Equity. Forbes. Published online April 6, 2023. https://www.forbes.com/sites/sethjoseph/2023/04/06/the-techquity-imperative-how-technology-and-platforms-can-help-improve-health-equity/?sh=75acca7470cc
  5. Shah A, Karaca-Griffin S, Safavi K, Michel B, Thorn K, Blumberg A. US Health Inequities: Beyond the Statistics. Accenture; 2022:28. https://www.accenture.com/content/dam/accenture/final/industry/health/document/Accenture-Health-Equity.pdf#zoom=40
  6. Gliadkovskay A. AWS selects 10 startups for its 2022 Healthcare Accelerator, focused on health equity. Fierce Healthcare. Published online August 31, 2023. https://www.fiercehealthcare.com/health-tech/aws-announces-finalists-its-2022-health-equity-accelerator
  7. Kahloon I. Thomas Piketty Goes Global. The New Yorker. 2020;(March 9, 2020). https://www.newyorker.com/magazine/2020/03/09/thomas-piketty-goes-global
  8. Sell SK. 21st-century capitalism: structural challenges for universal health care. Global Health. 2019;15(Suppl 1):76. doi:10.1186/s12992-019-0517-3
  9. Coghlan E, McCorckell L, Hinkley S. What Really Caused the Great Recession? Instititute fore Research on Labor and Employment University of California Berkeley; 2018:6. https://irle.berkeley.edu/wp-content/uploads/2018/09/IRLE-What-Really-Caused-the-Great-Recession-1.pdf
  10. Margerison-Zilko C, Goldman-Mellor S, Falconi A, Downing J. Health Impacts of the Great Recession: A Critical Review. Curr Epidemiol Rep. 2016;3(1):81-91. doi:10.1007/s40471-016-0068-6
  11. Backhaus I, Hoven H, Di Tecco C, Iavicoli S, Conte A, Dragano N. Economic change and population health: lessons learnt from an umbrella review on the Great Recession. BMJ Open. 2022;12(4):e060710. doi:10.1136/bmjopen-2021-060710
  12. Stokes S. Digital-health investing is in free fall — but early-stage deals are still a bright spot in the industry. Business Insider. Published online July 2022. https://www.businessinsider.com/digital-health-investing-startups-tech-vc-second-quarter-2022-7
  13.  Li J. The Viability Of The Digital Healthcare Sector In 2023. Forbes. Published online June 15, 2023. https://www.forbes.com/sites/forbestechcouncil/2023/06/15/the-viability-of-the-digital-healthcare-sector-in-2023/?sh=209286fe48a4
  14. Padmanabhan P. Why Digital Health Startups Are Struggling To Gain Traction And What They Can Do About It. Forbes. Published online August 11, 2022.
  15. Banja J. How Might Artificial Intelligence Applications Impact Risk Management? AMA J Ethics. 2020;22(11):E945-951. doi:10.1001/amajethics.2020.945
  16. Nicholson Price II W. Risks and Remedies for Artificial Intelligence in Health Care. Brookings Institute; 2019. https://www.brookings.edu/research/risks-and-remedies-for-artificial-intelligence-in-health-care/
  17. Shang H, Lu A, Abdalla M, Mcdermott M, Ghassemi M. Hurtful Words: Quantifying Biases in Clinical Contextual Word Embeddings. Proceedings of the ACM Conference on Health, Inference, and Learning. Published online April 4, 2020:16.
  18. Brumfiel G. Doctors are drowning in paperwork. Some companies claim AI can help. Shots: Health News from NPR. Published online April 5, 2023. https://www.npr.org/sections/health-shots/2023/04/05/1167993888/chatgpt-medicine-artificial-intelligence-healthcare
  19. Garcha I, Phillips SP. Social bias in artificial intelligence algorithms designed to improve cardiovascular risk assessment relative to the Framingham Risk Score: a protocol for a systematic review. BMJ Open. 2023;13(5):e067638. doi:10.1136/bmjopen-2022-067638
  20. Landi H. HEALTH TECH Healthcare data breaches hit all-time high in 2021, impacting 45M people. Published online February 1, 2022. https://www.fiercehealthcare.com/health-tech/healthcare-data-breaches-hit-all-time-high-2021-impacting-45m-people
  21. MacMillan D, Bensinger G. Google almost made 100,000 chest X-rays public — until it realized personal data could be exposed. The Washington Post. https://www.washingtonpost.com/technology/2019/11/15/google-almost-made-chest-x-rays-public-until-it-realized-personal-data-could-be-exposed/. Published November 15, 2019.
  22. Social Determinants of Health. World Health Organization; 2021:4. https://apps.who.int/gb/ebwha/pdf_files/WHA74/A74_R16-en.pdf
  23. Matias JN. AI Policy Will Fail Society Without Community Science. Citizens and Tech Lab. Published online June 2023. https://citizensandtech.org/2023/06/ntia-submission-06-2023
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The mission of the Boston Congress of Public Health Thought Leadership for Public Health Fellowship (BCPH Fellowship) seeks to: 

  • Incubate the next generation of thought leaders in public health;
  • Advance collective impact for health equity through public health advocacy; and
  • Diversify, democratize, and broaden evidence-based public health dialogue and expression.

It is guided by an overall vision to provide a platform, training, and support network for the next generation of public health thought leaders and public scholars to explore and grow their voice.