At this year’s Becker’s Payer Issues Roundtable, one message came through consistently: the challenge for payer organizations isn’t new ideas. They need execution that measurably bends trend while keeping decisions defensible in a more scrutinized environment. Across markets, leaders described a world of tighter margins, higher acuity, member disruption, and growing expectations that plans will coordinate care across an increasingly constrained provider ecosystem. At the same time, artificial intelligence (AI) was everywhere in the conversation but mostly as a means to improve workflows and decision making, not as a standalone strategy.
The Spring event, held April 13–14 in Chicago, brought together hundreds of payer executives, operators, and partners across tracks focused on health plan strategy and innovation, population health and value-based care, and AI and digital transformation. In the hallways and sessions, the themes were consistent: cost and trend control; a rising chronic and behavioral health burden; operational and regulatory complexity; the need for auditable decisions (especially in payment and risk); network/provider capacity limitations; and pressure to modernize data and technology without creating tool sprawl.
Top themes we heard from payer leaders
- Cost and trend pressure are the defining challenges
- Chronic disease and behavioral health are rising and costs are concentrating
- Provider capacity make navigation and decision support essential
- “Defensible” decisions are becoming non-negotiable
- Value-based specialty models are a near-term innovation hotspot
- Medicaid’s expanding scope increases complexity and feasibility matters
- AI is an enabler but data readiness and governance determine ROI
- Competitive advantage is shifting to capabilities and operational excellence
Speakers described the current cost trajectory as unsustainable. Rising unit costs, higher morbidity and comorbidities, and utilization patterns are pressuring employers, plan design, and provider operations simultaneously. Leaders are increasingly hesitant of implementing initiatives that cannot be clearly connected to medical cost impact or total cost of care (TCOC). Administrative efficiency matters, but it isn’t enough. Every investment is being evaluated through the lens of whether it meaningfully changes decisions and outcomes at scale.
Panelists noted a marked acceleration in chronic disease burden, including earlier onset in younger populations, which raises long-term trend and strains care delivery capacity. Behavioral health was repeatedly highlighted as both a clinical priority and a financial one. For example, a relatively small segment of members with serious behavioral issues and/or substance use disorder can drive a large share of inpatient and emergency department costs. Leaders pointed to emerging approaches that focus on engagement, diversion from avoidable ED use, and stronger pathways into treatment, such as partnership with community resources for people experiencing a lack of stable housing.
As complexity rises and capacity remains constrained, “do more care management” is not a complete answer. Plans are looking for ways to route members to the right setting, reduce friction in specialty journeys, and equip clinicians and care teams with a small number of high-confidence actions they can take now. Several sessions emphasized that interoperability alone doesn’t solve the problem. Information has to arrive in a form that’s usable in real workflows.
Across MA and beyond, leaders described a shift from “capture everything” to diagnosis validity and defensibility. The same expectation is showing up in payment integrity and prior authorization: decisions need to be transparent, traceable to source data and clinical guidelines, and supportable under audit. This theme came up frequently in conversations about AI adoption. Although “black box” approaches may be impressive in demos, they are harder to operationalize where trust, compliance, and reputational risk are at stake.
While value-based care adoption remains uneven by market and model, the most “practical innovation” stories often centered on high-cost specialties, such as oncology and cardiology, where navigation across fragmented journeys is challenging and where a vendor or partner may be willing to share risk. Multiple speakers stressed that these models succeed only when the operating model is clear. Aligned incentives, timely data exchange, and day-to-day workflows can make it easier for providers and care teams to act.
In Medicaid discussions, speakers pointed to a growing emphasis on social drivers of health (e.g., housing and nutrition) alongside a persistent pressure in balancing what Medicaid “should” cover versus what impacts health, especially under limited budgets. Even when evidence supports an intervention, operational and regulatory friction can undermine execution. Plans are being asked to do more, but they need implementation pathways that fit state requirements, documentation standards, and partner capacity.
Many sessions framed near-term “operational AI” as the most tangible value today. Capabilities such as workflow-embedded assistance, pattern recognition, and automation are designed to help people make faster, better decisions. But speakers were clear about what gets in the way: data quality, integration, and unclear ownership. Several leaders advocated unifying data governance and AI governance so data rights, privacy, and intended model use are resolved consistently. Another persistent concern centered on AI tool sprawl. Buying many point solutions can raise cost and complexity without improving outcomes unless there is a coherent architecture and a disciplined use-case strategy.
Across panels, particularly those focused on MA, leaders emphasized stability, retention, and execution. In a volatile environment, clear benefit design, proactive communication, and operational discipline during enrollment and onboarding were framed as differentiators. Looking ahead, many organizations are doing heavier multi-year scenario planning (often referencing the 2027–2029 window) to prepare for policy shifts, utilization pressure, and risk model changes. Sustained performance comes from repeatable capabilities.
How Milliman MedInsight helps payers turn these themes into measurable action
The common thread across the Roundtable was the need for a practical “data-to-decisions” operating model: trusted data, consistent definitions, and analytics embedded in workflows where people actually work. Milliman MedInsight (MedInsight) is designed to support that model, helping plans integrate claims and clinical data, standardize measurement, and deliver actionable insights across cost and trend management, population health, value-based care, and performance programs.
Total Cost of Care (TCOC): identifying what’s driving cost and what will change it
When cost pressure is the constraint, the first requirement is a consistent way to measure TCOC and understand where dollars are going and why. MedInsight helps plans standardize and segment utilization and cost so teams can compare performance across lines of business, markets, and populations, and then isolate the specific services and conditions driving trend. From there, plans can monitor whether an intervention is actually moving the underlying cost and utilization signals it was intended to change. For plans supporting employer groups, MedInsight can also streamline how cost and utilization stories are packaged and shared to help stakeholders align on the same facts and trade-offs.
Defensible decisions: connecting evidence, data, and workflow in risk adjustment
With scrutiny increasing, plans are prioritizing traceability and documentation discipline across risk adjustment. MedInsight supports these needs by helping organizations connect data to action in structured workflows, so suspected conditions, supporting evidence, and outcomes can be reviewed consistently. For example, our Risk Adjustment Platform unifies claims, clinical, and CMS data, enriches it with HCC and risk attributes, and applies AI-driven recapture analytics to prioritize opportunities and streamline coding workflows. The goal is not “automation at all costs,” but faster, more consistent decisions with a clear audit trail.
Data readiness and AI ROI: building a shared source of truth from reliable data
Many Roundtable discussions concluded that data readiness is the gating factor for sustainable AI. MedInsight’s approach is to help payers consolidate claims, clinical, and other data into a usable foundation with consistent definitions, so insights are comparable, explainable, and trusted. That foundation, supported by the MedInsight Data Confidence Model, provides teams with a consistent environment for analytics, governance, and reporting where they can build well-defined use cases, measure outcomes, and scale what works.
Where payer leaders can start now
- Make cost impact measurable: define the few trend metrics that matter most, and tie initiatives to those metrics.
- Prioritize concentrated risk: identify the highest-impact cohorts and build pathways you can monitor end-to-end.
- Design for defensibility: ensure decisions have evidence, traceability, and consistent documentation.
- Choose workflow-first AI use cases: start with narrow deployments that reduce friction and improve decision quality and then scale with clear owners and outcomes.
- Align on a shared truth: standardize definitions across claims and clinical views to reduce payer–provider friction and support quicker action.
- Prevent tool sprawl: rationalize analytics and AI investments around a governed platform strategy.
- Plan by market reality: tailor actions for MA (retention/defensible risk), ACA (ops excellence), and Medicaid (feasibility under state requirements).
What resources are available?
- Schedule a call: Connect with one of our healthcare analytics experts.
- Visit our website: Learn more about our flexible Payer Platform, Risk Adjustment Suite, and Risk Adjustment Platform and how they can scale to meet your specific needs.
- Read our blog: Learn how CareFirst modernized their analytics approach to deliver measurable cost of care impact across the enterprise by embedding analytics into day-to-day workflows, aligning stakeholders around shared metrics, and prioritizing use cases with clear ROI.
