Four imperatives for health systems: What leaders must do differently in the new era of healthcare

Engaging consumers/patients early in their care journey is increasingly critical—and difficult—as consumers have more ways to seek immediate answers across seeking advice for symptom management, understanding diagnosis and/or treatment plans, engaging with a provider, understanding expected costs, and deciding where to go for care.  

Most individuals start these searches via search engines or AI chat models rather than on a health system’s website or through the electronic health record (EHR). Health systems that have invested in search engine optimization (SEO), answer engine optimization (AEO) and generative engine optimization (GEO) are ahead of the game. However, this will not be enough as chats now offer answers as part of the search and patients do not need to click through to the health system website.  

As more health tech companies emerge, competition increases for individuals’ and families’ mindshare for clinical care. These focused options are not replacing health systems’ advanced, comprehensive clinical capabilities today. However, they are impacting health systems in a different way—by raising expectations for convenience, immediacy, transparency, and guidance. Health systems will need to consider how they continue to win the position of authority and trust for health information and navigation. 

Many patients already split their care across multiple entities, leaving health systems with an incomplete view. To shape enduring relationships, health systems need to modernize how they attract, acquire, and continuously engage patients. They need to serve as an always-on resource. And they need to provide trusted guidance that helps patients understand what to do, where to go, and how to stay connected across their care and health journey. 

Essential actions for health systems to attract, acquire, and retain patients include: 

• Offer multiple channels (e.g., text, phone, chat, synch/asynch) for patients to engage with the provider or AI care agent to receive a timely response and easily schedule an appointment when needed. 
• Build real-time “search to resolution” capabilities across a diverse set of channels so that individuals can resolve their needs (e.g., pharmacy refills, scheduling an appointment, clinical questions) regardless of how they engage (e.g., through the website, via the patient portal, or directly with administrative staff or the care team). Each channel should provide consistent and transparent information on availability, price, and provider fit to enable comparison and selection.  
• Develop proactive, AI-enabled 24/7 support that extends patient assistance beyond the visit. Some examples include navigation guidance, proactive patient outreach to reinforce care plans, and “always-on” care management—all with elevation to a human clinician when needed. 
• Optimize online presence to show up where patients are searching for healthcare answers and providers—not just SEO but also AEO and GEO. 
• Deploy targeted digital marketing campaigns based on demographics or other tailored factors so the health system is top of mind when patients need them (e.g., age-indicated screening like mammograms and colonoscopies). This should include calls to action like “one-click” scheduling. 

According to a recent AMA survey, 43% of physicians express feeling a great deal of stress due to their job. Key reasons include ineffective EHR systems, concerns about leadership transparency and support, inadequate staffing, and excessive administrative tasks.¹ 

AI scribes are now in use by a quarter to a third of physicians today. Early indications are that while actual time savings have been modest, ambient documentation has helped improve physician satisfaction and reduce feelings of burnout.²  

In addition, health systems are deploying AI to reduce burnout for nurses by assisting with clinical documentation, curating relevant information from different sources onto a single screen, and augmenting clinical nurse practice skills—enabling nurses to spend more face-to-face time with patients.³  

As the 65+ population grows, demand for care is projected to far outpace the already constrained clinical workforce capacity. Health systems cannot meet this demand through hiring alone. As health systems look to deploy agentic AI in new ways, they must include physicians and clinicians in designing the new workflows, selecting and/or building technologies, and managing the change required for successful activation.  

Essential actions for health systems to engage physicians and clinicians include: 

• Deploy agentic AI capabilities within the care team to take on administrative and coordination burden, including documentation, prior authorization, referral tracking, and care plan coordination. This allows clinicians to spend more time in work that requires their clinical skillset, judgement, and relationship-building. 
• Extend the care team’s reach between visits through adherence tracking, early deterioration flags, at-risk identification, and proactive outreach and follow-up. AI-enablement will allow the health system to support and monitor more patients without adding clinician hours or workload. 
• Adapt proven AI-driven clinical innovations, such as real-time analysis of images and tissue slides in pathology, to flag abnormalities and prioritize the most acute cases.  
• Equip clinicians and the care team for AI-enabled ways of working through targeted training, reskilling, and change management. Effective AI deployment will require engaging physicians and clinicians who can shape the vision, trust the tools, and define and implement clear workflows, activation plans, and oversight models. 

Three ways the future model of care will restore the promise of clinical work

Health systems historically have struggled to manage avoidable utilization, such as avoidable ER visits and preventable (re)admissions due to the challenge of identifying at-risk patients before they deteriorate. Health systems have had limited ways to monitor patients from home and offer them support proactively, due to the high cost of clinicians. And when patients have concerns, they often end up in the ER for lack of other options.   

AI-enabled care management, remote monitoring, and new modalities such as asynchronous care are making it more feasible to close these gaps and reduce the cost of delivering care. To advance access, outcomes, and affordability, health systems need to build a care model that is more proactive between episodes and more flexible across settings.  

That means helping patients before needs escalate, guiding them to the right level of care when they need help, and shifting clinically appropriate care into lower-cost, more convenient settings. 

Essential actions for health systems to advance clinical care include: 

• Integrate data from multiple sources into a unified, longitudinal record, including care delivered elsewhere, patient preferences, and social drivers of health. This gives the health system visibility in order to surface the insights needed for personalized, up-to-date care planning. 
• Provide ongoing, proactive support between episodes of care, including remote monitoring with escalation protocols, care plan adherence tracking, and always-available access and support. Health systems will need to develop the necessary engagement infrastructure to sustain relationships between and beyond episodes of care. 
• Guide patients to the right care through an AI-enabled triage and navigation capability that reassures patients about which steps to take, routes patients to the appropriate level of care when a need arises, provides timely access and ease of scheduling informed by clinical needs and patient preferences, and reserves acute capacity for genuinely acute demand.  
• Coordinate care journeys, including sequencing of required testing, timely review of diagnostics, and clear next steps, as well as closed-loop referrals and coordination when patients leave the health system for care. 
• Facilitate timely and convenient access by making scheduling easy and timely when care is needed, instead of requiring patients to call multiple numbers. Health systems should have standard protocols for which patients should be seen via virtual visits versus in-person (taking into consideration patient preferences) and which patients are prioritized based on clinical need. 

Reimbursement models may not fully pay for the new, emerging sites and modes of care, such as hospital-at-home, remote/virtual care, and AI-enabled asynchronous care. However, offering these new sites and modes of care will be essential to attracting and retaining patients, lowering the cost to deliver care, and creating capacity.  

While health systems cannot fully control financing dynamics or the pace of payment reform, they should act now on the levers they can control, such as avoiding capital outlays by creating lower-cost care settings and modalities; reducing avoidable utilization; aligning internal incentives; and negotiating or advocating for new payment models that support innovative care delivery models.  

Fee-for-service will likely remain the dominant reimbursement model for the near future, but health systems should also shape and take advantage of alternate financing models as they emerge.  

The Centers for Medicare & Medicaid Services (CMS) and other payers are adding targeted payment mechanisms that support proactive care management, technology-enabled services, and accountability for outcomes and total cost of care. These models create small funding pathways and operating templates for the care model changes health systems increasingly need to make. 

Essential actions for health systems to make the economics of care delivery more sustainable include: 

• Create capacity and avoid large capital outlays by deploying new models of care. Health systems should understand how much capacity they could create by moving care to different sites and modalities (remote, home, synchronous/asynchronous) and the opportunity to reduce avoidable ER visits and inpatient (re)admissions. They should factor cost and capital avoidance into business evaluations of these new models of care rather than solely focusing on how much fee-for-service reimbursement may be lost.  
• Partner with payers and employers to fund care model innovation. Craft new payment models with innovative payers and employers. This can be particularly effective where new capabilities enhance patient experience and manage the cost of care. Employers want less friction in their employees’ healthcare experience and manageable costs, and they may be willing to pay for innovations that achieve these goals.  

• Align internal incentives. Many physicians are paid on a production basis, which puts their desire to spend more time with each patient at odds with having to increase the number of patients they treat each day. As routine care is offloaded to agentic AI care managers, the risk is that physicians’ schedules are loaded with more acute patients. As the care model changes, how physicians are compensated must also change.

  The same applies for leaders throughout the health system. For example, if executives are incentivized for keeping beds or physician offices full without considering the mix of patients, shifting to new care models that decant these care settings can be challenging.

• Drive conversations with payers, employers, and policymakers regarding new payment models. Beyond risk-based and incentive-based payment models, health systems should advocate for alternate payment models that support the new, emerging models of care. For example, this could include payments for providing remote and asynchronous care; shifting care to lower cost care settings; and reducing avoidable (re)admissions).  

Healthcare’s financing evolution: Today’s novel models are learning labs