Why Patients Must Remain The Focus As AI Revolutionizes Healthcare
Smart, scalable and people-centered solutions should be at the heart of everything we do in healthcare.
Before the digital revolution transformed healthcare, paper-based systems and traditional contact centers were the foundation of most operational workflows. However, today's demands and fast-paced environment have rendered these manual processes unsustainable, inefficient and prone to risk.
Having spent my career leading digital innovation across a range of healthcare organizations—including managed care organizations, Medicaid programs and self-directed care providers—I've always been fascinated by how tools can improve outcomes, reduce friction and give individuals more control over their care.
But innovation, including technologies like AI, is only meaningful when it serves people. Let's look at how we can work to deliver future-ready healthcare systems with AI that put people at the center.
The Manual Challenge
Historically, managing paper records has required significant time and labor, leading to frequent delays, lost productivity, escalating administrative costs and quality issues. Similarly, legacy contact centers face limitations with high agent turnover, long wait times and outdated tools.
These factors not only impact efficiency but also drastically take away from the overall patient experience.
As a study from the National Library of Medicine comparing paper-based with electronic patient records found, 'Inconsistencies between a patient's electronic and paper-based medical record can lead to significant problems for the health care staff in daily practice.'
The modern consumer expects fast, personalized support across multiple channels. In fact, as reported by The Lund Report, 30% of patients have left an appointment due to long waits, and 20% have switched doctors for the same reason.
Traditional methods are also often vulnerable to data loss, security risks, limited accessibility and service inconsistencies that may hinder both communications and compliance. These challenges highlight an urgent need for smarter, scalable solutions in healthcare operations.
The New Age Of AI
AI has quickly evolved from a niche technology to a transformative force in healthcare. What began with automating simple tasks like appointment scheduling or form processing has now expanded into sophisticated applications such as predictive analytics, natural language processing and real-time clinical decision support.
But the concern is that AI could cause healthcare to lose the human touch.
To solve this, humanized AI seeks to use AI to create a blended approach that enhances rather than replaces humans. This idea is founded in empathy and context awareness to create systems that support patients and providers in more intuitive, effective ways.
Dr. Jonathan H. Chen, assistant professor of medicine at Stanford, sums up the idea nicely: "'What is a computer good at? What is a human good at?' We may need to rethink where we use and combine those skills and for which tasks we recruit AI."
Organizations are using humanized AI to create scalable, more intentional experiences for their teams and patients. For example, NRC Health created an AI engine, Huey, to keep the human experience at the center of healthcare.
From AI-powered chatbots delivering 24/7 support to predictive models that flag high-risk patients before emergencies occur, these tools can reshape healthcare delivery. Humanized AI solves some of healthcare's most persistent operational burdens, such as streamlining patient intake systems, verifying data in real time, reducing administrative workload and providing multilingual support, which enables human teams to focus on more complex and personal interactions.
As Dr. Rachel Callcut, associate professor of surgery at the University of California, San Francisco, explains in a recent report from GE Healthcare and the MIT Technology Review, "By focusing on areas that patients, providers or systems are invested in addressing, we have set the stage for more rapid adoption and dissemination of AI.'
A Phased Approach to Transforming Care
What excites me most about AI in healthcare isn't just the technology itself—it's the potential to remove friction from people's lives.
Leading the implementation of humanized AI at my organization was both an exciting and humbling experience. From the beginning, our goal was clear: to automate repetitive, paper-based workflows and contact center processes so we could improve efficiency and reduce human error. Throughout the process, however, I learned some valuable lessons:
The first is to engage early and often. We initially thought we had accounted for every business need—but our team quickly flagged key issues we hadn't considered. It's, therefore, crucial to involve subject matter experts and frontline team members in the earliest stages of planning.
Second, always have a backup plan. We pushed forward with an aggressive implementation timeline but overlooked the fact that AI systems operate on preset logic and improve over time. The lesson here is simple: Build a plan B to ensure business continuity while AI systems are learning.
Finally, implement in phases. Rolling everything out at once sounds efficient, but we learned that a phased approach gave us the space to incorporate real-time feedback and refine our plan for long-term success.
A the GE Healthcare and MIT Technology Review report cited above found, '80% of business and administrative healthcare professionals believe AI will make them more competitive providers.'
I agree with this. AI tools can transform how patients experience care. But it's not about replacing people or implementing AI at the expense of the patient experience. It's about making healthcare more responsive, more human and more efficient. Not someday, but today.
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