I have seen the evolution of healthcare over the course of my career, first as a Cardiologist, then as an entrepreneur and investor in healthcare. I have seen universally fatal diseases like hairy cell leukemia be cured with one round of chemotherapy!! If you had a heart attack in 1970, your odds of dying from that heart attack was over 30%. Now, it’s less than 5%!! That’s some serious progress! A lot of this progress is the result of increased funding for medical research, improved research and development infrastructure, and increased sophistication of the clinical trials and analytic methodologies.
We are all beneficiaries of this progress. We get to live longer and have higher quality of life. We have learned much about how to avoid disease, have more energy and be more productive. Everyday, we are adding more knowledge and insights on top of what we already know. Life expectancy has increased dramatically over the last 100 years. But, it has peaked over the last 10 years or so (in US, it is actually declining in certain segments of the population.) Progress in preventing and managing certain conditions such as cardiovascular diseases and kidney diseases has slowed down. This is due to several factors but a big explanation is that much of the low hanging fruit has been picked in these diseases. To have the next big step forward, we need new breakthroughs in research methodologies and how we extract insights from the data.
Enter Artificial Intelligence! AI has been around for some 80 years. It has gone through several periods of peak and trough in terms of research activity and interest in its applications. This time, it feels different! How? There appears to be a confluence of factors: some key methodological issues have been solved; computing power has increased significantly such that modern computers can handle some of the taxing demands of AI applications; and there has been an explosion of digital data in all industries. All of this applies to healthcare: implementation of electronic health records means healthcare data is being digitized; increase in the use of apps and wearables; and availability of data about socioeconomic issues affecting patients. All of this allows us to take a fresh look at new and old healthcare data and glean new insights that help improve the health of individuals and populations. The figure below shows the amount of knowledge and insights that is sitting inside the data waiting to be discovered. That’s something to be excited about!!
To extract the knowledge and insights in the data, we need powerful new ways to analyze the data. That is exactly what AI is built for! It can handle high volumes of data, and data that is multidimensional. It can find relationships, causality, correlations, and predict future outcomes. It can keep improving over time as it handles more data. This does not mean that a future with AI fully incorporated into the practice of medicine is right around the corner. Many issues have to be addressed before AI becomes mainstream in healthcare.
In this blog, we will examine those drivers and barriers and examine how AI’s applications in healthcare are making inroads.