The pace of change and innovation in healthcare is nothing short of staggering. Technologies once reserved for science fiction are now woven into the daily fabric of care delivery. New solutions emerge with an almost dizzying frequency (take 950+ AI or machine learning-enabled devices authorized by the FDA as of August 2024 as just one example.)
For many, this constant evolution feels like trying to keep up with a moving target–overwhelming and fraught with uncertainty. But as forces for good, health systems continue to master the balancing act between rapid innovation and responsibility, utilizing the most cutting edge tools that can safely improve clinician workflows and, most importantly, patient outcomes.
But finding that balance isn’t easy. At times, it seems impossible. With 24 hours in a day, how can a health system find additional resources to innovate as rapidly as technology and ensure its impacts are lasting?
The good news is that it doesn’t have to be overwhelming. A seamless move to the “brave new world” of clinical AI starts with a thorough strategy.
In this relentless maze of healthcare transformation, an AI strategy isn’t just offering a direction; it’s the compass that will help guide you to clinical innovation.
However, while many organizations recognize the need for an AI strategy, this journey can often feel confusing.
Your clinical AI strategy shouldn’t just involve choosing technology, but setting a course that aligns with your health system’s broader goals, navigating the nuances of each department and anticipating the needs of tomorrow.
Just as a compass helps explorers avoid aimless wandering, a well-defined AI strategy helps healthcare organizations focus on impactful, long-term goals. This strategic approach moves beyond a tech acquisition and ensures that this technology will be tailored to address the unique vision, needs and challenges of any given health system.
While AI use cases and needs vary across health systems, some of these ideas are universally applicable and may inspire new approaches you haven’t yet considered.
AI in healthcare spans a vast array of functions: billing, operations, patient care and more. Each domain has distinct requirements, much like the varied terrains on a journey. For instance, clinical applications involve FDA clearances and stringent data security and privacy considerations, while revenue cycle automation may focus on optimizing administrative workflows. With that, a one-size-fits-all AI strategy is bound to falter. Instead, health systems should adopt a multifaceted approach, with specialized strategies that reflect each department’s goals.
It’s important, however, to clarify that this piece and the strategic insights offered are centered around successful strategies seen within clinical AI initiatives.
Taking a long-term view, aiming for a 2-3 year horizon, helps ensure that AI initiatives are both scalable and responsive to evolving challenges. An Accenture report found that while only 15-20% of companies made the leap to strategic scaling of AI, these trailblazers enjoyed nearly three times the return of their counterparts, validating the importance of long-term, dynamic considerations when strategizing for AI. Short-term projects may provide quick wins, but they risk leading organizations back to square one, requiring constant re-evaluation and lacking the scalability needed to transform care delivery in a comprehensive way.
For health systems looking to scale, the choice between a platform and a point solution is pivotal. A platform, like a well-prepared travel itinerary, enables seamless expansion. In contrast, point solutions are often short-sighted, catering to immediate needs while limiting future growth. The platform approach, although initially demanding in terms of time and financial investment, can provide the infrastructure to support the widespread adoption of AI.
Think of a platform like Amazon or Apple’s App Store. They’re more than online marketplaces; they are ecosystems. Each service or application integrates seamlessly, allowing users to experience a unified journey without the hassle of individual contracts or complex integrations. In healthcare, point solutions showed proof of concept for clinical AI, but the lack of robust AI integration has stymied adoption.
Integrating 30-40 individual AI solutions creates workflow and management challenges but shifting adoption strategy to a platform approach will facilitate scalability. This shift will move health systems from one-off solutions towards an AI-enabled care transformation strategy, maximizing impact and driving meaningful outcomes.
Returning to our compass metaphor, strategic alignment in AI means knowing where you’re headed and charting a course that accounts for unexpected obstacles and changing conditions. Health systems planning with scalability in mind are better prepared to adapt, ensuring that their AI investments continue to deliver ROI and improve patient outcomes. This mindset protects them from short-sighted, piecemeal solutions that might satisfy immediate needs but fall short in the future.
Strategic alignment also means embracing cohesive AI strategies that span the entire enterprise, integrating applications seamlessly across functions. Health systems adopting this approach experience less friction in deployment and a more significant ROI, as their AI tools are part of a unified vision that supports broad organizational goals. Take, for example, this study in which an ROI calculator was developed to crunch numbers on the benefits of an “AI-powered radiology diagnostic imaging platform to inform decision makers interested in adopting AI.”
When accounting for strategic alignment, the study showed a substantial 5-year ROI amounting to 451% for implementing a platform in a stroke management-accredited hospital. The ROI increased to 791% when radiologist time savings were considered.
Strategic alignment isn’t just a guiding principle–it’s the key to maximizing AI’s full potential across a health system. When organizations commit to a cohesive, enterprise-wide AI strategy, they’re not just investing in technology: they’re setting themselves up to weather industry shifts, deliver lasting value and elevate patient care. With the right roadmap, these systems don’t just survive–they thrive, continuously reaping returns and pushing the boundaries.
Embarking on an AI journey requires more than technical expertise; it demands leadership, collaboration and a shared vision. AI is no magic fix for healthcare’s challenges, but with a robust strategy–our compass–it can help health systems navigate complex challenges and reach transformative destinations. By focusing on strategic, long-term planning, health systems can ensure that their AI investments align to boost present needs and future aspirations.
The path forward is clear for those with the foresight to plan for it. Clinical AI is not simply a tool but an essential component of an aligned, sustainable strategy that can truly elevate care delivery.
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