AI in healthcare
What are the possibilities and challenges of implementing AI in healthcare?
“Doctors can be replaced by software – 80 percent of them can. I’d much rather have a good machine learning system diagnose my disease than the median or average doctor.”
The quote above by the Indian billionaire and venture capitalist Vinod Khosla is perhaps a bit exaggerated. It will be a while before AI has replaced 80% of doctors. It’s probably also more likely that doctors will work together with AI, rather than being replaced. Nevertheless, it may represent how most of us will be thinking about our healthcare in a relatively near future. In this article Digi-Talks explores some of the possibilities and challenges of AI in healthcare.
Telemedicine
A change towards an AI powered healthcare will mean the advent of telemedicine. An example is wearable sensors that collect and analyse data that feeds into apps on the patient’s smartphone or tablet. In some cases, the app will be able to diagnose on its own, but more commonly the app will function in collaboration with a doctor who will be able to diagnose remotely. Telemedicine will greatly reduce the cost of care and more importantly improve the quality of patient care.
The prospect of telemedicine is promising. It will make it possible to monitor a patient’s health, and those who have trouble getting to the doctor will be able to get help more easily. However, one of the challenges is the connectivity between the different AI technologies. There are too many apps and systems that aren’t capable of communicating with each other, hence it creates too much friction, when the doctor wants to get an overview of the patient’s data. The problem is addressed as a lack of interoperability.
Also, much of the new digital health technology lacks an evidence base.
“Commercially successful apps do not necessarily have medical value for physicians to apply to decision-making for patient evaluation, diagnosis, treatment, or other options.”
Despite the current challenges of telemedicine, it has the potential to change the current healthcare model (primarily focused on treatment) towards a predict-and-prevent model.
Efficiency and big data
One of the great possibilities of AI in healthcare is that it can free up a lot of time for doctors to focus on patients. A critique often aimed at the Danish healthcare system is that the doctors don’t have enough time to give their patients the proper care.
With AI tools we could automate time-consuming paperwork, scheduling, timesheet entries and accounting. However, it is crucial to involve medical professionals in the development of AI. Medical professionals globally and more recently in the Danish healthcare have complained that the new IT-systems being implemented aren’t designed with enough consideration for how medical personnel work.
As demonstrated in a number of our other articles, the implementation of AI into business will require a lot of professionals with different academic backgrounds. Another challenge is that the medical professionals don’t have the time to properly learn how to use new AI technology.
“Not having a full understanding of new medical equipment may lead to errors, which is why it’s vital that medical facilities plan training for new processes or technology.”
If AI technology can enable employees in healthcare to collect big data and analyse it meaningfully, it may prove useful in a number of ways; from identifying high-risk groups based upon common factors to improving patient care to even managing inventory.
Cyber-security
IT risks are probably the greatest issue facing the digitalization of our healthcare. We’ve all heard of the ransomware attacks that struck healthcare systems all over the world. A lot of personal and confidential information is constantly at risk of being stolen.
“Cyber-insecurity is a major issue in healthcare and is likely to get worse before it gets better. Ransomware specifically is reaching epidemic proportions within healthcare, with the industry falling victim to 88% of all recorded ransomware attacks on U.S. industries in 2016.”
Want to learn more?
Digi-Talks is hosting an event about AI in healthcare; view the details here.
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Sources: 3 Challenges of Technology Implementation in Healthcare — Future challenges for digital healthcare — Four IT Challenges Facing Healthcare Organizations in 2018 — Technology in Healthcare: Adoption, challenges and progress — Here are the 12 healthcare issues that will define 2018, according to PwC