HLTH’s annual ViVE conference is one of the industry’s largest events focused on the business of healthcare and digital health innovation. Hosting leaders and innovators from across the healthcare space—including providers, payors, medtech developers, and investors—ViVE 2026 kept its focus on where healthcare’s headed, while also taking a hard look at some of the critical challenges facing the industry today.
Couldn’t make it to Los Angeles for the event, or just need a recap? We’ve got you covered. The Definitive Healthcare team was in attendance again this year, showcasing our strategy-driving data and analytics and tuning into the latest in digital health happenings.
From artificial intelligence and data interoperability to price transparency and patient access to health information, several themes connected sessions and discussions throughout the event. Here’s what we learned.
AI is making an impact—but are we using it to its fullest potential?
Artificial intelligence (AI) dominated conversations across the conference, highlighting healthcare’s continued push from pilot programs toward large-scale deployment across a variety of functions.
ViVE put this technology front and center with its dedicated space, the AI Zone, where attendees explored real-world applications like clinical decision support, predictive analytics, and workflow automation. Within the event’s panels and demonstrations, speakers emphasized several priorities for healthcare organizations adopting AI—as well as some caveats worth considering:
Clinical decision support
Machine learning (ML) models help clinicians diagnose disease and identify treatment pathways earlier. Whether rapidly scanning medical images for anomalies or analyzing patient medical records for diagnostic trends, the speed at which AI/ML models can parse and draw conclusions from vast datasets is undeniably a boon for overworked providers.
A session led by a representative of wearable device company WHOOP suggested that some of the most valuable data used in clinical decision-making actually comes from outside of clinical settings, where consumer-grade wearables and other smart devices can deliver recommendations based on real-time biomarkers and assist with early signal detection, prevention, and behavior change.
Operational automation
Agentic and generative AI tools can reduce administrative burden and improve workflow efficiency by automating routine tasks like scheduling, medical coding, and chart transcription. One session reviewed more than 300 AI solutions and found that AI-driven staffing and scheduling tools returned up to six hours per day(!) to nurse managers.
But while these tools save time, “shadow AI”—the use of unauthorized AI in the workplace—presents a potential threat to organizational cybersecurity and patient privacy.
Some organizations at ViVE say they’re training and leveraging their own secure, HIPAA-compliant AI agents. Whatever the use case, as AI becomes central to organizations’ operating models, enterprise-wide AI governance is increasingly being seen as a necessity by major players in the industry, with pillars including:
- Responsible AI review boards
- Cross-functional oversight
- Secure-by-design, secure-by-default principles
- Technical guardrails to prevent misuse
It’s not just about cybersecurity and compliance (though these should remain top priorities for all healthcare organizations); it’s about treating trust as the most critical currency—once it’s lost, it’s hard to regain.
Predictive analytics
Modern AI algorithms can help providers predict patient needs and outcomes on a population level, improving population health management and giving organizations selling into healthcare an opportunity to understand consumers more intimately.
One key predictive use case identified at ViVE 2026 is point-of-care clinical trial matching. This technology examines patient data to instantly match patients to one of hundreds of active clinical trials, connecting them with potentially life-saving experimental care while expediting and streamlining the research process at large.
Across applications, one message recurred: The successful use of AI depends heavily on high-quality data infrastructure. Industry leaders highlighted the importance of integrating clinical, claims, and operational datasets to ensure their models can generate reliable insights at scale.
Price transparency is both a challenge and strategic priority
Another theme with plenty of momentum at ViVE and beyond is healthcare price transparency. As regulators and employers push for greater visibility into healthcare costs, organizations are investing in technologies that improve pricing data accessibility and comparability.
Discussions at ViVE explored how price transparency initiatives are reshaping healthcare in a variety of ways—and why the system feels so broken to consumers.
For starters, the U.S. multi-payor system is inherently complex. Unlike other industries, there’s no set “market price” for a given procedure or pharmaceutical product. Multiple payors, negotiated rates, and proprietary contracts complicate pricing further, leading to a muddled market where price and quality are not strongly correlated.
To make matters worse, patients often discover coverage limitations, prior authorizations, and unexpected costs after a clinical decision is made, potentially resulting in unpaid care and bad debt for providers.
That’s why it’s ultimately a good thing—for patients and providers—that patients’ expectations are shifting toward clear, plainly outlined pricing structures. Whether through direct-to-consumer drug sales, cash-pay options, or discount tools, providing consumers with a retail-like experience is a competitive differentiator that pharmaceutical and care organizations can’t afford to pass up.
As with AI implementation, having access to reliable data is a prerequisite for effectively advancing price transparency. By combining cost and utilization data with clinical insights, employers and payors can more clearly understand the market and negotiate better value for themselves and their beneficiaries.
However, panelists at one healthcare pricing discussion cautioned that transparency efforts should not come at the cost of safety and efficacy. Successful organizations—especially those dealing in pharmaceuticals—will have to strike a balance between clinical oversight and patient accessibility.
Patients have unprecedented access to their own data
While many patients find themselves lost in the fog when it comes to healthcare pricing, they have a more clear-eyed look at their own healthcare data than ever before, thanks to national interoperability efforts like the Trusted Exchange Framework and Common Agreement (TEFCA).
Today, the average patient has access to records from three to four sites of care, and sometimes twice as many compared to those operating under traditional Fast Healthcare Interoperability Resources (FHIR)-based protocols. Discussions at ViVE 2026 explored how data transparency is another way to both foster trust and improve outcomes through encouraging patient engagement in their own care.
By making the patient the “conductor” of their own healthcare data ecosystem, patients are empowered to make more informed care decisions faster, reducing complexity, improving cost and access issues, and ultimately elevating the quality of care.
As patients gain more control of their healthcare data, certain technologies and care models could see a boost, including consumer-facing health apps and APIs, personalized digital health services, and remote monitoring and virtual care. Forward-thinking organizations should focus on building experiences that empower patients to participate more actively in their care by embracing these modalities.
There are still hurdles to overcome—standardizing identity verification, digital consent, and the role of AI in the process are all questions in need of answers—but if the trend continues, healthcare could see the further erosion of data silos and a greater emphasis on value-driven consumerism.
Data infrastructure and interoperability underpin innovation
Although AI may have been ViVE 2026’s most visible theme, data infrastructure was the foundation underlying nearly every session and conversation.
Panelists, healthcare leaders, and exhibition hall visitors repeatedly discussed the need for scalable data platforms capable of integrating information across electronic health records, claims systems, and third-party data sources.
Through TEFCA- and FHIR-based interoperability frameworks, real-time clinical data exchanges, EHR overlay platforms, and API-driven processes, major industry players are relying on technologies to create unified datasets that empower advanced analytics and AI-driven insights.
The Definitive Healthcare platform does just that. Combining carefully cleansed, curated, and compliant datasets—including all-payor claims, reference and affiliations data, consumer and population data, and more—with advanced analytical tools, Definitive Healthcare gives organizations across the healthcare space rapid access to insights that can shape strategy, guide decision-making, and support more effective patient care.
Easily accessible via our online platform or integrated within your existing systems and workflows, our intelligence gives you a clear view of the populations, organizations, and markets you need to understand to succeed. Sign up for a demo today to see how we can help you find your place on the cutting edge of healthcare.
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