Of all the areas in which artificial intelligence promises to improve outcomes, few seem as important as patient care. Some news reports say the US is approaching a healthcare crisis. Others say the crisis has already arrived.
If AI has the power to streamline workflows and fast-track data analytics, imagine the impact it could have on patient care when properly applied. It could be the tool needed to move the healthcare sector from crisis to credibility.
But what is the proper way to apply AI? My belief is that the best results won’t be found by leveraging AI for flashy applications like robotic surgery or futuristic diagnostics. To have a truly transformative impact on patient care, AI must be used to close the care gaps that are wasting resources, costing lives, and eroding trust in the US healthcare system.
Using AI to reclaim healthcare data
When the healthcare world went digital, it created a stream of valuable data doctors could use to improve diagnoses and identify trends. But the stream quickly became a river of data that flooded doctors or flowed past them before they could put it to good use.
Technology companies responded to the ever-increasing volume of healthcare data by developing systems to capture and interpret it. But the rush to provide a solution resulted in a fragmented landscape of platforms, each with its own structure, taxonomy, and format. As a result, doctors can’t use the data to get a solid picture of their patients’ needs, especially not at the point of care.
AI empowers efficient tools for normalizing and reconciling data across systems. AI-powered tools like natural language processing and entity recognition are allowing doctors to reclaim healthcare data and turn fragmented inputs into something coherent.
Using AI to normalize and reconcile data is a foundational shift that solves a foundational problem. It’s not flashy, but it provides results. By standardizing the chaos, it makes real insight possible and empowers better care coordination.
Using AI to reduce complexity
Incompetence is rarely the cause of the care gaps in the US healthcare system. Care teams and clinical ops know how to do their jobs, provided their jobs are manageable. But the complexity that has become a core part of healthcare systems — driven in large part by fragmentation of systems — has made many jobs unmanageable.
Fragmentation makes seeing the full picture a Herculean task. As a result, patient screenings are missed and critical lab follow-ups fall through the cracks. Things would be much different if the data spread across electronic health records, progress notes, referral platforms, and claim systems could be accessed and understood when and where it mattered.
AI has the capacity to function within the complexity, capturing the data that matters and turning it into actionable intel. It can scan records at scale, reconciling inconsistencies to create a body of data that is informative. As data is assessed, overdue interventions can be flagged and the next best action for clinical teams can be identified.
When healthcare providers tap into AI, they get a tool that can assess in seconds what takes days of manual review. And they get a level of consistency even the most experienced human navigator can’t deliver.
Using AI to optimize systems
If your organization is in crisis mode, you’ll be tempted to latch on to any tool that promises to leverage AI to keep you afloat. Don’t give in. Starting with AI won’t get you where you want to go. You need to start by identifying the outcome you want to improve.
Look at where care is falling through, and you’ll know where to focus your efforts. Start with an AI strategy, and it will be easier to identify the tools that can make a difference.
Once you hone in on the area that needs improvement, find a tool that will integrate with your systems. Tools that can’t connect data from the entire system won’t give you system-level insights. To ensure integration is effective, run a focused pilot at one clinic or focus on one high-impact workflow before you scale the tool across the entire enterprise.
The overall goal should be action, not just insight. Effective AI pushes beyond analysis to prompt real action. The right tool is the one that drives better decision-making.
To see AI’s promises become transformational solutions, healthcare providers need to stay focused on the operational truths that shape care and design around them. AI can reclaim data and reduce complexity, but only when used in a disciplined way. Technology alone doesn’t improve care. It’s the clarity of knowing which problems matter most to patients and clinicians, and the willingness to take ownership of those problems, that transforms potential into meaningful progress.
Chris Hutchins, Founder and CEO of Hutchins Data Strategy Consulting, provides expert guidance to healthcare institutions on developing scalable moral data and artificial intelligence methods.
