What are the challenges facing the healthcare industry? growing patient demandartificial intelligence (AI) and automation are giving hospitals and health systems the opportunity to rethink how they deliver care. However, many organizations struggle to determine where and how to implement these technologies.
“Artificial intelligence is not a hammer looking for a nail,” stressed Dave Henriksen, director of value-based care at Notable. “Organizations are struggling… they need to understand how AI can help them solve their core problems.” Drawing from their experiences implementing AI in leading healthcare systems, Henriksen and Notable’s Chief Medical Officer, Aaron Neinstein, MD, shared seven tips to lend a hand your organization execute on an enterprise-wide AI strategy.
1. Define your north star
“Don’t get into AI for its own sake,” Neinstein said. A healthcare organization’s AI strategy must be aligned with its mission and long-term vision. You need a clear vision of where you want to go as an institution.
Bill Gates created an opportunity clearly: thanks to the enhance in artificial intelligence productivity, organizations can “increase the quantity of results, improve their quality or reduce human work time.” While you’ll likely see improvement in all three areas, identifying your main goal is key. Are you working to expand access to care? Improve the quality of results? Reduce supplier burnout? Your AI strategy should accelerate progress toward these goals, not distract from them.
2. Set clear business goals
Go beyond the hype surrounding the employ of AI by defining specific, measurable goals. AI projects are more likely to fail if they start with problems rather than problems. Whether your focus is on operational efficiency, patient access, or quality metrics, your organization’s leaders must define what success looks like. Start with the workflow you want to improve, then determine how AI can lend a hand.
Neinstein shared a cautionary tale from a vast health care system affiliated with the university. Because its leaders focused on implementing a specific technology rather than identifying the business problem they wanted to solve, the health system’s initial implementation of a no-show prediction algorithm led to overbooking and did not improve outcomes.
3. Develop guiding principles
Don’t start your AI project from scratch; Instead, build on existing privacy, security and compliance frameworks while adding AI considerations. Henriksen emphasized, “Focus on how the patient experiences care while providing it at lower cost and higher quality.”
Healthcare organizations already have a solid foundation in IT governance, privacy, security and user experience. Although artificial intelligence brings up-to-date solutions, you don’t have to reinvent the wheel. Instead, embed the AI tool guidance into existing structures, focusing on:
● Patient experience and quality of care
● Support and effectiveness of caregivers
● Clear rules for applying artificial intelligence in clinical settings
● Data management and security
● Integration requirements
4. Invest in change management to accelerate adoption
Successfully implementing AI is not just a technical challenge; requires the involvement of the entire organization. Rather than avoid the problems associated with implementing AI, successful organizations address such problems head-on through education, storytelling, and engagement on the front lines.
During his time at Intermountain Health, Henriksen said that as up-to-date tools are integrated, leaders will reach out to employees to ask what’s working and what’s not. Many of their suggestions came from consumers’ experiences outside of their healthcare careers. “With artificial intelligence, we can enable these suggestions,” he explained.
The key to ensuring acceptance and employ of AI tools is to involve staff in the process, not just the recipients of the changes. This approach is not specific to artificial intelligence; similar strategies were used when health care organizations first transitioned from paper to electronic health records. This experience has shown that this approach is necessary to building trust and adoption.
5. Achieve early wins to accelerate your strategy
Instead of falling into analysis paralysis, successful organizations identify focused opportunities to achieve quick wins that build employee confidence and momentum. “Think big, start small and move fast,” Neinstein advised.
At Intermountain Healthcare, petite tests of changes on a subset of users have proven effective. Once employees could tell co-workers that the up-to-date tools saved them a lot of time, implementation took off naturally. These early supporters become crucial to winning over more skeptical team members.
Leaders should remember that all the planning in the world is no substitute for hands-on experience. One Notable partner reduced prior authorization times from days to minutes by receiving responses while patients were waiting in the office. This is exactly the kind of concrete victory that transforms skeptics into believers.
6. Create a strategic workforce transformation plan
Artificial intelligence will change the way healthcare workers do their jobs; There is no way to avoid this reality. However, successful organizations will approach this proactively and transparently, focusing on what artificial intelligence can do, rather than human work.
Consider a front desk role; by automating data collection tasks, AI can allow staff to focus on what matters most: patient interactions. “Stop requiring front desk staff to serve patients well if you also require them to be bill collectors,” Henriksen advised.
Don’t let your AI strategy become the “third rail” that everyone is afraid to talk about. Instead, involve your employees in planning the evolution of their roles. The Medical University of South Carolina is an example of this ten-year strategic planpreparing employees for future opportunities rather than leaving them anxious about change.
7. Establish long-term platform partnerships
Who you work with matters more than what specific products you buy. “You’re not just buying today’s product – you’re buying a company and a partnership,” Neinstein noted.
Avoid the temptation to rely solely on an electronic health record (EHR) provider or collect dozens of point solutions. EHRs are the backbone, the “load-bearing walls” of hospital operations, but the transformation requires partners that can move more nimbly while maintaining enterprise-grade reliability.
Look for customizable platforms that can solve many problems as your organization grows. The right partners will lend a hand you lead the rapid evolution of AI while staying focused on your core mission: delivering exceptional patient care.
What’s next?
The organizations that will thrive in 2025 won’t necessarily have the largest AI budgets or the most advanced technology. Success will be achieved by those who approach artificial intelligence strategically, adapt it to their mission and focus on solving real problems of their patients and staff.