 Medical care is both complicated and expensive. We hear horror stories about how someone goes into the ER to get some stitches on their hand, then gets a big nasty bill. Occurrences like this are in part due to the complex bureaucracy of our healthcare system, which result in nothing but nerve-wracking bills and confusion for patients. Regardless of whether you're in favor of more privatization or government control of healthcare, this is an issue which affects us all. And while there is no one and done solution, there are some potentially innovative ways to address these challenges. One of the most prominent is artificial intelligence. Although AI's introduction in healthcare is still in its infancy, it is already transforming the medical industry and may help make things easier on patients' wallets. How so? Well, stick around to find out. Recently, we had asked our viewers in several polls what they attributed as the primary cause of high healthcare costs. The most common answers were monopolies on life-saving drugs by massive pharmaceutical companies and lack of price transparency on both the provider's end and insurance company's end. Now, the truth is a bit more complicated than that. While these two factors are definitely a part of the problem, it is what we call the middleman in healthcare that is among many other things to blame for these high drug prices and lack of price transparency. The term middleman is what is used to refer to entities that facilitate various aspects of the healthcare processes between the provider and the patient. For drug companies, this would be the pharmacy benefit managers or PBMs, which negotiate fees with drug manufacturers, create drug formularies and related policies, and reimburse pharmacies for patient prescriptions. In the case of going to the doctor, this would be the health insurance companies to whom you the patient pay premiums to for them to reimburse your provider, either fully or partially, for their services. Tossing these middleman entities into the relationship between patients and their provider only adds to the complexity of the situation. Based on 2010 estimates, the US alone spent around $250 billion on unnecessary administrative burdens from things like billing and insurance costs due to mishaps like error and fraud among many other things, and it is safe to assume that number has gone up since and will continue to skyrocket. Now it's important to reiterate that there is no one solution that fits all to a problem as complicated as this. Even if we radically altered our system to where we didn't have these complicated middlemen and implemented all the suggestions in our poll into our healthcare systems, there will still be some unnecessary costs due to inevitable fraud and errors in administrative tasks. After all, as humans, we have imperfections and cannot expect our creations to be perfect, but that is okay because we can make them better in our never-ending chase for perfection and this is where artificial intelligence comes in. One area of healthcare where artificial intelligence can make a big impact is in billing. In order to track and manage a medical diagnosis and conditions for billing, an alphanumeric code called an ICD-10 code is used. ICD-10 codes are assigned by the physician for a specific type of diagnosis. This code is then sent to the insurance companies where it is determined if the services provided were medically necessary and how much the payout to the provider will be. The entry and processing of these codes requires a lot of manual labor and is often riddled with complexities and sometimes errors which can cause administrative slowdowns and additional costs. Now, imagine if we had an automated system powered by machine learning that could do all that coding and classification for us. While considering the average cost of ICD-10 implementation for a small medical practice is around $7,000 to $10,000, and the average cost for a medium-sized practice is $15,000 to $23,000, reducing that amount means less administrative costs and better quality of care for far less on the patient end. Outside of lifting administrative burdens, AI could reduce costs through diagnostics. For example, in analyzing mammograms for breast cancer, AI has shown a remarkable 99% accuracy. On top of that, the speed at which it can provide the diagnosis surpasses that of any human physician. AI can also be used for various forms of medical imaging such as CT scans and MRIs to detect the onset of serious health problems before they start with the precision and speed that could give a lot of human physicians a run for their money. Early interventions would save patients agony as well as money. For example, using AI for earlier screening of certain cancers from imaging could save the US around $26 billion a year in treatment costs according to one estimate. The opportunities are boundless with AI at our fingertips. AI is by no means perfect because once again, anything that was built by humans is more than capable of making mistakes like humans. We still have years worth of research development and testing before we can trust our healthcare and the health of future generations in the hands of AI. The path to making high quality healthcare affordable for everyone everywhere is a multifaceted problem with many proposals and potential solutions. While AI may not solve all those problems, it can certainly help to make them smaller and more manageable, which is definitely a first step in the right direction. We hope you enjoyed this video and learned something new today. If you did, then be sure to subscribe to The Science Verse and please hit that notification bell and stay tuned for more science videos.