In January of this year, we identified four key trends that would impact Patient Support in 2026¹: measuring efficiency, AI in case management, direct-to-patient models, and navigating growing compliance expectations. Now, more than halfway through the year, we are looking at what has happened, where momentum is building faster than expected, where adoption remains uneven and what these developments mean for patient support leaders moving forward.

Trend #1: Healthcare economics will force leaders to define and measure program efficiency in new ways

Outcome: Efficiency is expanding beyond activity metrics to focus more on patient access progress.

Key takeaways:

• Access progress matters more than activity alone. Leaders increasingly want to understand how quickly and effectively patients move from prescription to therapy, including benefits investigation (BI)/benefits verification (BV) turnaround, prior authorization (PA) submission and resolution and where patients encounter barriers.
• Technology is improving speed and visibility. Automation, digital workflows, and payer/pharmacy benefit manager (PBM) connectivity can streamline access work and surface barriers earlier, while the right balance of technology and human support will vary by program.

Performance expectations are advancing faster than commercial models. Manufacturers are placing greater emphasis on access performance and service quality, even as traditional FTE and hybrid fee structures remain prevalent.

Trend #2: Programs will use AI to reinvent patient case management

Outcome: AI is reshaping case management by shifting routine work to technology while preserving human accountability.

Key takeaways:

• AI is moving deeper into patient support workflows. Routine intake, documentation, status updates, and appropriate self-service can increasingly shift to technology, while people remain accountable for judgment, exceptions, relationships and escalation.
• The strongest model is high-tech and high-touch. AI and digital automation can expand capacity and consistency without removing the human interactions that matter most.
• The next stage is more proactive, personalized support. Predictive signals, next-best actions, and smarter use of program data can help identify barriers earlier and direct human support where it can add the most value.

Trend #3: Direct-to-Patient solutions will proliferate, expanding access to care while offering convenient treatment options

Outcome: Direct-to-Patient (DTP) solutions surged in 2026, with every top-10 manufacturer now in-market with at least one program.

Key takeaways:

• Policy tailwinds accelerated DTP. 2026 policy changes helped move DTP from an emerging innovation to a viable commercial channel by reducing regulatory uncertainty, promoting direct purchasing pathways, and increasing focus on patient affordability and pricing transparency.
• DTP moved beyond obesity. DTP models are beginning to influence specialty categories beyond the GLP-1 access channel, with 2026 growth spanning immunology, ophthalmology, oncology, hemophilia, Parkinson’s disease, and rare disease.

Prepare for the specialty inflection. Immunology, oncology, and rare disease are already part of DTP program growth plans. To live up to consumer expectations, program design must integrate concierge logistics, HCP support and complex clinical monitoring.

Trend #4: BV and AI-driven patient finance will face heightened scrutiny, raising both risk and opportunity

Outcome: Scrutiny is rising around data use, governance, and integrity in BV and patient finance.

Key takeaways:

• Governance is moving to the center. As automation expands across BV and patient-finance workflows, manufacturers are placing greater emphasis on permissible data use, privacy, security, auditability, and appropriate human oversight.
• Accountability extends across the ecosystem. Connected vendors, data sources, and workflows raise the importance of clear ownership and controls, particularly where health and financial information intersect and affordability-program integrity is at stake.

Performance proof is part of buyer expectations. Manufacturers also want to understand how automation performs across their patient population and payer mix before changing staffing or operating models, creating opportunities for solutions that can demonstrate both performance and strong governance.

Additional forces already shaping 2026 patient support program design

Beyond the original four predictions, two additional developments are already influencing patient support program design, operating models and manufacturer expectations in 2026: regulatory convergence and increasing PBM transparency.

Additional force #1: Regulatory convergence is reshaping patient support operations

AI and Call Center Policy: 2026 saw the acceleration of regulatory and policy developments influencing patient support operating models. For example, the proposed bipartisan U.S. federal bill, Keep Call Centers in America Act of 2025, along with mirrored Federal Communications Commission (FCC) 2026 Notice of Proposed Rulemaking (NPRM) and the FCC AI Disclosure NPRM examine offshore call centers, customer service, data security, AI calls, and consumer protections.^2,3

Outcome: Regulatory convergence is moving patient support operations beyond a cost-focused service model toward strategically governed engagement platforms in which compliance, AI oversight, patient experience, and operational performance are designed together.

Key takeaways:

• Governance is becoming a design requirement. As AI becomes more deeply embedded in patient support workflows, organizations need clear oversight, transparent practices, and defined escalation paths. The FTC’s proposed 2026 policy statement reinforces the application of consumer-protection principles to companies marketing AI systems.⁴
• Location strategy is evolving. The FCC proceeding is prompting renewed examination of onshore, offshore, and hybrid models, particularly for interactions involving sensitive information or consumer requests for U.S.-based support.
• AI deployment is shifting from efficiency to accountability. The question is no longer simply whether AI can automate patient support activities, but how organizations monitor AI-enabled interactions and transition to human support when needed.

Compliance, technology and operations are converging. Future patient support programs will need regulatory resilience built into operating model and solution design decisions from the outset.

Additional force #2: PBM transparency is reshaping affordability and access strategies

Evolving PBM Mandates: PBM reform, transparency initiatives, and changing pharmacy-benefit economics began influencing patient support strategy. The direction is not one nationwide mandate taking effect at once, but a multiyear transition: proposed Department of Labor disclosures could affect some self-funded ERISA plans beginning in 2027, the FTC settlement requires Express Scripts to offer a more transparent net-price-based option beginning in 2027, and broader statutory requirements generally take effect for calendar-year plans on January 1, 2029.^5,6,7

Outcome: Greater transparency is accelerating a multi-year transition from opaque rebate-driven models toward more visible pricing structures, point-of-sale affordability approaches, and net-cost benefit designs. Patient support programs will play an increasingly important role in helping patients and manufacturers navigate a more transparent but also more fragmented and technically complex access landscape.

Key takeaways:

• Affordability program economics are becoming more visible. Enhanced disclosure and reporting are increasing visibility into rebates, spread pricing, PBM and affiliate compensation, formulary economics, specialty-pharmacy practices, and manufacturer assistance. This creates a stronger basis for evaluating whether affordability support reduces patients’ financial burden as intended.
• Support programs must adapt to more individualized benefit designs. Transparency may make accumulator and maximizer activity easier to identify and design around, but it will not eliminate these programs. Manufacturers will need payer-specific rules and a broader portfolio of affordability interventions rather than a single copay model.
• The market is moving beyond traditional rebate models. Point-of-sale discounts, net-cost formularies, explicit administrative fees, cost-plus pharmacy reimbursement, and more structured specialty-benefit arrangements are changing how affordability is delivered and measured.
• Patient support is becoming an intelligence and orchestration layer. Programs will need stronger benefit verification, accumulator and maximizer identification, claims and deductible reconciliation, appeals support, and payer-specific analytics to show where assistance dollars go and whether they are benefiting patients.

In summary

As 2026 has demonstrated, patient support is evolving beyond traditional service models toward connected, outcome-focused engagement ecosystems. Organizations are increasingly balancing technology and human expertise to improve access, personalize support, expand care delivery options, and operate more efficiently. At the same time, advancements in AI, automation and digital engagement, along with pharmacy-benefit transparency, are elevating expectations for governance, transparency, accountability, and measurable outcomes. For patient support leaders, success in 2027 will depend not only on embracing innovation but on designing programs that deliver measurable outcomes while earning the trust of patients, providers, regulators, and manufacturers alike.

Driving better patient outcomes

IQVIA Patient Access and Support Services is enthusiastic about the importance of programs that help people start and stay on life-changing and life-saving therapies. Our team partners with manufacturers to improve patient access, strengthen engagement, support long-term adherence, and deliver high-performing support programs in an increasingly complex healthcare landscape. Learn how IQVIA can help advance your patient support strategy.