Artificial intelligence (AI) and its use in health care and social services is one of the most buzzed-about topics across the industry. While it can be a panacea for many challenges, when it comes to population health management, its application must be used thoughtfully and strategically. Here are some ways the power of AI can bring clarity, utility, and capacity to the organizations and leaders using it to realize better population health management and improve the effectiveness of care providers.
Elevating System-to-System Sharing
In fragmented health care ecosystems, AI offers powerful potential as a translator, helping unify information from disparate platforms like EHRs, payer systems, and community services. When deployed strategically, AI (such as natural language processing, known as NSP, and machine learning) can normalize and integrate data from clinical, claims, and social services sources, delivering a more complete picture of patient needs and ideally enabling improved collaboration between health plans, clinicians, and social service organizations. When used to bring together structured and unstructured data, AI can enable real-time insights into patient risk to accelerate care decisions, enable proactive outreach, and avoid duplicative or delayed interventions.
Making Data Actionable, Not Just Accessible
Too often, organizations struggle just to access the data they need, relying on time-based and ad hoc reports or complicated dashboards that offer static views. With the right infrastructure and governance, AI can support the delivery of actionable population segmentation, prioritizing outreach, flagging care gaps, and automating engagement so that providers can focus where it matters most. Whether it’s nudging a well-controlled diabetic patient with a personalized alert or automatically flagging a social determinant need like housing insecurity, AI can reduce administrative burdens while making population health efforts more precise and proactive. Applied correctly, AI can help triage the level of engagement with patients based on their chronic condition control levels, automate appointment reminders, and prioritize and escalate the most complex cases for care team intervention while ensuring other patient cohorts receive appropriate levels of support and intervention as needed.
Delivering Strategic Value in Value-Based Care
AI also shows particular promise in supporting value-based care models. In environments where organizations carry risk, early identification and intervention, along with ongoing management, are key to success. Improved risk stratification leads to more efficient care delivery and reduced long-term costs. AI can help providers hit the ground running with risk-based contracting, and meeting the needs of identifying rising-risk patients faster, and stabilize them sooner, leveling out utilization spikes and improving clinical and financial performance.
Avoid Pitfalls and Respect Guardrails
AI is not designed to replace humans; its strongest application is to enhance their work. The best results come when AI is embedded in team workflows—empowering clinicians and navigators, not replacing them. Used wisely, AI can reduce cognitive overload and bring critical insights to the surface faster. In addition, AI should be a compass—not the driver. Human discernment, contextual awareness, and trust-based relationships remain irreplaceable in health care, especially when serving vulnerable populations where trusted and personal relationships are often invaluable. When AI is woven into the fabric of care delivery in a way that’s sustainable, equitable, and effective, it can serve as a strategic asset in building a more responsive and resilient health care system.