Transformative Power of Medical AI in Rural Developing Nations
Africa has more than 24% of the global burden of disease, but only has access to 3% of the world’s healthcare workers. The Sub-Saharan Africa region has about 0.19 doctors per 1,000 individuals as compared to the United States which has 2.6 per 1,000. That means there is 1 doctor per 5,263 individuals in Sub-Saharan Africa as compared to the United States which has 1 doctor for every 385 individuals. Sub-Saharan Africa is not an anomaly when it comes to these ratios of doctors per population in developing parts of the world.
According to the WHO, Papua New Guinea has 1 doctor for every 18,903 individuals, Saint Lucia has 1 doctor for every 9,497 individuals, and Cambodia has 1 doctor for every 5,945 individuals. Other countries—aside from the Sub-Saharan Africa region and the other three aforementioned countries—that face these extreme ratios include Vanuatu, Madagascar, Federated States of Micronesia, Solomon Islands, Haiti, Afghanistan, Yemen, Honduras, Samoa, Guatemala, Bhutan, and Indonesia, to name a few. Healthcare is especially poor in the rural areas of developing nations such as these. This is where medical AI comes into play.
According to an article from Forbes, there is currently “untapped potential” in terms of AI in healthcare and the benefit it could have on humanity. However, if AI usage is maximized, it has the ability to transform the state of healthcare as we know it in these regions and beyond.
The current state of healthcare in developing areas includes a tremendous lack of physicians. This shortage of doctors results in lack of availability for visits as well as high costs for the patient. It is often difficult to be seen for emergency visits, let alone for preemptive appointments and preventative healthcare. Physicians that do work in these rural developing areas are often general practitioners who are not specialized in any one particular area. Due to the lack of specialization, these general practitioners often try to fill the role of specialized doctors.
This oftentimes leads to misdiagnosing and/or lack of correct course of treatment. Additionally, it is nearly impossible for many specialized procedures and surgeries to take place since they are outside the realm of the general practitioner’s knowledge. Not only is there a lack of physician specialization in these parts of the world, there is also a lack of technology. However, while many expensive medical technology is scarce in such resource-poor areas, the possession of smartphones is not. Currently, close to half of the population in Sub-Saharan Africa—one part of the world with the least access to medical technology—own smartphones.
So what if access to cell phones could be used to their advantage? Medical AI used in conjunction with basic technology such as phones and computers could make this possible, replacing expensive medical technology such as MRI machines, radiation therapies, and precision surgery robots. Currently, in many of these rural areas of developing nations, doctors must read images themselves (such as holding x-rays up to the light) rather than evaluate them on a computer, as is done in developed nations today. People oftentimes cannot get an x-ray because of the high cost.
However, if the reading of these x-rays could be digitized and done by AI technology from a cell phone or basic computer, then costs would decline and more people would have access to that healthcare resource. Not only would this save time for doctors and reduce the cost for patients, but it would also diminish the need for general practitioners to perform as specialized doctors. If this occurred, general physicians would be able to focus more on overall healthcare by outsourcing specialized tasks to different AI algorithms. Such uses for this specialized AI could consist of predicting vaccine usage, more accurate diagnosing using imaging technology, and predicting vector-borne disease outbreaks by tracking weather and land-use patterns.
In addition to the benefits of smartphones for use in hospitals, medical AI can also be used from home by patients. This type of AI would be as simple as using a smartphone app. These apps would be able to diagnose medical conditions early on, as well as be able to recommend the best treatments before medical issues become uncontrollable. In turn, this would reduce the need for people to go to the doctor, saving physicians time and giving them the ability to treat other patients for in-person visits who must be seen for more urgent issues.
As mentioned earlier—due to the lack of healthcare workers in rural areas of developing nations—doctors often perform routine tasks such as checking vitals and drawing blood. If blood pressure could instead be automated using monitors and infrared vein finding technology could be used to help make drawing blood a simpler task, then these routine vital checkings could be performed by people with less or no medical education. This will reduce the need for physicians to perform these tasks and instead allow them to focus more on critical thinking as well as emotional care. “Thus, medical AI technology can not only improve doctors’ efficiency and the quality of healthcare services, and reduce medical costs, but nurses and paramedical health workers can also be trained to use these tools to compensate for a lack of doctors.”
Given the current state of healthcare in rural areas of developing nations and the potential impact that medical AI has, these parts of the world will benefit tremendously. According to Dr. Sameer Maskey in his Forbes article AI For Humanity: Using AI To Make A Positive Impact In Developing Countries, “the impact could have a multiplier effect in developing countries where resources are limited.” This is why Segmed is so passionate about working towards this future, specifically with our focus on eliminating AI biases (you can read our past blog post on AI biases here).
What differentiates us from other medical AI companies is that we are collaborating with healthcare institutions from across the globe, not just from America and Europe. By doing so, we are hoping to prevent AI biases, which—in turn—will allow for this technology to work even in rural and developing regions. We are focused on improving the state of healthcare in all parts of the world, including impoverished and low-resource countries, who may be some of the largest beneficiaries of this technology.
