Blog: Where would AI make the greatest impact? Why? How?
Where and Why?
Of all the sectors that Artificial Intelligence (AI) is to have a impact, it will be the most significant in healthcare. Why so? Healthcare delivery because of the processes involved in detecting, managing and treating diseases involves a complex approach. This complex approach requires collaboration not just between professionals or medical disciplines but also between providers and beneficiaries. This collaboration is unlike many other sectors.
However, achieving this collaboration is not easy and can be costly. Medicine has become increasingly specialized over the years leading to compartmentalization of healthcare delivery. Where collaboration is necessary, it is not occurring. Further, the importance accorded to the end product(health) means that investment in the sector is relatively higher compared to many other sectors.
These combination of factors have meant healthcare is ripe for disruption or at the least in need for operational and financial efficiency measures. Technology (whether it is AI, Genomics, VR, AR, Blockchain, Digital Infrastructure, Robotics..etc) is set to play a big role in this disruption. Tech companies that haven’t been traditionally involved in healthcare delivery are now seeing the value of introducing technology in healthcare and heavily investing in this sector.
Of all the technological innovations being used or trialed in healthcare delivery, I strongly believe AI (I include machine learning/deep learning and robotics here) will have the greatest disruptive factor. Yes, genomics and digital health will have a great impact, but they are set-up to integrate into traditional care models rather than be disruptive. I have to clarify here when I use ‘disruptive’, it doesn’t mean total replacement of clinicians nor how patients perceive health as a product, but it relates to how and where medical treatment is delivered. To explain this, let me start with a basic component of healthcare delivery: medical workforce. While governments and private players continue to invest in medical training, the increasing demand for healthcare and the time taken to train medical doctors has meant shortages of doctors continue to persist. In some places, it is all the more acute (see below figure).
From a patient’s perspective, all things being ideal, they should be able to pick the doctor or health service they require at the location and time of their choosing. However, because of reasons that are too complex to cover in this current article, this doesn’t occur in reality. In developing countries, there isn’t even a choice with absence of health services and doctors in many rural locations. In these situations, any form of basic healthcare delivery would be welcomed. Digital Health through tele-medicine and now AI (through remote triaging/screening and virtual health assistants) can fill in the void efficiently and effectively. This is why in less resourced countries there is more willingness to accept AI (see below figure).
Yet, AI is not just applicable to low-resource settings or for substituting medical workforce, it is also useful to contain burgeoning costs that health services face irrespective of the country where they are located. While it is beyond the scope of this article to explain the reasons for the increasing costs, but to summarise quickly they are an ageing population, the chronic disease burden, inefficient health funding mechanisms and recurrent costs (read workforce salaries). AI can play a huge role in addressing most of these cost-drivers. Many countries and companies see the opportunity to do this. Hence, a growing interest and investment in AI in Healthcare from commercial enterprises (see below figure).
This investment and interest will see more and more AI applications introduced into the healthcare market and service delivery in years to come. By informing new care models that are more efficient and effective, AI will not only contain costs of medical treatment but will also improve access and patient outcomes. How? Where there is repetitive and less complex medical activity, machine learning can simulate these functions for much lesser costs on the long run. This leaves human clinicians to drive and manage complex medical activity and spend time with patients more effectively. Also, low-cost AI technology delivered through economies of scale means wider availability of health services. A case in point is AI driven primary screening and virtual health assistants that are now increasingly being offered by several providers. Further, incorporation of machine learning in drug development can not only reduce the costs of development for the company but also decrease the price of medication when offered. In addition, AI driven diagnostics in laboratories and medical imaging departments can accelerate the diagnostic process and lessen the time spent in hospitals for patients, thus reducing costs and the risks associated with lengthy hospital stay.
These are just some of the examples, how AI can reduce costs and improve health outcomes. There will be as AI technology develops and gets used in healthcare, more examples to be seen. Therefore, AI will have it’s greatest impact in healthcare*.
*In previous articles here and elsewhere, I have written how certain conditions need to be fulfilled if this impact was to be realized. See: https://www.linkedin.com/pulse/ai-healthcare-are-we-yet-sandeep-reddy/