How AI And Machine Learning Will Impact The Future Of Healthcare
Our modern healthcare system is currently facing huge challenges exacerbated by the pandemic, a rise in lifestyle-related diseases, and an exploding world population.
The good news is that using AI to create intelligent processes and workflows could make healthcare cheaper, more effective, more personalized, and more equitable.
Some experts are predicting that the healthcare industry is the sector that could be the most affected by the enormous changes of the fourth industrial revolution.
I recently spoke with Tom Lawry, National Director of AI for Health & Life Sciences at Microsoft, about the future of healthcare. Here are some of his biggest insights and predictions:
The U.S. currently spends more money on healthcare than any other country in the world, but its individual health outcomes are lower than most other developed nations.
Additionally, clinician burnout is a huge problem, particularly since the pandemic.
Individuals in different generations also want healthcare that is personalized to their needs. Tom says:
“Millennials want to be able to have their healthcare consult from the same place they order their dinner — which is their couch. Meanwhile, you have groups like baby boomers who have a very different approach. They’re much more inclined to want to focus on a primary care provider…so we have the ability to go from that one-size-fits-all in care delivery with these systems to using data and AI to truly personalize it, starting with care that’s generational. Then even within each generation — millennials, Gen Z, etc. — we have the ability to allow them to access and manage care on their own terms.”
The good news is that most large healthcare organizations are beginning to make use of some form of AI. However, we’re still early in the journey of learning how we can apply artificial intelligence to make healthcare better.
One of the primary use cases is using machine learning and AI to make predictions. Organizations are using AI to predict everything from emergency department volumes (to get a better handle on staffing and triage) to predicting which treatments might be most effective for women who develop breast cancer.
Healthcare teams are also using natural language processing to improve the interpretation of patient scans by augmenting the work of human radiologists. Tom says:
“When a radiologist looks at a scan, they’re typically looking for one thing, which is the reason you have that image done. But many times in the background, there’s something else that can be seen. So as radiologists are dictating, natural language processes are being used to call out these secondary issues for follow-up, where previously those things might go unnoticed…so it’s a preventive way of trying to get out ahead of a future health problem.”
The biggest promise of AI in healthcare comes from changing clinical workflows. AI can add value by either automating or augmenting the work of clinicians and staff.
