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AI made headlines across healthcare in 2023 - and with good reason. The impact that the technology could have on scribe services and record-keeping was immediately apparent. Early adopters of AI initially implemented it for back-office operations, and since then, there’s been a significant advancement in AI’s use in care delivery.
With a renewed focus on experimentation, healthcare organizations are calling on their IT teams to research and test AI integration. While this is a sign of progress, a limited regulatory framework has left the industry alone in adopting AI safely and responsibly. Most leaders that I talk to agree that innovating with AI is the only way forward, but they rightfully have questions about its impact and safe implementation.
I recently hosted a discussion to talk about this in depth, joined by some of the most innovative leaders in the healthcare space today: Rick Abbott, Senior Vice President of Employer Solutions at Priority Health, Emily Young, President of Tufts Medicine Integrated Network, and Laurent Rotival, Executive Vice President and Chief Information Officer at Cambia Health Solutions.
Building on that conversation, here are some additional insights about why it is critical to embrace AI in healthcare, and how it can be done thoughtfully and responsibly.
Why AI is Essential to Healthcare
Workforce shortages in healthcare contribute to an environment where patients currently wait up to an average of 26 days to get a non-emergency appointment scheduled.Innovation to increase access to healthcare is increasingly urgent, and that’s where AI has been able to shine. AI has already streamlined patient intake, record-keeping, and other administrative tasks that have traditionally added to provider burden. By alleviating administrative demand on clinical staff, health systems and providers have been able to devote more time to care delivery.
Take Tufts Medicine, for example. When Tufts Medicine partnered with Curai to expand its virtual care offering to patients, their patients were provided with 24/7 access to primary care. Patients were able to conveniently connect with a clinician virtually, which allowed Tufts to “save that time in the physician’s office for some of the sicker patients” according to Emily Young.
AI’s ability to free up clinician time has made it easier to increase patient engagement and satisfaction. The “always-on” aspect of AI means that patients can get care instantly and receive personalized, continuous care at their convenience. AI has also made it easier to expand access to historically underserved communities.
Priority Health, which works with Curai to provide free virtual care to uninsured adults in Michigan, uses AI as a clinical enablement tool. Where some patients might have previously delayed medical care due to long wait times or hard-to-reach facilities, they can now receive clinical care right away with the support of AI.
There is a growing consensus among providers and payers that AI expands clinical capacity and improves patient satisfaction, but concerns remain around AI governance and implementation.
How to Start: Identifying the Right Use-Case for AI
For leaders exploring AI, there may be questions about how to adopt AI while mitigating risk. When asked about their approach to adopting AI responsibly, our panelists agreed that the best way to get started is by deciding on a workflow that could be improved by AI’s efficiency.
Laurent Rotival at Cambia Health Solutions suggests leaders “Work on a problem that you think is compelling in the context of your business model.” Understanding how the AI can be used to solve for one particular issue can inform the prototype for widespread adoption.
Rick at Priority Health also emphasized how starting small could be helpful in addressing concerns from skeptics or traditionalists that may be wary of AI. “One of the things that we did [...] was we found a very mission driven, purposeful, contained pilot [...] that had very minimal risk. [...] So it was just finding some very specific problem to solve, solving that problem, and now we're building upon it.”
Focusing on a specific use case can be an effective way to test an AI’s capabilities, and develop what Emily Young at Tufts Medicine calls a “minimally viable product.” AI is advancing rapidly, and testing the technology for all possible scenarios is not feasible. As a result, iterative development that starts small is an effective way for any organization to get started.
I often advise executives that they consider a “crawl-walk-run” approach, and plan to update the technology over time with thoughtful, but rigorous testing, to set the foundation for long-term success. . AI will change the face of healthcare as we know it, but the technology can produce misleading results if it's not implemented properly. Being intentional about the deployment of AI, and introducing it correctly, will enable organizations to build trust and downstream satisfaction. That’s why governance is a crucial step to adopting the technology.
Governance Can’t Be an Afterthought
It’s clear that the rapid evolution of AI calls for responsible management of the technology. As organizations move to innovate, adopting AI also means establishing governance and guardrails, something many organizations are doing for the very first time.
Governance means not only having a policy in place that documents how the AI is managed and implemented, but a cross-functional committee that monitors, evaluates, and tests it in an iterative manner to ensure its success.
An effective governance committee includes a range of experts who can evaluate not only technical capabilities but also clinical effectiveness. This team may include physicians, clinicians, data scientists, engineers, legal professionals, product developers and marketing experts. The composition of any governance committee is dependent upon the organization, but it’s important to have both clinical and technical oversight to ensure AI delivers on its promise, and operates within an appropriate framework.
The Path Forward
AI is here to stay. For any organization that wants to expand care access, improve experience, and scale impact, this is the time to lean in.
But the path forward isn’t reckless experimentation. It is thoughtful deployment, guided by clear goals, rigorous testing, and strong governance. The health systems and payers getting this right are those that are moving fast, but not cutting corners.
At Curai Health, we’re proud to partner with forward-looking organizations like Tufts Medicine, Priority Health, and Cambia. Together, we’re demonstrating that AI’s role in healthcare is broader than any one use case. It's about transforming care delivery - enhancing access, improving efficiency, and creating a more connected, responsive experience for all.
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