AI has shown tremendous potential in transforming healthcare, offering innovative solutions to long-standing challenges. However, it is crucial to be aware of the hype and pitfalls to ensure effective and ethical use of this powerful tool. Hackensack Meridian Health CEO Robert Garrett breaks down how the largest health system in New Jersey is making progress.
As more health systems embrace the power of AI, there is also tremendous hype about its potential. Can you give some examples of how HMH is harnessing its power now?
RG: The power of AI is evident in many areas of healthcare, especially in diagnostic support and predictive analytics. We are working with our experts on cases where AI can identify complex patterns in imaging data and provide quantitative evaluation of radiographic traits. This will potentially allow us to better manage the radiology workflow queue, ensuring more complex and urgent images are prioritized. They may also detect modalities that can benefit from further inspection. Beyond diagnostics, AI algorithms can analyze large datasets and predict disease outcomes, patient deterioration, and potential treatment responses, assisting in personalized medicine, early intervention, and resource allocation. We have built a Predictive Health team that is working with stakeholders across the network to leverage AI technology to predict and detect disease and embed such intelligence into clinical workflow. Here’s a great example. We are developing a program to identify patients who would benefit from serious illness care interventions. The goal? By getting patients into the right setting of care sooner, we can improve their care, decrease bed days and readmission rates. We are also using AI-powered workflow to enable primary care providers to identify Stage 3 chronic kidney disease earlier to slow disease progression.
Another promising area for AI is in drug discovery and development. Can you explain how this has tremendous potential to expedite new treatments and do you have any examples in the network?
RG: Keep in mind that only about 12% of drugs entering clinical trials are ultimately approved for introduction by the FDA. This is an expensive and challenging process. AI applications can analyze vast amounts of data to quickly identify high-potential drug candidates, predict their effectiveness and safety, and optimize their design. Our Digital Technical Solutions team and leaders from our Center for Discovery and Innovation, along with Google are working towards the development of Research Data Enclave and Digital lab infrastructure that will enable and accelerate research. Our first two use cases are in the area of infectious diseases and cardiac care.
Emerging from the pandemic, the industry has prioritized ways to address shortages with staffing supply chains and more. How are you using AI to improve operational efficiency?
RG: There’s no question AI has tremendous potential in this regard. Consider nurse staffing, which accounts for a major proportion of a hospital’s workforce. Administrators are increasingly using analytics to improve a process that was once the realm of phone calls, text messages and spreadsheets. We also know that it is important to account for the “pairwise’’ familiarity – the number of past collaborations of pairs within the clinical team. A Harvard Business Review article noted that researchers studied cardiac teams conducting more than 6,000 surgeries over seven years and found that the composition of the team had a significant impact on productivity. At HMH, we are utilizing AI for Operating Room Forecasts. in addition to looking at pair trends for procedures to optimize efficiency, we are also developing recommendations of procedures for patients that can fill unused time.
With all of the promise in AI, what are your concerns about this technology?
RG: My concerns are shared by many industry leaders. First, AI has the potential for bias. The effectiveness of AI models relies heavily on the quality, representativeness and diversity of the data used. Biased or incomplete datasets can lead to algorithmic biases and erroneous outcomes, potentially exacerbating healthcare disparities. There are also many ethical concerns related to privacy, security and informed consent. Ensuring responsible and ethical AI use requires robust governance frameworks and adherence to regulatory guidelines. Mindful of these issues, Hackensack Meridian joined the Health AI Partnership, a first-of-its kind collaborative to develop best practices for AI in healthcare. The group also includes Mayo Clinic, Kaiser Permanente, Jefferson Health and others. I am an optimist by nature and I believe we can harness the power of AI to live our mission, which is to transform healthcare and be the leader of positive change. There’s a great quote from Albert Einstein that says it all. “You can’t solve a problem on the same level that it was created. You have to rise above it to the next level.’’
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