Stanford Health Care Appoints First Chief Data Scientist | Information Center
For example, researchers at Stanford Medicine are already demonstrating how algorithms could help doctors differentiate between new disease subtypes, allowing them to accurately treat individual patients. AI could help healthcare teams provide better end-of-life advice or iron out scheduling issues, by anticipating people who might miss an appointment and sending additional reminders. The algorithms could help doctors proactively monitor patient records and flag patients who may have undiagnosed genetic disorders.
“It’s about improving patient care,” Shah said. “I want patients to say, ‘This is the most proactive care I’ve ever had’, or ‘The planning was a breeze’ or ‘My surgery was delayed, but thank God my wife was informed that she should come an hour later. .’ These things aren’t necessarily going to be the basis of big, flashy newspapers, but that’s okay.
Implementing artificial intelligence throughout the healthcare delivery system will undoubtedly be a boon for patients and providers, Shah said. The trick, he added, is to integrate AI in a way that doesn’t disrupt an already strained healthcare ecosystem.
“Furthermore, we must be mindful of fairness and justice when considering adopting AI-guided decision-making and be open to the possibility that there are situations in which we should not. use AI,” Shah said. “Creating and integrating an algorithm into any workflow will have ripple effects that go beyond what the algorithm does. So we are thinking about integrating AI as a global delivery science. It’s not just the algorithms that we need to consider; algorithms and clinicians must work as partners.
The goal is not for every decision to be made by an algorithm but for every decision to be supported by an algorithm, he added.
A (hypothetical) example
Shah further illustrates the potential of artificial intelligence through a somewhat futuristic hypothetical patient scenario. Vera, a 60-year-old woman with a history of high blood pressure and asthma, goes to the hospital. She arrives with a shortness of breath. Her doctor should diagnose and treat her condition and consider how to monitor her future health risks, such as heart failure, as well as assess her risk for chronic conditions, such as heart attack, stroke, and kidney failure. . That’s a lot of data to collect.
But what if Vera could don a wearable device that monitors her heart rate, breathing, blood sugar and blood pressure? This continuous stream of data would provide a real-time view of Vera’s health, and with AI-powered algorithms, her care team could precisely and accurately monitor her health. (Perhaps a prolonged, irregular heartbeat would trigger an alert for her doctor, and a scheduling system would automatically contact her with the times of an available appointment.)
Although this case is hypothetical and Vera fictional, the situation she finds herself in is common for patients and providers.
“What if we could do that – and more – for every patient? Broadly speaking, part of that is looking at how AI can support personalization in healthcare at scale,” Shah said. “The goal is to bring AI to clinical use in a safe, ethical and cost-effective way, basically.”