Why Black Investors Need to Invest in Healthcare AI Now
Joseph Kemp (JD/MBA, University of Michigan) *josephmk@umich.edu
Joseph Kemp (JD/MBA, University of Michigan) *josephmk@umich.edu
The intersection of artificial intelligence (AI) and healthcare is poised to revolutionize the way doctors serve patients, and the healthcare landscape in general. This is indicated by the record-breaking venture activity in the health space, specifically in AI, healthcare solutions, and healthtech over the last two years of 2018 and 2019 (1). These investments are disrupting the healthcare industry, which is exponentially growing (currently a ~$9 trillion dollar global industry), but there is a critical question to consider with the junction of AI and healthcare: How will it affect people in the near and long-term future? (2) Behind the veil, it seems like the technology will transform the industry in efficient and positive ways for all people. However, lifting the veil, people of color are often adversely affected. Without more diverse voices involved in the shaping of these technologies in their early stages, we will continue to face significant and profound healthcare AI biases. I argue the only way for this to change, now more than ever, is for African Americans to invest at the crossroads of AI and healthcare. Thanks to greater availability of verifiable information for diligence, a lack of industry knowledge is no longer a credible barrier to investment (3). The three reasons for this call to action are, again, 1) the VC industry has a heavy focus on this area with promising ROI's; 2) given the negative impact bias has on the African American community, the only way to change that is for more African Americans to have a voice at the table through their investment dollars; and 3) by getting in early and helping shape the technologies, one can identify and prevent the bias from seeping into the product, thus improving the solutions and outcomes for everyone.
As indicated by Silicon Valley Bank’s (SVB) Trends in Healthcare Investments and Exits 2019 report, record investments and fundraising continue in the healthcare space (4). The report reflects record-breaking trends in 2018, where $9.6 billion was invested -- also shattering previous years’ records. According to the 2018 report, United States and European VC investments surged 50%, IPOs doubled, and M&A activity increased in the healthcare industry. Moreover, returning to 2019 and dipping into the 2020 SVB Healthcare Investments & Exits Report that is still being generated, “US healthcare venture fundraising in 2019 set a record for the third consecutive year and US/Europe investment into venture-backed healthcare companies dipped only slightly from a year ago. Strong M&A and IPO performance led to significant mark-ups and returns in all four sectors – biopharma, medical device, diagnostic/tools and healthtech.”(5) This is a clear indication that the healthcare (and healthtech) space is where the smart money is going. Whether you are an expert in the industry or not, or just looking for a diversified portfolio, the intersection of diagnostics and artificial intelligence is an exciting area of investment, as well as impact. Given the focus and need for healthcare during this COVID-19 pandemic, the strength of this vertical continues to increase, it's importance is now more widely recognized, and returns are stronger than ever.
Coalescing performance in healthcare and advances in technology (especially artificial intelligence), we can see a powerful duo shaping up for success. For example, according to the PwC | CB Insights MoneyTree 2018 Q4 report, “AI-related funding significantly jumped last year, increasing 72% compared to 2017, despite a dip in deal activity, with 466 startups funded from 533 in 2017.”(6) In addition to that, AI startups raised a record $16.8 billion in 2018 worldwide, its best year ever at the time. According to CB Insights, AI funding broke its record in 2019 as well, hitting $26.6 billion(7). The number of AI unicorns ($1B+ valuations) have risen significantly: in 2017, there were 10, in 2018 there were 19, and in 2019 there were 24 (8). Moreover, if we follow the investing trends & M&A activity with some of the largest companies in the world like Google, Apple, Amazon, Microsoft, and Facebook (FAANG + M) whose acquisition rate is the highest of all verticals to expand, increase efficiency, and bolster their businesses and profits, examining their behavior further validates the value proposition of investing in this rapidly expanding area (9). Lastly, merging the two interests in this piece, healthcare and AI, funding and deal activity has also hit historic highs in 2018 for this combination, nearly doubling in the last two years (10). According to CB Insights, “in the private market, healthcare AI startups have raised $4.3B across 576 deals since 2013, topping all other industries in AI deal activity.” (11) It is clear by the investment and returns activity, this is one of the most promising areas of investment.
With all this explosive activity and development, AI is changing how we operate in all facets, especially in business and healthcare. However, as mentioned above, there is a critical impact we must be aware of and address. At the crossroad of AI and healthcare, there is a disproportionate effect on people of color, especially black people. AI analyzes and creates new solutions with the data that is inputted. In healthcare, the data collected from former and current patients is used to treat future patients. Of course, there are certain boxes that must be checked and distinctions because humans are unique, but we are grouped by race. Historical society, legal, and wealth gaps have (and will) bias the data, which result in negative health consequences exacerbating the current prejudices that affect populations of color (12). The AI algorithms feed off of the biased data and underestimate the number of people of color who are actually in need of greater care, just like doctors do with patients of color, especially those who are black (13). One major example is the mortality rate of black women during childbirth, which is 3x the rate of their white counterparts according to the CDC (14). Another example is that patients of color are less likely to receive pain management compared to white patients in emergency rooms (15). In fact, black patients were 40% less likely than white patients to receive pain management for similar levels of injury according to the American Journal of Emergency Medicine (16). These cognitive biases influence the data that is fed into the algorithm furthering the gap in diagnosis and treatment for people of color. Another real-life example concerns a widely used algorithm in the U.S healthcare system created by Optum that was studied and shown to exhibit significant racial bias (17). Tools like that of Optum purportedly affect 200 million people each year. “The algorithm used heath costs to predict and rank which patients would benefit the most from additional care designed to help them stay on medications or out of the hospital.” (18) Black patients were assigned the same level of risk by the algorithm though they were sicker than white patients, which led to the algorithm falsely concluding that black patients are healthier than equally sick white patients. According to the American Association for the Advancement of Sciences (AAAS), “the algorithm, [which] is typical of this industry-wide approach and [affects] millions [emphasis added] of patients, [exhibited] significant racial bias… [And] remedying this disparity would increase the percentage of Black patients receiving additional help from 17.7 to 46.5%.” (19) This increase is alarming to anyone, much less a black person as myself. This further reinforces the compelling reasons why it is important for people of color to have a role in shaping the technology that will affect us profoundly.
With more investment from communities of color, especially the black community, into healthcare AI, we can finally have a role in shaping this technology while benefiting from increased returns previously only enjoyed by a majority of the non diverse population. It is now easier than ever to diligence venture funds through data, existing investments, and other third party input, where you can invest your dollars to move the needle. (20) By investing as a Limited Partner (LP) in a smaller, more focused venture fund, you can ask questions and get familiar with the technologies in which the funds invests. Larger funds rarely have room for your money, much less the interest to accept anyone who's not a multi-billion dollar pension fund. This is a call to share your knowledge and money with the General Partners who invest it into their portfolio companies, where we can finally impact the outcomes. Engaging with the developers while they are creating their algorithms and testing the technology to insure there are no potential biases and if they exist, that they are addressed before going to market is the way to insure all individuals are created equal in the eye of the heathcare system. It is not necessary to have the expertise in venture investing or the vertical yourself anymore - there are plenty of data sources and independent valuations which more than satisfy the business of diligencing a new fund. If biases are addressed early, the companies will likely fare better in the long run – increasing ROI potential. If we put more money and time into the early stages of developing these life-changing technologies. then we can improve the outcomes for everyone, not to mention realizing market share and profits. Most important and more significantly, you are also making an impact with your money in this space for yourself and people like me.
Diversity of investors leads to diversity of fund managers which leads to diversity of entrepreneurs and solutions created for a diverse population. One way to target impact is to require a percentage of your money to go to diverse founders or companies. By making those investments, the necessary step of including answers into solutions of “how will/does this affect me?” will likely be considerations of the inventors and product creators. In summary, if you are concerned about the ability to shape the technology but lack the expertise, investing in a smaller fund is how you can bridge these gaps. According to Michele Colucci, Managing Partner of DigitalDx Ventures, smaller funds allow investors to be more engaged with portfolio investments and are more willing to include LP's in the learning process. “Unlike a lot of fund managers, I love it when our investors want to plan an active role in helping our companies succeed. It takes a lot of talent to build and scale these game-changing diagnostic companies and a diverse skill set is absolutely critical to their success.” (21) Equally important is the understanding that, while the larger deals are where the money is made, getting into those deals in the earlier stages allows one to play at a more affordable level and to learn and grow your knowledge. DigitalDx Ventures, an example of a smaller firm that meets these criteria, invests at crossroads of AI and healthcare/diagnostics. Most important, the data shows that smaller funds like these have higher returns than the larger ones (22). Investing in this area as an LP in a smaller fund is not only a catalyst for impact and change, but also for great returns.
This is the right time for diverse investors to put skin in the game. Healthcare AI, as well as patient care, is changing. These industries are seeing the most venture activity, which is increasing every year. This area is also in desperate need of informed and powerful people of color to help shape the technology in a way that is equitable, bias free, and accurate for people like us and generations to come while jumping in at a time of exponential growth and strong exits/ROIs. Those looking to diversify should take a serious look at small, vertical focused expert VC funds in these emerging areas. Money is power, and simple questions and proffered considerations could result in greater impact while also increasing ROI and exit potential. Now is the time for diverse investors to invest into healthcare AI. Not only are high returns possible, but large-scale impact is obtainable when you vote with your wallet.
As indicated by Silicon Valley Bank’s (SVB) Trends in Healthcare Investments and Exits 2019 report, record investments and fundraising continue in the healthcare space (4). The report reflects record-breaking trends in 2018, where $9.6 billion was invested -- also shattering previous years’ records. According to the 2018 report, United States and European VC investments surged 50%, IPOs doubled, and M&A activity increased in the healthcare industry. Moreover, returning to 2019 and dipping into the 2020 SVB Healthcare Investments & Exits Report that is still being generated, “US healthcare venture fundraising in 2019 set a record for the third consecutive year and US/Europe investment into venture-backed healthcare companies dipped only slightly from a year ago. Strong M&A and IPO performance led to significant mark-ups and returns in all four sectors – biopharma, medical device, diagnostic/tools and healthtech.”(5) This is a clear indication that the healthcare (and healthtech) space is where the smart money is going. Whether you are an expert in the industry or not, or just looking for a diversified portfolio, the intersection of diagnostics and artificial intelligence is an exciting area of investment, as well as impact. Given the focus and need for healthcare during this COVID-19 pandemic, the strength of this vertical continues to increase, it's importance is now more widely recognized, and returns are stronger than ever.
Coalescing performance in healthcare and advances in technology (especially artificial intelligence), we can see a powerful duo shaping up for success. For example, according to the PwC | CB Insights MoneyTree 2018 Q4 report, “AI-related funding significantly jumped last year, increasing 72% compared to 2017, despite a dip in deal activity, with 466 startups funded from 533 in 2017.”(6) In addition to that, AI startups raised a record $16.8 billion in 2018 worldwide, its best year ever at the time. According to CB Insights, AI funding broke its record in 2019 as well, hitting $26.6 billion(7). The number of AI unicorns ($1B+ valuations) have risen significantly: in 2017, there were 10, in 2018 there were 19, and in 2019 there were 24 (8). Moreover, if we follow the investing trends & M&A activity with some of the largest companies in the world like Google, Apple, Amazon, Microsoft, and Facebook (FAANG + M) whose acquisition rate is the highest of all verticals to expand, increase efficiency, and bolster their businesses and profits, examining their behavior further validates the value proposition of investing in this rapidly expanding area (9). Lastly, merging the two interests in this piece, healthcare and AI, funding and deal activity has also hit historic highs in 2018 for this combination, nearly doubling in the last two years (10). According to CB Insights, “in the private market, healthcare AI startups have raised $4.3B across 576 deals since 2013, topping all other industries in AI deal activity.” (11) It is clear by the investment and returns activity, this is one of the most promising areas of investment.
With all this explosive activity and development, AI is changing how we operate in all facets, especially in business and healthcare. However, as mentioned above, there is a critical impact we must be aware of and address. At the crossroad of AI and healthcare, there is a disproportionate effect on people of color, especially black people. AI analyzes and creates new solutions with the data that is inputted. In healthcare, the data collected from former and current patients is used to treat future patients. Of course, there are certain boxes that must be checked and distinctions because humans are unique, but we are grouped by race. Historical society, legal, and wealth gaps have (and will) bias the data, which result in negative health consequences exacerbating the current prejudices that affect populations of color (12). The AI algorithms feed off of the biased data and underestimate the number of people of color who are actually in need of greater care, just like doctors do with patients of color, especially those who are black (13). One major example is the mortality rate of black women during childbirth, which is 3x the rate of their white counterparts according to the CDC (14). Another example is that patients of color are less likely to receive pain management compared to white patients in emergency rooms (15). In fact, black patients were 40% less likely than white patients to receive pain management for similar levels of injury according to the American Journal of Emergency Medicine (16). These cognitive biases influence the data that is fed into the algorithm furthering the gap in diagnosis and treatment for people of color. Another real-life example concerns a widely used algorithm in the U.S healthcare system created by Optum that was studied and shown to exhibit significant racial bias (17). Tools like that of Optum purportedly affect 200 million people each year. “The algorithm used heath costs to predict and rank which patients would benefit the most from additional care designed to help them stay on medications or out of the hospital.” (18) Black patients were assigned the same level of risk by the algorithm though they were sicker than white patients, which led to the algorithm falsely concluding that black patients are healthier than equally sick white patients. According to the American Association for the Advancement of Sciences (AAAS), “the algorithm, [which] is typical of this industry-wide approach and [affects] millions [emphasis added] of patients, [exhibited] significant racial bias… [And] remedying this disparity would increase the percentage of Black patients receiving additional help from 17.7 to 46.5%.” (19) This increase is alarming to anyone, much less a black person as myself. This further reinforces the compelling reasons why it is important for people of color to have a role in shaping the technology that will affect us profoundly.
With more investment from communities of color, especially the black community, into healthcare AI, we can finally have a role in shaping this technology while benefiting from increased returns previously only enjoyed by a majority of the non diverse population. It is now easier than ever to diligence venture funds through data, existing investments, and other third party input, where you can invest your dollars to move the needle. (20) By investing as a Limited Partner (LP) in a smaller, more focused venture fund, you can ask questions and get familiar with the technologies in which the funds invests. Larger funds rarely have room for your money, much less the interest to accept anyone who's not a multi-billion dollar pension fund. This is a call to share your knowledge and money with the General Partners who invest it into their portfolio companies, where we can finally impact the outcomes. Engaging with the developers while they are creating their algorithms and testing the technology to insure there are no potential biases and if they exist, that they are addressed before going to market is the way to insure all individuals are created equal in the eye of the heathcare system. It is not necessary to have the expertise in venture investing or the vertical yourself anymore - there are plenty of data sources and independent valuations which more than satisfy the business of diligencing a new fund. If biases are addressed early, the companies will likely fare better in the long run – increasing ROI potential. If we put more money and time into the early stages of developing these life-changing technologies. then we can improve the outcomes for everyone, not to mention realizing market share and profits. Most important and more significantly, you are also making an impact with your money in this space for yourself and people like me.
Diversity of investors leads to diversity of fund managers which leads to diversity of entrepreneurs and solutions created for a diverse population. One way to target impact is to require a percentage of your money to go to diverse founders or companies. By making those investments, the necessary step of including answers into solutions of “how will/does this affect me?” will likely be considerations of the inventors and product creators. In summary, if you are concerned about the ability to shape the technology but lack the expertise, investing in a smaller fund is how you can bridge these gaps. According to Michele Colucci, Managing Partner of DigitalDx Ventures, smaller funds allow investors to be more engaged with portfolio investments and are more willing to include LP's in the learning process. “Unlike a lot of fund managers, I love it when our investors want to plan an active role in helping our companies succeed. It takes a lot of talent to build and scale these game-changing diagnostic companies and a diverse skill set is absolutely critical to their success.” (21) Equally important is the understanding that, while the larger deals are where the money is made, getting into those deals in the earlier stages allows one to play at a more affordable level and to learn and grow your knowledge. DigitalDx Ventures, an example of a smaller firm that meets these criteria, invests at crossroads of AI and healthcare/diagnostics. Most important, the data shows that smaller funds like these have higher returns than the larger ones (22). Investing in this area as an LP in a smaller fund is not only a catalyst for impact and change, but also for great returns.
This is the right time for diverse investors to put skin in the game. Healthcare AI, as well as patient care, is changing. These industries are seeing the most venture activity, which is increasing every year. This area is also in desperate need of informed and powerful people of color to help shape the technology in a way that is equitable, bias free, and accurate for people like us and generations to come while jumping in at a time of exponential growth and strong exits/ROIs. Those looking to diversify should take a serious look at small, vertical focused expert VC funds in these emerging areas. Money is power, and simple questions and proffered considerations could result in greater impact while also increasing ROI and exit potential. Now is the time for diverse investors to invest into healthcare AI. Not only are high returns possible, but large-scale impact is obtainable when you vote with your wallet.
(1) https://www.svb.com/trends-insights/reports/healthcare-investments-and-exits/2019-annual#downloadreport
https://www.forbes.com/sites/jeanbaptiste/2019/02/12/venture-capital-funding-for-artificial-intelligence-startups-hit-record-high-in-2018/#e999c1041f77
https://www.svb.com/globalassets/library/uploadedfiles/reports/healthcare-report-2020-annual_abr.pdf (See Page 6 & 7)
(2) https://policyadvice.net/health-insurance/insights/health-care-industry/
(3) This will be discussed later how you are still able to “invest in what you know” despite lacking deep industry knowledge and avoid Theranos-like situations.
(4) https://www.svb.com/trends-insights/reports/healthcare-investments-and-exits/2019-annual#downloadreport
(5) https://www.svb.com/trends-insights/reports/healthcare-investments-and-exits/2020-annual
(6) https://www.forbes.com/sites/jeanbaptiste/2019/02/12/venture-capital-funding-for-artificial-intelligence-startups-hit-record-high-in-2018/#e999c1041f77
(7) https://venturebeat.com/2020/01/22/cb-insights-ai-startup-funding-hit-new-high-of-26-6-billion-in-2019/
(8) https://venturebeat.com/2020/01/22/cb-insights-ai-startup-funding-hit-new-high-of-26-6-billion-in-2019/
(9) https://www.cbinsights.com/research/top-acquirers-ai-startups-ma-timeline/
(10) https://www.cbinsights.com/research/report/ai-trends-healthcare/
(11) https://www.cbinsights.com/research/report/ai-trends-healthcare/
(12) https://www.ajemjournal.com/article/S0735-6757(19)30391-2/fulltext
(13) https://www.boozallen.com/c/insight/blog/ai-bias-in-healthcare.html
(14) https://www.cdc.gov/reproductivehealth/maternal-mortality/pregnancy-mortality-surveillance-system.htm?CDC_AA_refVal=https%3A%2F%2Fwww.cdc.gov%2Freproductivehealth%2Fmaternalinfanthealth%2Fpregnancy-mortality-surveillance-system.htm
(15) https://www.boozallen.com/c/insight/blog/ai-bias-in-healthcare.html
(16) https://www.ajemjournal.com/article/S0735-6757(19)30391-2/fulltext
(17) https://www.nbcnews.com/news/nbcblk/racial-bias-found-widely-used-health-care-algorithm-n1076436
(18) https://www.nbcnews.com/news/nbcblk/racial-bias-found-widely-used-health-care-algorithm-n1076436
(19) https://science.sciencemag.org/content/366/6464/447
(20) Michael Tellini’s paper/another Impact DDX fellow (diligencing vc funds)
(21) Michele Colucci is the Co-founder and CEO of DigitalDx Ventures, which is a diverse, early stage impact venture fund that invests in digital health startups leveraging artificial intelligence technologies in diagnostics.
(22) Michael Tellini
https://www.forbes.com/sites/jeanbaptiste/2019/02/12/venture-capital-funding-for-artificial-intelligence-startups-hit-record-high-in-2018/#e999c1041f77
https://www.svb.com/globalassets/library/uploadedfiles/reports/healthcare-report-2020-annual_abr.pdf (See Page 6 & 7)
(2) https://policyadvice.net/health-insurance/insights/health-care-industry/
(3) This will be discussed later how you are still able to “invest in what you know” despite lacking deep industry knowledge and avoid Theranos-like situations.
(4) https://www.svb.com/trends-insights/reports/healthcare-investments-and-exits/2019-annual#downloadreport
(5) https://www.svb.com/trends-insights/reports/healthcare-investments-and-exits/2020-annual
(6) https://www.forbes.com/sites/jeanbaptiste/2019/02/12/venture-capital-funding-for-artificial-intelligence-startups-hit-record-high-in-2018/#e999c1041f77
(7) https://venturebeat.com/2020/01/22/cb-insights-ai-startup-funding-hit-new-high-of-26-6-billion-in-2019/
(8) https://venturebeat.com/2020/01/22/cb-insights-ai-startup-funding-hit-new-high-of-26-6-billion-in-2019/
(9) https://www.cbinsights.com/research/top-acquirers-ai-startups-ma-timeline/
(10) https://www.cbinsights.com/research/report/ai-trends-healthcare/
(11) https://www.cbinsights.com/research/report/ai-trends-healthcare/
(12) https://www.ajemjournal.com/article/S0735-6757(19)30391-2/fulltext
(13) https://www.boozallen.com/c/insight/blog/ai-bias-in-healthcare.html
(14) https://www.cdc.gov/reproductivehealth/maternal-mortality/pregnancy-mortality-surveillance-system.htm?CDC_AA_refVal=https%3A%2F%2Fwww.cdc.gov%2Freproductivehealth%2Fmaternalinfanthealth%2Fpregnancy-mortality-surveillance-system.htm
(15) https://www.boozallen.com/c/insight/blog/ai-bias-in-healthcare.html
(16) https://www.ajemjournal.com/article/S0735-6757(19)30391-2/fulltext
(17) https://www.nbcnews.com/news/nbcblk/racial-bias-found-widely-used-health-care-algorithm-n1076436
(18) https://www.nbcnews.com/news/nbcblk/racial-bias-found-widely-used-health-care-algorithm-n1076436
(19) https://science.sciencemag.org/content/366/6464/447
(20) Michael Tellini’s paper/another Impact DDX fellow (diligencing vc funds)
(21) Michele Colucci is the Co-founder and CEO of DigitalDx Ventures, which is a diverse, early stage impact venture fund that invests in digital health startups leveraging artificial intelligence technologies in diagnostics.
(22) Michael Tellini