Brad Porter, Global Chief Executive, Orion Health.
It’s the twelfth week you’ve woken up with sore eyes. Drops from the pharmacy didn’t work, but it’s always less irritating as the day goes on. And so the weeks stretch on in a never-ending cycle.
At what point does it become worthwhile to schedule time off work and shell out $75 or more to see the doctor for five minutes about something so trivial? Not to mention the time and life juggling associated with a doctor’s appointment.
Many of us in developed communities make these calls daily, ignoring symptoms because the cost of seeking help is too great. The problem is that the cost of seeking no help can eventually be much worse—including corneal damage and vision loss.
We live in the knowledge era. Smart people around us and before us have seemingly figured out explanations for everything. Solutions are tracking up there, too. But the dynamics of the societies we live in, for many places worldwide, have created new challenges in providing equitable healthcare.
The shortage of healthcare professionals to service their communities is at the top of the list for many. Understaffing stresses workers, causing more people to leave the profession and compromising patient care and outcomes. Underscoring this is the lack of access to essential health services that still plague half the world’s population.
Could artificial intelligence (AI) be the circuit breaker we’re looking for? I’m optimistic the answer is yes—with conditions.
Just like us humans have shortcomings, so too does technology. What are these, and how can we best use people and tech to complement our strengths and address our weaknesses?
In People We Trust
The adage that trust is hard won and easily lost rings true in the highly sensitive healthcare space. Nursing has ranked as the most trusted profession for 22 years in a row, with medical doctors and pharmacists close behind in second and third positions. Overall levels of trust have declined since the Covid-19 pandemic, though, further adding to the challenges healthcare providers face today.
Now, this is a gut instinct call—something you’ll find doctors and nurses must do a lot of in their work—but I think the historically high trust healthcare professionals have enjoyed reflects the fact that most get into this line of work because they care about the well-being of people and especially their patients. And people, instinctively, know that.
There’s no way to dress it up—an AI tool doesn’t care about the person interacting with it. So, how do we build and maintain trust in our tech solutions?
Would You Trust A Hallucinating Doctor?
If you did, I might be a bit worried. Since early-stage generative AI chatbots stormed the headlines last year, there have been some interesting tales about AI chatbots dreaming up answers that look (but, in fact, are not) absolutely legitimate seemingly out of nowhere. Entertaining, sure. Building trust? Not so much.
You wouldn’t trust a healthcare professional unless they had the necessary training, qualifications and experience for their position. So, if AI is to be used in a healthcare setting, we need to establish this same baseline credibility.
And in my line of work, this is top of mind. At the fundamental level, we need to ensure that the knowledge base a generative AI tool operates on is from a verified and trusted source. With access to robust, trusted datasets, we can build quality-assured solutions that patients and doctors can feel and be safe using.
Building Trusted Partnerships
I’m optimistic about AI’s potential to transform the future of healthcare because we’ve got the right ingredients on the table. We have knowledgeable and experienced clinicians and carers, mountains of healthcare data and information from which to pull insights and innovative technology.
The trick is bringing these ingredients together because it requires trust to bind them effectively. We’ve got to instill trust in all three to unlock their true potential—and that will take industry-wide collaboration and new forms of partnerships.
Selling The Vision
I’m confident that we’ll forge new types of collaborative partnerships across datasets, healthcare providers and technology solutions and between carers, patients and AI. In doing so, we’ll see an industry-wide movement emerging to achieve what’s needed to give AI the recipe for success because the vision is so compelling.
Use cases for AI, including generative AI, are growing by the day. From a healthcare professional’s perspective, the excitement is often greatest when discussing how they can save time and still add more value and even empathy than carers are often able to provide for their patients.
Take, for example, the conundrum doctors face when a person presents with a rare condition. There are so many rare conditions that it’s, in fact, quite common for a person to have one (although each person has a different one!). But not even the most brilliant doctors are expected to be walking encyclopedias on every rare condition out there. On the other hand, we can absolutely expect technology to know all about those conditions. And we can connect patients with empathetic, trusted AI that can walk through explanations in a user-friendly way, complementing and enhancing the level of service carers provide.
Another source of excitement is the potential for machine learning to predict probable outcomes and then use AI to provide preventative interventions to change the course of those outcomes. An example is using predictive population modeling to prevent a potential high-risk pregnancy from eventuating.
By taking the best of what we humans have to offer and the best of technology, we’ve got the right ingredients to mix them for success so that AI can indeed be the circuit breaker we’re looking for in healthcare. It’s complex but not rocket science, and we can achieve it.
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