Category: Uncategorized

Operational efficiency isn’t just another key performance indicator—it’s the base that enables health plans to scale based on industry demands. As payers face mounting pressure to reduce administrative costs, meet regulatory demands, and deliver better member experiences, many turn to outsourced solutions. But not all outsourcing models are created equally.

Business Process Outsourcing (BPO) and Business Process as a Service (BPaaS) can both offer relief, but serve fundamentally different purposes: One adds capacity, the other supports acceleration.

When it comes to BPO models, payers contract with third-party vendors for distinct point solutions, like administration or claims processing. While BPO has the potential to enhance workflows for payers, it still relies on manual work rather than automation.

Meanwhile, BPaaS solutions are based in the cloud, allowing for enhanced automation and optimization for health plan business processes. BPaaS leverages advanced analytics, machine learning, and artificial intelligence (AI) technologies to simplify vital areas like claims processing, policy administration, and member enrollment.

BPO: The High-Control, High-Cost Path

BPO attracts health plans with its promise of immediate cost savings with lower labor costs.

Key Benefits:

• Immediate cost savings through lower-cost labor
• Automation of specific business processes
• Prioritization expertise through legacy knowledge and specialized skills

However, this deceptively simple solution often reveals significant challenges over time. While BPO providers focus on automating specific business processes, they frequently struggle with broader operational effectiveness.

Critical Challenges:

• Limited understanding of macro-level healthcare processes
• Insufficient investment in modern technology
• Reliance on outdated Core Administrative Processing Systems (CAPS)
• Struggle to adapt to evolving industry needs

The real cost challenge emerges as health plans scale. What begins as an attractive financial solution often becomes increasingly expensive through change orders and service delivery adjustments. These tools, frequently used to cover service delivery overruns during periods of fluctuating demand, gradually erode initial cost savings while making operations more rigid.

Technology Implications:

• Legacy systems struggle to adapt to business changes
• Limited investment in modern platforms
• Outdated data systems
• Growing cybersecurity risks
• Reduced operational flexibility

Instead of focusing on innovation and improving member experiences, leadership often becomes entangled in managing complex vendor relationships. Meanwhile, competitors who embrace more strategic partnership models gain significant advantages in the market.

BPaaS: Transforming Your Business

BPaaS goes beyond staffing—it reimagines how organizations can work. By combining cloud-based platforms, AI, and automation, BPaaS replaces manual workflows with intelligent systems that adapt, learn, and scale.

The healthcare industry is witnessing a transformative shift with the emergence of BPaaS partnerships. This innovative model fundamentally reimagines how health plans can operate, combining the cost efficiencies of traditional approaches with the strategic flexibility demanded by modern healthcare organizations. Unlike conventional operating models, BPaaS represents a sophisticated, connected ecosystem that extends far beyond the common misconception of being merely “BPO + Platform.” At its core, BPaaS delivers a comprehensive operational framework built on four essential pillars:

1. Pre-defined, configurable services that adapt to organizational needs
2. A scalable infrastructure that supports sustainable growth
3. Refined, standardized processes to help ensure operational excellence
4. Cost-efficient ownership model to maintain financial sustainability

What truly distinguishes BPaaS is its unwavering focus on agility and outcomes. Each health plan benefits from dedicated infrastructure specifically designed to support its unique operational and strategic goals. This tailored approach ensures organizations can maintain their competitive edge while advancing their long-term objectives.

The model delivers value through its:

• Seamless integration of emerging technologies
• Rapid response capability for regulatory changes
• Enhanced operational transparency
• Streamlined transition to value-based care models

In practice, BPaaS partnerships transform how health plans operate by creating a dynamic, collaborative environment. Organizations retain strategic control while gaining access to specialized expertise and advanced technological capabilities. This balanced approach enables health plans to focus on their core mission—improving member outcomes and driving innovation—while maintaining operational excellence

BPaaS isn’t about outsourcing tasks—it’s about upgrading your operating model.

Choosing the Right Model for Your Health Plan

If your goal is to extend the capacity of your team and maintain current workflows, BPO may be an option. But if you’re ready to modernize operations, reduce risk, and unlock long-term value, BPaaS offers a future-ready solution.

At HealthEdge®, we help health plans assess their needs and implement the right model. We would love to hear more about your organization’s goals and challenges. Let’s connect.

Read more about operating models and BPaaS in the whitepaper: Finding the Right Operational Model.

By Alice Zhan, AI team

Part 2: Technical Implementation

This is part two of a two-part blog series on HealthEdge’s AI Summarizer feature; this post focuses specifically on the feature’s technical implementation. Read Part One here for an overview of the business challenges and operational benefits.

Addressing Information Overload in Care Management

Healthcare organizations face a growing challenge as healthcare professionals struggle with information overload from extensive documentation. Our AI team recently developed the AI Summarizer feature for our GuidingCare care management platform to address this problem. This feature simplifies a care manager’s workflows by analyzing care management notes to generate a concise summary and a list of key action items.

The AI Summarization functionality can reduce care manager review time, translating conversational content from notes into specific tasks and insights.

A Platform-First Architecture

HealthEdge’s approach to AI implementation centers on building reusable platform capabilities rather than one-off solutions. Our AI team created a summarizer API within our broader GenAI platform, which manages the complex technical details that would otherwise burden individual product teams. These include decisions around model choice and temperature settings, as well as comprehensive logging, observability, and security protocols.

The platform also collects user feedback establishing a foundation for continuous improvement and future model evaluation.

This centralized infrastructure management allows product teams like GuidingCare to focus on what matters most for their specific use cases. Each use case defines its own summarizer configuration, including the input data schema, custom prompts, and desired output formats. This division of responsibilities enables each team to implement AI features as needed without creating bottlenecks. The result is faster deployment cycles and more targeted solutions that address specific business needs.

Embedding AI into GuidingCare Workflows

For GuidingCare, we embedded the AI summarization functionality directly into existing care management workflows through a simple “Summarize” button in the Member Notes interface. The technical architecture follows a secure data flow between components, including the GuidingCare UI, the GuidingCare Cloud API, the WSO2 gateway that connects GuidingCare to external services, and the AI Summarizer. Each layer manages specific responsibilities for data processing and security.

Behind the scenes, the summarization API follows a streamlined processing pipeline that ensures both reliability and traceability. When a summarization request is received, the system first loads and validates the configuration. The prompt template is then dynamically formatted using runtime parameters, the user-defined input data schema, and any optional prompt addenda before invoking the OpenAI chat API. Each operation generates comprehensive logs that capture both the formatted prompt and the resulting output, providing full audit traceability before returning the processed response to the requesting application.

One of the most impactful parts of this project was working closely with our business stakeholders to craft a carefully engineered prompt template. Through direct feedback from clinical teams, we learned that care managers primarily read extensive notes to identify their next actions. This insight drove the design of the prompt to not just summarize notes, but specifically extract actionable follow-ups, a distinction that makes the difference between a generic summary tool and one that directly addresses workflow pain points.

The prompt template uses a structured approach, instructing the AI to analyze clinical notes in JSON format and produce summaries that highlight key diagnoses, reasons for visits, and follow-ups or recommendations, along with a separate, clear list of actionable items. The system processes notes using a schema that includes note type, health notes content, care staff information, and timestamps. To balance comprehensiveness with performance, the summarization feature uses notes from the last 90 days of history. The 90-day lookback limit was established based on both performance and clinical factors—limiting the number of notes improved system efficiency while simplifying the summarization process for the model, reducing the risk of overlooking critical information or producing inaccurate content.

AI Safety and Quality Assurance

As with all AI systems, the inherent risks of inaccurate, incomplete, or unsafe outputs required careful consideration. Our implementation addresses these concerns through multiple layers of protection. The system architecture ensures that AI-generated content is exclusively derived from existing notes within the system, guaranteeing that the outputs are as reliable and secure as the input data. This design principle prevents the AI from introducing external information or making claims beyond the information in the clinical record.

The platform provides comprehensive logging and audit trails for each summarization, enabling ongoing evaluation, monitoring, and debugging. The feature incorporates responsible AI protocols, including explicit AI-generated content disclaimers and human validation, ensuring clinical judgment remains central to care decisions. We also subjected the system to rigorous testing that included both expected inputs and adversarial scenarios, helping to ensure reliability across various input conditions that might occur in real-world healthcare environments.

Security and Compliance

The implementation maintains enterprise-grade security through multiple layers of protection. Data transmission utilizes secure APIs with HIPAA compliance throughout the data flow, while authentication relies on OAuth 2.0 for secure API access. The underlying LLM services are hosted through Azure, leveraging Microsoft’s enterprise security infrastructure and compliance certifications, with all data remaining within HealthEdge’s controlled infrastructure.

Role-based access controls limit functionality to authorized users through a layered permission system that requires both appropriate role permissions and access to the underlying clinical data. This controlled rollout approach ensures proper governance while the feature undergoes early adoption validation.

What’s Next for AI in Care Management?

With intentional platform design, strategic prompt engineering, and robust risk mitigation, we have demonstrated how healthcare technology teams can effectively integrate AI to enhance clinical workflows—and this is just the beginning. Next, we are expanding the summarizer’s capabilities to include interactive features that will allow care managers to ask follow-up questions and engage in a conversational dialogue about member information. This evolution will transform the summarizer from a one-time analysis tool into a dynamic, intelligent assistant that provides deeper insights and even greater operational benefits.

To explore how HealthEdge is shaping the future of care with responsible, practical AI, visit Artificial Intelligence | HealthEdge.

A Day in the Life of a Payment Integrity Analyst

For a payment integrity analyst at a modern health plan, the gap between identifying a payment error and implementing a solution is often a chasm of bureaucratic delays, complex IT dependencies, and costly vendor engagements. This operational friction can drain resources and allow financial leakage to persist, undermining core business objectives. The traditional “pay and chase” model, defined by manual interventions and fragmented systems, is no longer sustainable in an industry demanding greater efficiency and accuracy.

What follows is an example of this paradigm shift, illustrating how one analyst transformed a months-long struggle into a single day of decisive action. This journey from operational gridlock to proactive control is powered by HealthEdge Source™, a platform designed to empower analysts and redefine what is possible in payment integrity.

The Old Reality: A Process Built for Frustration

Picture this: It was Monday morning, and I had just identified a recurring payment issue that our post-pay vendors had flagged repeatedly. Using traditional methods, a straightforward policy correction can become a months-long odyssey through bureaucratic quicksand.

First came the IT ticket—a detailed request queued behind dozens of other “urgent” priorities. Then the vendor coordination dance began: multiple meetings, new requirement specifications, and cost estimates that made the Chief Financial Officer wince. Timeline projections often stretched into the next quarter. All the while, the same incorrect payments continued to flow out the door, compounding the financial impact.

The savings speculation phase was particularly painful. Without real, accessible data, we were forced to make educated guesses about the financial impact, potential provider disruption, and member effects. When we took these vague projections to policy approval committees, they demanded concrete numbers we simply did not have. The inevitable result was endless delays, frustrated stakeholders, and a growing pile of payment inaccuracies that our post-pay vendors were happily collecting their contingency fees on.

This was the nightmare of traditional payment integrity—layers of bureaucracy standing between identifying a problem and actually solving it.

The New Reality: Welcome to Payment Integrity Paradise

Fast-forward to today, and I’m working with HealthEdge Source Platform Access. That same Monday morning scenario now unfolds with precision and speed.

9:00 AM – Problem Identified

I notice the same payment issue hitting our post-pay reports again. Instead of reaching for my IT ticket template, I open the Advanced Custom Edit tool within HealthEdge Source.

9:45 AM – Solution Created

Using the intuitive user interface, I configure a new payment rule logic that precisely addresses our policy requirements. There are no developer tickets or external vendor requests. I have direct control to configure complex logic, including member history analysis, frequency limits, and sophisticated date range calculations. In forty-five minutes, I have architected and built a solution that previously would have taken months to implement.

9:50 AM – Environment Deployment

With a few clicks, my newly configured edit is available in both our pre-production and production environments. The platform’s configuration hierarchy means I do not need to tediously enable it across every single setup. I simply activate monitor mode for our entire Medicare, Medicaid, or Commercial lines of business.

9:51 AM – Data Collection Begins

From the very next claim hitting the HealthEdge Source program, I’m collecting invaluable impact data. I can instantly see how this new edit affects our provider networks and member plans across the board. The speculation is gone—replaced by real, actionable intelligence.

10:00 AM – Historical Validation 

While Monitor Mode quietly collects prospective data, I activate the HealthEdge Source What-If Modeling capabilities on our historical claims. Within minutes, I’m running two years of claims against my newly created edit, validating my edit has resolved the issue while revealing exactly where payment inaccuracies occurred and quantifying what accurate payments should have looked like.

The Power of Immediate Intelligence

Armed with concrete data, I can now approach policy approval committees with confidence. The platform provides the insights needed for targeted network education and drives more strategic contracting decisions. HealthEdge Source analytics transform raw data into compelling narratives that stakeholders can understand and act upon.

This is the most exciting part. I’m no longer dependent on external vendors for identification and recovery. That historical analysis immediately becomes a recovery project package. I can notify providers of the inaccurate payments and initiate recoupment processes, all while eliminating those painful contingency fees that drain our budget.

A Complete Transformation in One Day

By 5:00 PM on that same Monday, I’ve accomplished what previously took months:

• Identified a payment policy problem
• Developed a comprehensive solution
• Deployed monitoring across multiple configurations
• Collected real-time impact data
• Analyzed historical payment patterns
• Packaged overpaid claims for recovery
• Eliminated vendor dependency and fees

The New World of Payment Integrity 

HealthEdge Source delivers more than process improvement—it represents a fundamental shift in how payment integrity functions. The platform completely reimagines what is possible when payment integrity analysts have direct access to powerful, intuitive tools. 

We have moved from reactive cycles to proactive, data-driven decision-making. From months-long implementation timelines to same-day solutions. From educated guesses to precise intelligence. And from costly vendor dependency to self-sufficient, in-house expertise. The future of payment integrity is not a distant goal. It is here today, transforming how health plans approach payment accuracy, compliance, and financial stewardship with HealthEdge Source.

This is the new world of payment integrity, powered by HealthEdge Source.

Are you looking for more information on scaling your payment integrity process and streamline health plan operations? Read our case study: Transforming Payment Accuracy and Operational Efficiency at a Large National Health Plan.

In today’s healthcare environment, care managers are at the heart of improving outcomes for members with complex needs. Yet, the growing volume of documentation, assessments, and free-text notes often shifts their focus away from direct member engagement. We see firsthand how health plans are searching for ways to reduce this administrative burden while ensuring accuracy, compliance, and personalized care delivery.

At HealthEdge®, we believe artificial intelligence (AI) is a powerful tool to meet these demands. By embedding AI directly into care management workflows, we can accelerate information processing, identify actionable next steps, and empower care teams to do what they do best—deliver high-quality, person-centered care.

AI-Powered Care Management

Within the HealthEdge GuidingCare® platform, a comprehensive care management solution that integrates data analytics and workflow management tools to support evidence-based, person-centered care strategies, we introduced the AI Summarizer feature. This innovation streamlines how healthcare professionals process member information, enabling care teams to support more members at an increased scale while improving care quality and responsiveness.

The Information Processing Challenge

HealthEdge consistently hears from healthcare organizations that care managers face growing challenges with information overload from extensive member documentation. This challenge is especially pronounced for high-risk members, who may be contacted weekly or monthly, resulting in substantial volumes of detailed notes with free-text content that cover care plans, assessment responses, member outreach efforts, and more.

Through direct feedback from clinical teams, HealthEdge learned that care managers often read through extensive notes primarily to identify their next action items—what they need to do next for each member. This need for both background context and actionable next steps creates time-intensive workflows that reduce capacity for hands-on clinical work and individualized care planning.

Building Intelligence into Care Workflows

Recognizing the need for intelligent automation in care management workflows, our team developed an enterprise-grade solution using GenAI with stringent healthcare compliance standards. Our objective is to enable care managers to quickly assess and understand member needs while maintaining data privacy and clinical accuracy standards.

We embedded AI summarization functionality directly within existing GuidingCare workflows through a simple “Summarize” button in the Member Notes interface. The system analyzes all care management notes from the past 90 days using a carefully engineered prompt template approach. It then processes the input notes, extracting key member context and actionable items from the free-text content.

For example, when a care manager documents a phone conversation where a member mentions being unable to get medication refills due to financial issues, the summarizer feature can extract the specific action item: “reach out to community resources to find low-cost or subsidized medication options and share findings with member”—translating conversational content into specific workflow tasks.

The system produces two key outputs: a Member Summary highlighting key diagnoses, reasons for visit, and recent activities, plus an Actionable Follow-Ups section with a prioritized task list. This design responds directly to clinical team requirements for rapid identification of next steps for each member.

We implemented validation procedures, including testing and evaluation, along with integrated user feedback mechanisms such as thumbs-up/thumbs-down ratings and human oversight requirements. By collecting this feedback, we’ve laid the groundwork for continuous improvement, ensuring that user evaluations and suggestions directly enhance the precision and clinical applicability of AI summarization.

Security and responsibility remain at the core of everything we build. The solution maintains enterprise-grade security through secure APIs, HIPAA compliance, and role-based access controls confined to HealthEdge infrastructure. We also integrated responsible AI protocols, including explicit disclaimers about AI-generated content and human validation, so clinical judgment remains central to care decisions.

Operational Results and Performance

The AI Summarizer has already demonstrated a significant impact. It reduces care manager review time, decreasing the effort required to understand and act on member needs. This efficiency enables healthcare organizations to manage larger member populations while maintaining care quality standards through more informed and attentive clinical decisions.

Care managers now receive consolidated insights into member situations, with both background context and actionable next steps clearly identified. This supports faster response times and more targeted care approaches. Ultimately, our technology helps care managers redirect time from information analysis to direct clinical engagement—expanding their capacity for hands-on member care activities.

Delivering Immediate Impact

The AI Summarizer represents a practical solution to healthcare’s information overload challenge, delivering measurable time savings while maintaining clinical quality and compliance standards. For healthcare organizations struggling with care management efficiency, this technology offers immediate operational improvements with built-in safeguards for responsible AI deployment.

Looking ahead, we’re expanding AI capabilities across GuidingCare with enhanced interactive features, more intelligent summarization throughout workflows, and AI-powered agents designed to further streamline care management tasks. These upcoming enhancements will continue to reduce administrative burden while empowering care managers to focus on what matters most—delivering personalized, high-quality member care.

Shaping the Future of Care Management

The pressure on care managers will only continue to grow as health plans take on larger member populations and more complex care coordination. With our AI Summarizer in GuidingCare, we’ve shown how technology can transform documentation into actionable insights—helping health plans achieve operational efficiency without compromising care quality.

As we continue this work, we believe the future of care management will be defined by balance: smarter workflows powered by AI, and compassionate care guided by people.

Contact HealthEdge to learn how our AI Summarizer can streamline your care management operations and enhance member outcomes.