From reactive to proactive: Health systems look to AI and digital to flip the healthcare delivery paradigm within 5 years

Finding 1: Executives say they must fundamentally change how they operate in the next 5 years—from reactive to proactive care delivery

Implications

The current paradigm of reacting to patient demand as it presents at health systems’ doorsteps is inherently inefficient. And it’s unsustainable in the face of the known challenges of the coming 5 years.  

Health systems previously invested significant time and money to overcome the intrinsic challenges in the reactive care delivery paradigm. They invested in costly brick-and-mortar care sites and staff but did not substantively change the underlying care models or technologies supporting them. By treating the symptoms rather than the cause, they realized only modest improvements in addressing patient health needs but failed to drive the necessary transformational change that would address the underlying cause of the inherently inefficient, reactive model.  

Optimizing the reactive model is necessary but insufficient. The US has a growing need for care, and expanding a model that is not financially viable on a marginal cost basis is not sustainable. If health systems are increasingly losing money on each marginal patient they serve, no increase in volume will ever make it up.  

Finding 2: Executives seem cautiously optimistic they will achieve the shift to proactive care with AI and other digital enablement

Large health systems are highly confident they will see results, but even small and mid-sized health systems are more confident than not.

Academic health systems are further along with clinical decision support and care at home  
Academic health systems are more likely to be piloting and implementing clinical decision support (63% vs. 48% overall) and digitally enabled nonacute care at home (60% vs. 38% overall). This may reflect that academic health systems were among the first to pilot acute care at home capabilities and are now translating their learnings to nonacute care at home programs.

9 in 10 are prioritizing digital and AI tools to serve more patients  

With resource pressures only increasing, executives are planning to grow their capacity through digitally enabled care models that don’t require additional facility square footage or clinical headcount. 

Implications

As health systems shift to a proactive paradigm empowered by digital enablement, they are rightly focused on transforming access, personalizing the patient journey, fitting resources to demand, and serving more patients.

Health system leaders are increasingly confident that digital and AI enablement will be the key to creating a dynamic operating model that’s faster, less capital-intensive, and capable of proactively addressing care issues upstream.

Successful health systems will more accurately predict and efficiently manage their clinical demand instead of simply reacting to patients presenting at their “front door.”  

Leading health systems will leverage real-time data insights to forecast patient health needs. This will allow them to anticipate demand and deploy earlier, less intense, more clinically appropriate interventions to avoid complicated, resource-intensive, higher-cost downstream care. They will proactively engage consumers to better characterize their health needs and direct them to appropriate access channels and care settings. These increasingly digitally enabled channels and settings will be more accessible and drive better outcomes at lower cost.  

Finding 3: Executives believe the key differentiators of leading health systems in 5 years will be a digital-first experience and digitally enabled care 

Implications

Executives anticipate that what differentiates health systems from their competition will soon change. They agree that historically important attributes, such as size, won’t remain a key differentiator in the future.  

In fact, size or growth alone won’t insulate health systems from the multiplying industry challenges. Size can theoretically yield economies of scale and lower operating costs. Conversely, given the complexity of the transformation that must occur, size can also create significant challenges that make the necessary changes more difficult to achieve across the larger enterprise.

The playing field is more level as smaller health systems have an opportunity to differentiate through increasingly important digital strategies. Considering the growing expectations of consumers and staff for more digitally forward ways to deliver, receive, and maintain healthcare, a digital-first experience is a particularly low-regrets strategy. 

What’s next: Our recommendations

Health system executives seem to know what they need to do over the next 5 years: They need to redesign operations for proactive care delivery, enabled through innovative AI and digital tools.  

Now, they must establish the foundation and intensively execute to achieve transformative results. Several factors will be critical:

• Prioritize investments that will enable proactive care in the four major domains. Health systems should align their digital investments with opportunities to redesign care and operating models for nimble flexing of supply to demand. These investments need to demonstrate not only efficiency gains in specific processes but also transformation of entire domains of core activities. The result should be deployment of more proactive care models that yield improved direct financial results. 
  
  Health systems should also explicitly consider how they will quantify and measure these gains in their existing books of business. A common mistake is assuming proactive care models only work in value-based care payment models or are “table stakes” with no tangible ROI in fee-for-service settings.
• Aim for business transformation, not just process digitization. Until recently, organizations commonly viewed digital tools as process enablers, virtualizing a historically in-person activity or assisting with standardizing or measuring a process. But they weren’t typically deployed as an operational force multiplier that allows the health system to fundamentally redesign the business. Tools were largely viewed as technology overlaying existing people and processes, as opposed to technology enabling entirely different deployments of people and processes.  
  Agentic AI and other advanced digital tools can now augment people and processes to substantially increase capabilities (e.g., interpreting complex patient needs and recommending specific actions). And they can take on actionable tasks at scale (e.g., translating layperson prompts to schedule appointments, summarize records or test results, and triage patients to the right care setting). 
  
  With such capabilities, health systems can rethink how they apply these tools in novel ways to address long-standing problems (e.g., greater patient access), not just implement select digital tools as a means to modestly improve legacy process inefficiencies.
• Avoid pilot purgatory. Health system executives recognize the importance of across-the-board digital enablement for delivering proactive care. But piloting these capabilities is not the same as operationalizing them at scale—which is many orders of magnitude more challenging. This challenge is the fundamental difference between health systems that are doing digital, versus those that are focused on being digital. 
  
  The risk of stalling in the piloting phase is high, as people, processes, and culture present all the reasons not to change. Health systems must introduce discipline and clear commitment to their digital and AI transformation efforts. They must establish specific metrics for value creation, set clear timelines to demonstrate value, and design with future scaled deployments in mind.  
  
  Key practices that further drive transformative impact from pilot to scale include: aligning initial AI and digital projects with enterprise priorities; integrating the technology into existing workflows and strategic initiatives; investing in data infrastructure and readiness; and establishing robust change management capabilities that support enterprise adoption and scaling.
• Build in adaptability for future change. As technology continues to rapidly advance, health system executives will need to become dynamic learning organizations. They will need robust management systems that allow them to actively apply the lessons from both successful and failed digital and AI implementations into future iterations. Failure of transformation pilots isn’t bad, but not learning from them and adapting the direction can be catastrophic. 
  
  This organizational “muscle memory” is already becoming a differentiating factor between health systems that have tried the “let 10,000 flowers bloom” piloting approach and those that focus on generating value from highly structured pilots and subsequent scaled digital and AI deployments.  

Health system executives anticipate a paradigm shift from reactive to proactive care over the next 5 years. But it won’t happen with the flip of a switch, and it won’t happen without strong leadership. It will happen among organizations with strong, visionary leaders, who thoughtfully plan and build practical bridges from their current reality to a transformed future. Leaders who are consistent in their overall direction and investments will yield transformative results over the years to come.