How AI and Data Can Streamline Healthcare
Diving into the subject of AI and healthcare, Owning the Future of Healthcare host Daniel Litwin spoke with expert Dr. Jason Jones, Chief Analytic and Data Science Officer at Health Catalyst. There’s a lot to unpack around current applications and the future. First, Dr. Jones wanted to clarify that AI, in this case, is augmented…
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Diving into the subject of AI and healthcare, Owning the Future of Healthcare host Daniel Litwin spoke with expert Dr. Jason Jones, Chief Analytic and Data Science Officer at Health Catalyst. There’s a lot to unpack around current applications and the future.
First, Dr. Jones wanted to clarify that AI, in this case, is augmented intelligence, not artificial. “It’s purposeful in thinking, ‘What do we want the computer to do for us, and what do we retain?’”
Litwin and Dr. Jones spoke about the findings from a report, Healthcare Workforce and Organizational Transformation with AI – Enacting Change from EIT Health. The report’s main points included how AI applications can alleviate some workforce challenges and improve care delivery.
Dr. Jones explained his perspective for AI’s applications in healthcare is the Quadruple Aim, which has four components: improving population health, reducing costs, enhancing the patient experience and optimizing the work-life of providers.
Dr. Jones discussed applications that align with the Quadruple Aim. “AI can help providers with EHRs. On the patient side, it can offload and triage simple conditions.”
Dr. Jones explained where AI isn’t meeting its potential. “Right now, the focus is on transactional models. That’s important work, but it’s not maximizing the utility of transactional data.”
The other area where a gap exists is that predictive models don’t include change management, but every decision involves change.
In Dr. Jones’ opinion, there are also bigger questions AI can answer around inequity of care.
Dr. Jones offered the example of looking to predictive models to forecast readmissions. “We apply the model to the clinical context, but we should use the same tools to look at personal characteristics that can impact the risk of readmission. With augmented intelligence, we then know where to focus and what type of patients are experiencing disparities.”
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