Can A.I. Fix America’s Broken Healthcare System?
As we all know, healthcare in the U.S. is ridiculously expensive. Some reports show that the number one reason for personal bankruptcies in the U.S. is from the people who cannot pay hospital/medical bills. What is even more ridiculous is that even insured patients can face crushing medical bills leading to bankruptcies.
While doctors can earn a lot of money, the very high cost of healthcare is certainly not the fault of doctors (who have to repay hundreds of thousands in student loans), but is rather rooted in many inefficiencies in the healthcare and insurance system which could be solved by Artificial Intelligence.
While the very high cost of healthcare is not only limited to the U.S., it certainly feels the worst here since the citizens bear the pain of directly paying for the costs. In other countries with social healthcare where the very high cost of healthcare is on the government’s shoulder, indirectly being paid by citizens, we can see reduced quality of care, in the case of United Kingdom with under-equipped hospitals, and in the case of Canada with the infamous super long wait times.
Artificial Intelligence has already started to and is going to touch every aspect of our lives, and while it may unfortunately result in many people loosing their jobs, it will make many processes optimized, more effective, and will ultimately reduce costs for the consumers.
A.I. startups which are working to disrupt healthcare have attracted the highest amount of investment from venture capital firms among all different categories, even higher than cybersecurity, fintech, and sales/CRMs. (Source: CBInsights)
According to CB Insights, Healthcare+A.I. category of startups have collectively raised more than $2.14Bn in VC funding in the past 5 years. The most active VCs in this area are GV, Data Collective, Khosla Ventures, and AME Cloud Ventures.
While A.I. can help increase the quality of healthcare in many ways, in this article I will focus on how Artificial Intelligence can bring the cost of healthcare down, for governments and hospitals, and ultimately result in lower costs for patients and hopefully lower insurance premiums:
1) A.I. Will Reduce Administrative-Related Costs
More than 30% of medical costs is associated with administrative related fees in the U.S. When you visit your doctor, your medical bill isn’t just for your doctor’s time. You’re also indirectly paying for the staff needed to process billing and insurance-related activities like going after unpaid medical bills, processing insurance claims and making sure the insurance on file is up-to-date. By some estimates, these administrative costs amount to over $300Bn. A.I can help reduce these costs significantly by automating the paperwork, finding the correct vendors for drugs, automating the insurance claims and preauthorization and reducing fraud.
2) Automated Diagnostics Means Less Doctor Time
This can be divided into two sub-categories:
A) pre-diagnostics chatbots: You talk about your symptoms, perhaps take pictures if relevant, and A.I. powered chatbots can diagnose the potential diseases and refer you directly to a specialist or prescribe medical tests like blood tests or medical images. This reduces the time your general practitioner and nurses spend and therefore reduce the overall costs. This will also help educate the patients better about their symptoms and in their treatment process.
B) diagnostics of medical images and medical tests: After you had your blood sample taken or MRI image taken, A.I. can help diagnose your syndrome and either refer you to a specialist or suggest a treatment.
A.I. powered diagnostics not only reduce the costs by decreasing time spent by doctors, but also decreases costs by higher diagnostic and treatment accuracy. A better diagnosis and therefore a better targeted treatment means higher chance of recovery with the first suggested treatment and hence decreased costs.
3) Faster Drug Discovery Means Cheaper Drugs
There is this infamous saying going around among people working in the drug discovery space which is that you are lucky if the drug you are working on hits the market before you retire. The average time it takes for a drug from start of the process to when patients start consuming is a hefty 10–15 years and the R&D cost for each drug can mount to over $1Bn.
Many startups are applying A.I. to different parts of the drug discovery process in order to reduce the time and decrease the costs. These efforts include:
- aggregating and synthesizing information
- repurposing existing drugs
- generating novel drug candidates by applying A.I to the organic chemistry and research data
- automating the running of preclinical and clinical experiments
- finding the best patients for trials
- optimizing the number of types of clinical experiments
- automatically publishing the results
All of this, means cheaper and faster drug discovery which ultimately results in cheaper drugs, cheaper healthcare, and more drugs for rare diseases.
4) Less Human Error Means Lower Malpractice Insurance
Doctors get sued for malpractice all the time, which if the case is won for the patient, may result in hundreds of thousands of dollars (or in cases millions) in damages to be paid to the patient or their family. Doctors pay for medical malpractice insurance which varies based on the state and the type of doctor they are. Doctors pass these costs to hospitals and providers, they pass it to insurance companies, and the insurance companies pass these fees to customers by increasing the premiums.
Automated A.I. driven diagnosis with higher accuracies than humans means less human errors and therefore a lower chance for malpractice, which effectively results in lower premiums.
Moreover, the fear of malpractice by the doctors results in defensive medicine, which is arguably even a larger cost for the healthcare providers. Defensive medicine is the situation where the doctor prescribes more tests, images, and referrals to specialists than is needed, just to make sure they are not liable for the one in thousands case that could go wrong.
5) Efficiently Run Hospitals Means Lower Operational Costs
A.I. can be utilized to improve a variety of units in the hospital, such as the emergency room, preoperative care, inpatient units and pharmacy. A.I.’s can monitor, and learn from the current operations and can provide recommendations to best handle events and new patients.
For example, some startups are tackling the surgery room and others are targeting Emergency Rooms. Both of these are very expensive prime locations in the hospital with a lot of expensive equipment and doctors. By better predicting the exact timing required for each operation, the occupancy of the surgery room can be optimized. In the emergency room, by better deploying doctors with specific skills and assigning staff and doctors to different patients automatically, less doctor time will be wasted.
I certainly hope that with all these improvements applied to the healthcare system, we would see the cost of healthcare go down and we could see lower insurance premiums. Please let me know in the comments below what are the problems you see with the healthcare system and if you think A.I. can fix that?
I will be posting another article about the top startups disrupting the healthcare space using A.I. soon, please follow me here on medium and on linkedin to be notified.