Managing the Tsunami of Healthcare Data with AI to Deliver Precision Care for All
Healthcare data and AI integration enable proactive, precise care by anticipating disease and personalizing treatments. Partnerships and clinician involvement are key to success.
Managing the Tsunami of Data and Adopting AI Technology to Create Precision Care
How the Integration of Data and AI Can Help Provide Better Care for More People
Healthcare organizations have digitized nearly every aspect of care over the past decade, generating an overwhelming volume of data. Now, health systems are exploring how to integrate comprehensive data from across their enterprises and apply AI solutions to improve care delivery for more patients.
At the 2025 Healthcare Information and Management Systems Society Global Health Conference & Exhibition (HIMSS25) in Las Vegas, a panel of experts discussed how AI and holistic data approaches can create a more precise, responsive, and patient-centered healthcare system. The panel featured Terri Couts, SVP and Chief Digital Officer at The Guthrie Clinic; Curt Langlotz, MD, Professor at Stanford Medicine; Tim Zoph, Senior Advisor at McKinsey & Company; and Shez Partovi, Chief Innovation Officer at Philips.
Managing the Tsunami of Data to Create Precision Care Delivery
What is Precision Care?
Precision care moves healthcare away from reactive treatment toward proactive strategies that prevent or mitigate disease. Early diagnosis plays a key role, enabling timely interventions that improve patient outcomes.
Tim Zoph from McKinsey notes, “The current care model won’t get us where we need to be. Precision care means anticipating disease and monitoring patients before symptoms appear. Using data like molecular markers, we can guide patients on treatments or lifestyle changes that make a difference at each stage of their journey.”
To implement precision care effectively, start by clearly defining the clinical problem, removing barriers to access, and building AI models that can be tested and refined—cancer care is a prime example.
Curt Langlotz adds, “We’re now able to understand a patient’s cancer more deeply, including how they might respond to treatments based on genetics and imaging. This is a significant shift from past approaches.”
Leveraging AI in Healthcare
AI can improve healthcare by increasing the accuracy and speed of diagnosis and treatment decisions. Algorithms analyze large datasets to detect patterns and make predictions that support clinical care.
Personalized medicine benefits greatly from AI, which can evaluate genetic profiles, medical histories, and lifestyles to recommend the most effective treatments. AI-powered chatbots also provide patients with personalized health advice, boosting engagement and well-being.
Successful Implementation of AI-Driven Solutions in Real-World Settings
Panelists emphasized that AI solutions must process data in real time, regardless of where patients are on their care journeys. Care should be delivered when and where it’s needed, ensuring timely interventions.
Terri Couts explained, “Our command center uses data to identify when a patient is likely ready to go home or qualify for hospital-at-home programs. This approach moves away from fixed schedules, using analytics to coordinate care tailored to each patient’s needs.”
The Impact of AI on Patient Care and Operations
With so much data available, healthcare providers must determine if AI models can deliver a clear return on investment (ROI). Beyond improving clinical outcomes, AI’s value lies in boosting operational efficiency and reducing clinician burnout.
Couts states, “If AI helps retain and engage clinicians, that alone justifies its use.”
Partnerships Are Paramount
Tim Zoph warns, “Precision health isn’t something healthcare organizations should pursue alone. Successful AI development requires partnerships with patients for data, with tech companies to manage large datasets, and with clinical teams to validate algorithms.”
Terri Couts adds, “Recruiting enough clinicians is tough. We rely on partners willing to co-develop AI models using our data. Clinicians must own and monitor AI tools to ensure they are safe and effective.”
No Access, No Precision
The panel agreed that precision medicine cannot succeed without broad access to care. Nearly half of US counties lack cardiologists, highlighting the need for new models supported by AI and partnerships that improve operations and enable proactive patient care.
What the Latest Data Tells Us
According to the Philips 2025 Future Health Index global report, 82% of healthcare professionals believe AI and predictive analytics can save lives through earlier interventions. Seventy-five percent agree these technologies will reduce hospital admissions.
The report, based on responses from nearly 18,000 patients and clinicians across 16 countries, also found that clinicians remain the most trusted source of information about AI for patients. For AI to scale effectively, clinicians must lead and be supported in these efforts.
Clinicians are not just users of AI; they are gatekeepers and champions of its trusted application in care delivery.
For those interested in expanding AI skills in healthcare management, exploring AI training courses tailored for healthcare professionals can provide practical knowledge and tools to implement AI solutions effectively.
