Setting the course to better healthcare: AI, consumerism, and trust-based alliances

Healthcare delivery has shifted from a hospital-centric model to a fuller continuum of care, with more care being delivered in ambulatory, virtual, and at-home care settings. In addition, remote patient monitoring devices are becoming more prevalent. Coupled with technological advancements that enable real-time processing of these data, this holds promise for more care moving out of traditional settings. 

With tomorrow’s future in mind, organizations can design and begin to operate expanded hybrid delivery systems as truly integrated, patient-centered networks that extend access and lower costs.

• Orchestrate a multimodal system of care. Financial pressures, capacity limits, and clinical innovation are fueling continued movement toward lower-acuity, lower-cost physical and virtual sites of care. Reimbursement and regulatory constraints may moderate the speed of these shifts, but the trend is toward a more digitally forward—if not entirely digital-first—era.

  Hybrid delivery models are becoming more prevalent, allowing providers to identify and address health drivers outside of episodic encounters. Examples include condition-specific virtual programs integrated with physical clinics, such as diabetes management programs, remote patient monitoring for high-risk, post-acute care, and hospital-at-home programs.

  Purposeful orchestration across next-generation networks of care will be critical. For example, leading organizations are expanding their command centers to direct care not just within acute care centers but also across their post-acute care and hospital at home networks. Organizations are also applying this concept of capacity management across sites of care to how they schedule cases for perioperative and ancillary testing, with embedded stratification for potential risk.

• Deploy real-time data insights to elevate performance. Healthcare is a data-rich industry, yet these data are often siloed and difficult to access in a “real-time” manner to drive behavior change. The availability of large language models (LLMs) and AI directed at healthcare should help drive proactive interventions, empower patients, support caregivers, and enable better and more sustainable health outcomes.

  Already, AI tools are supporting essential processes, including: 

  • Searchable medical information that can be delivered at the point of care to support clinicians in diagnosis and next best action
  • Clinical decision support (e.g., predictive models for readmission, sepsis, clinical deterioration, and risk of complications embedded directly into EHR workflows and point-of-care algorithms that drive personalized care at clinicians’ fingertips) that monitors and improves performance as it learns
  • Ambient assistants (e.g., automated note generation and clinical documentation improvement, and chart abstraction and summarization to reduce clinician burden and improve accuracy)
  • Operational intelligence (e.g., predicting bed demand, staffing needs, and OR utilization; and dynamically adjusting schedules and resources)

  Real-time data availability and point solutions require alignment with operating and business models as well as human-centered change management to shape new workflows and care pathways.

• Keep humans at the center of tech-forward clinical capacity. AI and other technological advances are showing early results in easing clinical workforce challenges. Programs like digital sitters are complementing in-person nursing teams, and ambient listening is reducing documentation time.

  Yet even for a relatively straightforward use case like an ambient scribe, patient concerns and clinician adoption rate plateaus demonstrate the complexity and sensitivities at play. Just making powerful tools available will not drive timely, measurable impact at scale.

  Organizations will need to mindfully engage their workforce and patients as they pursue even these first-stage AI opportunities within current clinical operating models and workflows. 

Consumerism flooded the healthcare lexicon in the early 2000s, fueled by enthusiasm for patient choice and market-style competition. Two decades later, the day-to-day reality of how patients and healthcare organizations interact remains largely the same. Yet where and how they receive health information has changed. 

Sixty percent of US adults say they’ve used AI to ask questions about their health or healthcare in the past 3 months. Top queries are about symptoms they’re experiencing, medical terms or instructions, and treatment options. Notably, most people seek information when facilities are closed, with 7 in 10 healthcare conversations in ChatGPT taking place outside of normal clinic hours.  

AI is pushing this new paradigm further toward technology, as consumers are increasingly loading their health data into AI for advice, a trend furthered by the recent release of ChatGPT Health. Almost two-thirds of consumers report confidence in the reliability of AI-generated information. Stories about “Dr. ChatGPT” abound, with some affirming experiences and some very serious risks, particularly related to mental health and suicidology.

Meanwhile, a recent consumer study noted that nearly 60% of adults reported using digital care in the prior 12 months. More than 50% own a wearable or connected device. However, generational differences are noteworthy around connectivity and trust.  

Health systems need to meet patients where they are headed in this emerging AI-enabled healthcare environment.  

• Shift from episodic patient treatment to lifetime consumer engagement. 
  The first wave of healthcare consumerism targeted certain aspects of healthcare as a “shoppable” service. For example, search fundamentally changed over the last decade from primarily word-of-mouth to web search. Scheduling also changed from call to online. In some cases, organizations coupled search and scheduling to nearly one click to make it as easy as buying an airline ticket.

  This next wave of healthcare consumerism innovation will shift the paradigm from episodic interactions to individualization and continuous engagement. For example, consumers could receive push notifications for customized preventive screenings (even beyond demographic-based screenings) with quick links for scheduling and embedded health information. A patient with a chronic condition could receive automated, interactive digital check-ins and medication support. And parents could receive age-based anticipatory guidance for their children, even when no one is sick.

  The health system becomes a health companion when it learns, anticipates, and acts, connecting outside of visits and creating a new kind of health relationship between individuals and organizations over a lifetime.

• Develop a new capability set to activate tailored engagement models. More traditional consumer industries use intent-to-action engines to surface services and products that anticipate consumer need. They then work to convert discovery to conversation, then engagement.

  Most healthcare organizations, however, have only a nascent understanding of their consumers’ needs or preferences. Health systems will need to make investments in the capabilities to garner consumer insights. These should include not only what consumers say they want but also how they act during their healthcare “buying” journey. This requires instrumentation to capture customer behavior and tailor experiences to reduce friction and optimize conversion.

  Additionally, health systems will need to build an enterprise-grade consumer data platform to marry relevant information sources and personalization capabilities required to operate with the precision, relevance, and behavioral insight consumers experience everywhere else.

  As health systems lean into technology-powered engagement, they will need to ensure that the digital divide does not leave individuals behind. Tailored models will accommodate a range of needs—not only the most tech-savvy consumers. This is the principle of meeting consumers and patients where they are (in the right venue or modality, in the channels they use, with experiences that are intuitive and adaptive).

• Define a roadmap toward clinical personalization and a connected care experience. Collecting more fulsome and timely data from the EHR, claims, wearables, and connected devices should enable better care and outcomes. This includes managing chronic diseases more effectively, facilitating early detection of diseases and health risks, shaping real-time insights at the point of care, and fostering shared decision-making between patients and providers.

  But moving from information collection to a more insight-driven, proactive, and personalized model of care requires real change in how providers and patients interact with each other and the health system.

  Clinical personalization design needs to begin at the level of clinical condition or patient cohort. It also needs to include the full patient experience across the continuum of care, with supporting clinical, financial, and operational enablement. Health systems can engage interdisciplinary design groups to position care teams and patients as co-owners of the model, and involve other functional stakeholders, such as revenue cycle and ancillary services.

  Shaping a roadmap will enable a deliberate transition to this model in a multi-phased approach. For example, in the first phase, technology enables broader health information collection, which the care team can review during treatment.

  The next phase moves from descriptive to predictive, identifying the patient is at risk. The care team receives an alert to reach out, review, and determine appropriate action.

  In the final stage, an agentic AI team member may communicate directly to the patient and automatically schedule an appointment based on a triangulation of care team input, clinical need, patient preference, capacity, and financial considerations.

Financial pressures and uncertainty are impacting all parts of the healthcare value chain. While past attempts to align segments along the value chain to moderate the total cost of care have had limited success, continuing on the current path is likely untenable. 

Technology-oriented investments and financial headwinds are fueling market consolidation, closures, and new entrants within each segment. Organizations will need to construct more bridges across historic divides to encourage shared value creation. Collaboration models should build trust and bolster the human connections that differentiate healthcare.

• Move beyond strained payer relationships to find common ground. Over the past year, payer and provider relationships seemed to take a step back. Margin compression on both sides drove many into zero-sum negotiation cycles and contentious disputes. Meanwhile, payer payment integrity and provider revenue cycle management are in an “AI arms race,” in which bots are fighting bots to speed processing and optimize payment.

  In many cases, these activities create near-term gains but may damage institutional and individual relationships longer term. Consumers bear the after-effect of payment policy misalignment when they are left with financial obligations or delayed or denied coverage or access.

  Mistrust in both payers and providers is widespread and growing. A 2025 consumer survey conducted by Jarrard, a Chartis Company, suggests that more than three-quarters of consumers believe insurance companies and more than two-thirds of consumers believe hospitals are placing priority on making money over caring for patients.
  
  The recent commitment of multiple leading health plans to simplify prior authorization is a constructive step toward a more effective model of interaction among payers, providers, and consumers. Other smaller steps can help build trust between parties—including finding new ways to deliver tailored consumer engagement to improve the individual financial experience. Better communication can also enable organizations to anticipate and mitigate unintended consequences of policy or contractual changes.

• Shape broader alliances to advance a more transformed ecosystem. Healthcare depends on community wellness at the human level (e.g., vaccines and screenings) as well as industry health at the corporate level (e.g., rural and safety net financial viability and clinician/workforce availability). Organizations that forge alliances to strengthen the broader ecosystem and their role in it will be better able to mitigate risks and position for the future.

  Examples may include:

  • Convening providers, social services, and community leaders to support vulnerable communities 

    An example is the South Side Healthcare Collaborative (SSHC), a member-driven network of federally qualified health centers, free clinics, and community hospitals. These organizations share a mission to improve the health of Chicago’s south side residents by advancing the work of its members through service, education, networking, and advocacy.

  • Creating educational partnerships to expand workforce pipelines and reskill existing teams
  • Combining industry funding to drive clinical research and innovation
  • Developing novel physician alignment and investment models to bolster services diversification
  • Shaping direct-to-employer services to address employer needs
  • Establishing technology arrangements to accelerate digital adoption
  • Exploring relationships with consumer and digital health companies to access new capabilities that go beyond traditional IT functionality  

  Organizations can elevate partnerships beyond transactional exchanges to deliver higher impact in the long term by grounding relationships in trust, aligned purpose, and compatible operating and governance models.

• Tell the organization’s story to reengage with federal, state, and local policymakers and rebuild community trust. Healthcare will remain in the political headlines and policy agenda. This will reveal deep divisions over the role of government in healthcare, fuel competition for increasingly scarce funding pools, and create uncertainty and noise.

  Against this backdrop, health systems will need to reposition from reactive to proactive partners in solution development alongside policymakers at the local, state, and federal level. To support this engagement and secure community trust, healthcare organizations will need to tell their stories: of their purpose, the critical role they play, and the individuals who rely on them.

  Effective communications will emphasize their day-to-day work with communities and patients, organizational mission, and impact. Transparency—particularly when hard decisions must be made—builds understanding and trust.