For decades, consistent and effective member engagement has been an elusive North Star. Despite significant investment, many health plans remain trapped in a reactive paradigm, hindered by a “triple threat” of legacy constraints:
- paper-based processes that delay critical outreach,
- incomplete data silos that obscure member needs,
- and a one-size-fits-all approach to interventions.
The cost of this friction is no longer just administrative; it is existential.
As members increasingly demand the same seamless interactions they experience in retail, banking, and other areas of their lives, health plans that fail to modernize risk significant attrition. Recent data suggests that payers who prioritize a digital, consumer-centric approach can achieve a substantial rise in member satisfaction and measurable improvements in long-term retention.1 Health plans may also experience a subsequent rise in Centers for Medicare & Medicaid Services (CMS) Star ratings.
Still, the gap between strategy and execution is widening. While the industry is racing toward artificial intelligence (AI) adoption, a staggering 74% of healthcare leaders report that poor data quality and the lack of a “single source of truth” remain critical barriers to the successful use of technology, including advanced analytics and AI.2 Indeed, data fragmentation frequently leads to “mismatched” interventions—outreach that members ignore because it lacks the appropriate context. Whether a member is struggling with network navigation, care gaps, or rising social needs, the result of this mismatch is the same: eroded trust and missed opportunities for early, effective intervention.
New Architecture, New Approach
To bridge the gap and better engage members, health plans must first modernize the user experience. Delivering the hyper-personalized experiences required to drive member loyalty and clinical outcomes demands “a single pane of glass;” seamless data integration that gives care managers, utilization managers, quality managers, and other industry professionals clear and timely insights.
Forward-thinking health plans are achieving this and enabling more targeted member interactions by leveraging a modern strategy comprising three foundational pillars:
- A unified data platform. This makes more complete and fully integrated data readily available and usable, and normalizes disparate data streams into actionable insights.
- State-of-the-art digital tools. These permit health plans to shift from traditional outreach methods (e.g., telephonic) to digital solutions capable of more personalized, real-time member connection.
- Traditional AI + emerging AI capabilities.These include using AI-driven clinical intelligence engines to automate “next best actions,” with the potential for agentic AI solutions to orchestrate entire processes in a compliant and efficient manner.
With these three pillars in place, health plans can manage complex populations and risk more effectively—becoming the proactive health partners that members desire. Following is a practical assessment of each pillar, offering a clear-eyed view of modern member engagement and what the future holds.
Pillar #1: Unified Data Platform Facilitates Action
Bringing together fragmented clinical, behavioral, and social data is a critical first step toward achieving the holistic picture of members’ health needed to drive stronger engagement and better outcomes. Yet, as every health plan knows, it is no small task to accommodate data originating from countless systems in a multitude of formats.
Solving the challenge requires flexible data ingestion—the ability to bring any data, in any format (i.e., structured, semi-structured, or unstructured) directly into a single, unified platform. Such flexibility allows health plans to distill data faster, transforming it into intelligence that supports decision-making and timely action.
Ideally, a unified data platform should be able to improve outcomes at scale by:
- Enabling compliance with interoperability regulations, including the Interoperability and Prior Authorization Final Rule (CMS-0057-F) that requires Application Programming Interfaces (APIs) for patient access, provider access, payer-to-payer information exchange, and prior authorization. A unified data platform represents a crucial first step toward accomplishing the systemic overhaul of data-sharing capabilities desired by CMS.
- Applying analytics and intelligence to surface actionable insights.
- Enabling real-time workflows and automated care actions.
- Identifying which members need support, what actions to take, and when to intervene.
Here is a real-life instance that illustrates the impact of one such platform.
Case Example #1: Data Transformation
One health plan with a rapidly growing member base was struggling to operate with a variety of data sets—provider, labs, eligibility, authorizations, clinical alerts based on ADT messages, etc.—that were inconsistent in quality and format. The inconsistency presented a significant obstacle to effective digital transformation.
To simplify data management, the health plan leveraged a cloud-based data platform purpose-built for health plans and providers. Because the platform could easily ingest data in its native formats, the health plan avoided the substantial time and cost typically associated with data conversion. Instead, raw data is now standardized and integrated to provide a holistic view of members’ health journeys in real time. In this case, the health plan chose to update most data daily. The exception is real-time ADT clinical alerts, which are ingested at 15-minute intervals (as soon as the health plan receives them from its vendor).
Today, the data flowing into the system is refined by a clinical intelligence engine that also automates the “next best action” according to the health plan’s rules, alerts, and strategies. It provides the segmentation and personalization needed for deep insight into each member’s health journey. It feeds directly into risk-segmented campaigns and workflows—including care management, utilization management, and population health.
Within just a few months, these and other platform features helped the health plan achieve and maintain a 74% member engagement rate. Since deploying an associated suite of digital care management tools, 46% of the health plan’s members have completed their behavior change and plan-of-care goals.
Pillar #2: Digital Outreach Drives Meaningful Care Management Engagement
All care management programs are rooted in the mission to improve clinical and financial outcomes concurrently. This holds true whether performing health risk assessments (HRAs) or engaging members in disease-management programs.
Consequently, the industry has expressed significant interest in closing care gaps and strengthening member engagement through technology-enabled care management. However, a recent report reveals a stark disconnect between expectations and reality when it comes to digital care management (DCM).3
Medecision, in conjunction with Sage Growth Partners, conducted a national survey of 50 health plan executives that shows health plans are trying to deliver more personalized, data-driven care management at scale, but are often held back by outdated systems and manual processes. Among the survey’s findings:
- Only 8% of health plan leaders say their DCM tools can act in real time.
- 52% report their tools fail to engage members effectively.
- Although 98% of health plan leaders aim to personalize member outreach, just 10% can do so today.
- 65% say seamless data integration is critical—yet only 17% say their platforms deliver it.
Nevertheless, despite those findings, health plans that have successfully leveraged DCM confirm that the expected benefits can be realized. Here is another case example that exemplifies the possibilities of DCM.
Case Example #2: Enhanced Member Engagement
A Midwest-based, diversified portfolio of health plans serving 26 million members primarily in the Midwest and South decided it was time to adopt a digital-first care management strategy. The plans hoped that doing so would improve care managers’ workflows and free them to spend more time engaging with members.
Over a six-month period, 40,000 members were invited to participate in a DCM program:
- 100% of contactable members were successfully invited via email or SMS in the initial six months of go-live.
- 43% of those reached via DCM journeys engaged meaningfully with the program.
Integrating DCM required minimal care manager administrative effort, yet the health plan portfolio’s DCM engagement metrics were significant:
- 61% program completion rate
- 49% open rate (i.e., number of emails/messages opened)
- 23% click-to-open rate [i.e., number of link clicks (Yes, No, More Information clicks)]
By embracing digitization, this portfolio of health plans:
- Improved operational efficiency
- Enhanced member engagement
- Laid the groundwork for continuous future innovation
Pillar #3: “Conventional” AI Sets the Stage for Scalable Orchestration
Health plans are increasingly turning to AI-driven technologies to fill the gap left by long-established care management and utilization management strategies, which struggle to keep pace with administrative and regulatory burdens, workforce shortages, and complex member needs.
For instance, predictive AI-generated insights and recommendations already enhance member satisfaction in many care management programs. They automate outreach, improve data-driven decision-making, and expand digital engagement across all risk levels.
Utilization management workflows, too, can benefit from the amplified efficiency and member responsiveness offered by conventional AI and automation, as evidenced by the following case example:
Case Example #3: Streamlined Prior Authorization
Case Example #3: Streamlined Prior Authorization
One Virginia-based health plan sought to boost efficiency while simultaneously reducing provider and member abrasion. It was determined to tackle its prior authorization process, which lacked data integration, automation, and AI-driven workflows.
Automating prior authorization workflows can also help health plans build a robust regulatory compliance infrastructure. This is an important step since modernizing prior authorization workflows is no longer optional for many health plans, due to the requirements in the abovementioned CMS-0057-F for FHIR-based prior authorization APIs.
The Virginia health plan chose to implement a healthcare-native data platform that allows users to streamline prior authorization and care reviews with AI-powered policy management and automated decision rules. Authorization requests were automated and seamlessly integrated directly into the platform, establishing efficient workflows and auto-approvals that expedited turnaround times and reduced the time and expense of previously manual processes.
The result was a dramatic 57% decrease in authorization turnaround times, with the process now taking less than a day. The improved workflow efficiencies also cut down on the number of staff resources required to address prior authorization phone calls. Yet even as the health plan reduced its headcount, members and providers voiced heightened satisfaction.
Over time—and with proper AI governance in place—health plans will increasingly take the next step into agentic AI. The value of agentic AI is that it does more than move data; it can seamlessly orchestrate the entire utilization management cycle for a more frictionless member experience. For instance, health plans can use agentic AI to:
- Automatically align cases to NCD/LCD guidelines and flag missing facts instantly with a prior authorization review agent.
- Enable “touchless” approvals with configurable engines that allow for “Gold Carding” and immediate auto-approvals for rule-compliant requests.
- Automatically assign complex cases to the right licensed expert with smart routing, thus eliminating bottlenecks.
Although scalable orchestration powered by configurable AI agents represents a new frontier in member engagement, it’s vital to take a responsible approach to data and AI that balances rapid innovation with value-aligned products and services. Even though federal regulation of AI has been slow to develop, nearly every state has introduced some form of AI-focused legislation. Among the areas of scrutiny are prior authorization, medical necessity, clinical oversight, and patient disclosure and consent.
So, agentic AI solutions must always consider emerging state legislation, be grounded in context, and be built to solve tangible health plan challenges—from managing rising workloads to reducing care team burden and achieving meaningful cost savings. Moreover, agentic AI solutions must be used to complement and amplify the skills of healthcare professionals, preserving critical human oversight at every step.
From Fragmented to Future-Ready: The New Architecture for Modern Health Plans
The path forward for health plans is no longer a choice between administrative stability and digital innovation; it is a mandate to unify both. As we have explored, cracking the code on member engagement requires moving beyond reactive, paper-based legacy constraints that obscure member needs and erode trust. True transformation is found at the intersection of a unified data platform, digital outreach, and intelligent AI orchestration.
By grounding technology in real-world clinical context, health plans can finally achieve the “single pane of glass” view necessary to deliver hyper-personalized experiences. Adopting this new architecture gives health plans end-to-end visibility, streamlined workflows, a consistent compliance infrastructure, and a future-ready foundation that improves productivity today while enabling automation and innovation tomorrow. This shift delivers tangible results across the enterprise, from care management teams finally receiving actionable context with fewer clicks to utilization management teams gaining the ability to route smarter and decide faster.
Ultimately, the architecture of intelligent health is built on the simple truth that better clinical and financial outcomes are inextricably linked to successful member engagement. The evidence is clear: when data flows seamlessly, and AI amplifies human expertise, organizations see dramatic improvements in operational efficiency and member satisfaction. Those who embrace these three pillars today will not only solve for the friction of the present but will emerge as the proactive health partners members demand for the future.
References:
- Healing consumer confidence through AI-powered, human-centered healthcare. McKinsey & Company. February 19, 2026. https://www.mckinsey.com/industries/healthcare/our-insights/healing-consumer-confidence-through-ai-powered-human-centered-healthcare
- Healthcare RCM Leaders Say AI Ambitions Are Running Ahead of Data Reality. Black Book Research. November 20, 2025. https://www.newswire.com/news/healthcare-rcm-leaders-say-ai-ambitions-are-running-ahead-of-data-22678902
- Medecision Report Reveals Disconnect Between Digital Care Management Expectations and Reality. Medecision. May 21, 2025. https://www.medecision.com/medecision-report-reveals-disconnect-between-digital-care-management-expectations-and-reality/