Join this engaging panel discussion to gain expert insights into how modern utilization management is evolving to meet new regulatory demands while improving care delivery. Hear directly from state and industry leaders as they explore how data, technology, and collaboration are transforming prior authorization processes, reducing administrative burden, and enhancing transparency across Medicaid programs.
What you'll learn:
- Key Regulatory Updates & Challenges:
Understand the impact of CMS interoperability and prior authorization rules, including new timelines, reporting requirements, and transparency mandates—and how states are preparing for implementation. - Implementation Strategies & Innovations:
Learn how states and partners are leveraging data-driven decision-making, automation, and portal enhancements to streamline workflows, improve provider experience, and optimize utilization management practices. -
The Role of AI & the Future of UM:
Explore how artificial intelligence is being applied responsibly to support clinical decision-making, increase efficiency, and maintain accountability—while keeping clinicians at the center of care delivery.
Participants
- Andrea Browman, RN, BSN, Vice President of Care Management, Acentra Health
- Katrina Etter, DNP, RN, CMCN, Director of Clinical Operations, Indiana Family & Social Services Administration (FSSA)
- Sean Harrison, EVP, Chief AI & Analytics Officer, Acentra Health
Read the transcript
Note: This is a polished transcript of the full session and is not intended to be a verbatim record.
Opening and policy context
[Approx. 00:00] The session opens by highlighting the critical role of modern utilization management (UM) in ensuring members receive the right care at the right time while controlling costs. Speakers frame UM as a key driver of healthcare access, quality outcomes, and equity, particularly for vulnerable Medicaid populations.
[Approx. 05:00] The discussion shifts to the evolving policy landscape, with a focus on the CMS Interoperability and Prior Authorization Rule (CMS-0057-F). This rule introduces new requirements around faster decision timelines, transparency, and data sharing, signaling a major shift toward more efficient and accountable Medicaid operations.
CMS interoperability and regulatory changes
[Approx. 10:00] Panelists break down key components of the CMS rule, including 72-hour turnaround times for expedited requests and 7-day timelines for standard prior authorizations, as well as requirements for clearer denial rationale and public reporting of UM metrics. These changes are designed to reduce administrative burden and improve provider and member transparency.
[Approx. 15:00] The conversation also explores API-driven data exchange, including patient access, provider access, and payer-to-payer APIs. These capabilities aim to improve care coordination, data interoperability, and continuity of care across Medicaid programs and managed care transitions.
State implementation and operational strategies
[Approx. 20:00] States share how they are preparing for implementation by shifting from reactive to proactive prior authorization models, leveraging data and provider input to streamline workflows and reduce delays. A key focus is identifying services suitable for rules-based or automated approvals.
[Approx. 25:00] Operational improvements include enhancing provider portals, standardizing processes across fee-for-service and managed care, and increasing transparency around benefit criteria and utilization limits. These efforts are positioned as foundational to improving provider experience and compliance.
Data-driven decision making and transparency
[Approx. 30:00] A central theme is the importance of data analytics in utilization management, enabling states to evaluate which services require prior authorization, detect cost drivers, and monitor compliance. Data is also used to optimize resource allocation and reduce unnecessary administrative burden.
[Approx. 35:00] The panel emphasizes that increased transparency—through real-time authorization tracking, clearer criteria, and improved communication—builds trust among providers, members, and stakeholders while supporting better health outcomes.
Technology, automation, and AI in utilization management
[Approx. 40:00] The discussion turns to technology-enabled UM solutions, including member and provider portals, automated notifications, and rules-driven approvals that streamline submission and decision-making processes. These tools are designed to accelerate access to care and reduce friction for providers.
[Approx. 45:00] Artificial intelligence is introduced as a key enabler of efficiency, with use cases such as clinical documentation summarization, criteria matching, and automated correspondence generation. AI helps reduce review time while improving consistency and accuracy in decision-making.
Responsible AI and stakeholder considerations
[Approx. 50:00] Panelists stress the importance of responsible AI use in healthcare, emphasizing that AI should support—not replace—clinical decision-making. Maintaining a “human in the loop” is critical to ensuring fairness, accuracy, and compliance in prior authorization determinations.
[Approx. 55:00] Concerns around transparency, provider trust, and regulatory oversight are addressed, with recommendations to establish clear governance frameworks and align AI use with federal guidelines and risk management standards.
Infrastructure, innovation, and closing takeaway
[Approx. 60:00] The session highlights ongoing investments in digital infrastructure, automation, and interoperability readiness, including enhanced communication tools, API integrations, and continuous system improvements to meet CMS requirements.
[Approx. 65:00] The closing takeaway emphasizes that the future of utilization management lies in data-driven strategy, advanced technology, and strong state-partner collaboration. Organizations that invest in automation, transparency, and responsible AI will be best positioned to improve care delivery, reduce administrative burden, and achieve better Medicaid outcomes.