Artificial intelligence (AI) holds tremendous potential for healthcare payers but realizing that potential hinges on one crucial factor: data readiness. In a recent webinar hosted by Emids, ‘Modernizing Data Foundations for AI: How to Accelerate Value from Legacy to Cloud’, industry leaders from Snowflake, BHI and Emids came together to explore why many payer organizations are struggling to translate AI enthusiasm into real-world outcomes, and what they can do to change that. 

Fragmented Data Environments 

AI innovation is advancing at a pace that outstrips many organizations’ ability to adapt. For healthcare payers, this challenge is compounded by complex, fragmented data environments. From siloed systems and inconsistent formats to unstructured and incomplete datasets, the foundational infrastructure often isn’t equipped to support modern AI workloads. 

Transitioning from pilot programs to operational AI is especially difficult. Many payers struggle to define what to prioritize and how to scale proof-of-concept efforts into production-ready solutions. Without a clear roadmap and aligned data assets, progress tends to stall before value is realized. 

Data Modernization: Still an Afterthought 

While investments in cloud infrastructure and digital transformation continue to rise, the data that powers these initiatives is too often left behind. Managing unstructured data and fragmented clinical records is still treated as an afterthought in many payer modernization strategies. 

Without a data strategy that runs in parallel with digital transformation efforts, organizations lack the ability to generate the insights AI needs to deliver value. This not only limits immediate returns but also jeopardizes the long-term adaptability required to keep up with ongoing healthcare and technology innovation. 

There’s No AI Strategy Without a Data Strategy 

A key mistake many organizations make is treating AI as a standalone initiative. In reality, AI effectiveness is directly dependent on data that is governed, reliable, and accessible. 

Organizations must understand where their data originates, how it’s accessed, and how it is used across departments—from finance to medical management. Integrating AI into the enterprise-wide data strategy ensures consistent use of validated datasets and supports trust, auditability, and transparency across the organization. 

Lack of Business & IT Collaboration 

Payers embarking on AI modernization must resist the urge to pursue novelty. The most successful implementations start with solving specific, business-relevant problems. That might mean improving governance structures or bringing business teams closer to data engineers to align on real-world use cases. 

Too often, AI and data initiatives are siloed within IT, with minimal input from the business side. This lack of collaboration slows down value realization and disconnects data solutions from operational needs. Engaging business users early on ensures alignment, improves adoption, and builds momentum for broader AI integration. 

Legacy Platforms Block Unstructured Data 

Emerging data platforms now allow for seamless integration of structured and unstructured data—including PDFs, audio files, and clinical notes—into unified environments that support richer analytics. This level of interoperability is critical for advancing initiatives such as value-based care and personalized member engagement. 

Once connected to robust data foundations, AI agents can begin to accelerate analytics, automate data cataloging and quality checks, and even streamline schema generation. These capabilities bring significant operational efficiency to the enterprise. 

Low Trust in Data and Partners 

Trust emerged as a central theme in the panel discussion. Internally, trust is built through transparency and data lineage. Users need to understand what data informed an insight, how it was processed, and whether the output can be trusted. 

Equally important is the trust placed in partners. Many AI initiatives fail not because the models themselves are ineffective but because implementation partners lack the healthcare domain expertise needed to embed solutions into complex payer workflows. Trusted partners combine technical acumen with industry-specific insight to ensure AI delivers lasting impact, not just impressive demos. 

Moving Forward: Imperfect Data, Real Impact 

A common misconception is that AI requires perfect data to function. In truth, no dataset is flawless. What matters more is having visibility into data quality, identifying gaps, and building processes to improve incrementally. 

Success also hinges on finding internal champions who understand both the strategic and technical sides of AI. These leaders play a vital role in translating model performance into business value, balancing innovation with governance, and bridging the gap between data science and operational execution. 

Aligning for Real-World AI Impact 

AI’s promise for healthcare payers is real, but it will not be realized through technology alone. Payers must intentionally align AI goals with enterprise data strategy, invest in strong governance, involve business users early, and engage trusted partners with deep domain expertise. Those who start, even if imperfectly but strategically, will be best positioned to accelerate real transformation. 

Rising healthcare costs and chronic illness are shrinking payer profits. This has payers exploring wellness platforms as a path to better health outcomes and long-term gains, but many payers struggle to see ROI. The market is crowded—with established brands, niche apps, and influencers all competing for attention. To succeed, insurers must define a clear, strategic position or risk wasting resources and missing member engagement. Ignoring wellness altogether may leave them falling behind in the market and losing out on growth. 

Whether you’re a healthcare payer exploring wellness tools to revamp your member engagement, or you’re looking to enhance your existing wellness offerings to be more effective, this article explores how to design effective wellness programs and what tools can be the key to your success. 

Wellness Platforms and Their Strategic Importance 

Before we dive into building a wellness platform that delivers value and drives member engagement, let’s dig into the unique value potential they hold for payer organizations. 

• Lower healthcare costs through preventive measures 
• Reduce costly emergency interventions by promoting proactive health management 
• Strengthen competitive differentiation in a growing market 
• Increase member engagement and satisfaction   
• Gather actionable data insights to further optimize programs 

A study by the Mayo Clinic shows that effective wellness programs boost preventative health practices, resulting in healthier members with lower risk profiles and fewer emergency interventions. These programs often involve educational services, health risk assessments, and interventions like health counseling and support groups. 

Our research found that wellness platforms and their related functions are the least engaged digital health plan offering – yet 79% of health plan members consider wellness programs either somewhat or very important when choosing a plan.  

These member trends motivate payers to consider wellness tools and features to support their competitive edge and address gaps in digital engagement.  

For wellness offerings to be successful at engaging their members, payers need to focus on creating wellness platforms that are integrated, engaging, and scalable. They not only provide vehicles for long-term engagement, but they also position payers as authentic, trusted partners in their members’ health journeys.  

Ultimately, the best​ ​wellness platforms align member needs with organizational priorities to drive benefits for both payer and member. 

At Emids, we’ve developed our own wellness application design framework. WellXD outlines five design pillars formulated especially for wellness applications – Usability and Accessibility, Behavioral Design, Creative Design, User-Centered AI, and Wellness Ecosystem Interoperability. Together, these pillars establish a solid foundation for design to address the specific needs of members, rather than repeating ineffective practices common in the industry.  

Providing Value In a Saturated Wellness Market 

Creating a wellness service that truly connects with members and delivers ROI requires empathy, a thoughtful strategy and the right technology. But the saturation of the wellness market can complicate the role payers serve in the wellness ecosystem.  

Payers should begin by clearly defining business or operational objectives their wellness programs aim to achieve – whether it’s cost reduction, improved member engagement, or growth etc. – and then design digital tools that will effectively activate members to support those outcomes.  

Next, payers must take time to understand their members’ existing healthcare context. This includes identifying the technologies they already use to manage their health, the perceptions they hold about their insurance provider, and their expectations for support and care. This insight is critical to designing solutions that integrate meaningfully into members’ health practices.  

We conducted a survey in January 2025 about members’ digital engagement practices, and when it came to wellness platforms, members expressed the following as the most valuable digital wellness plan features:  

• Custom health advice based on personal health data 
• Health assessments followed by personalized plans 
• Connecting to third party wellness trackers, apps, and medical devices (e.g., FitBit, Apple Health, etc.) 
• Programs to help manage chronic conditions 

Generic, one-size-fits-all wellness platforms will not meet today’s high consumer expectations, where personalization is not a luxury, but a necessity. Through user-centered AI, wellness platforms can deliver tailored health advice, individual plans, and real-time guidance based on each member’s unique health data and plan benefits. This ensures members receive value at every touchpoint, fostering long-term engagement.  

Interoperability to Adapt to Changing Member Habits  

Outside of their health plan, the top five digital health platforms members engage with include fitness devices and wearables, fitness and exercise apps, health and wellness monitoring apps, existing provider portals or apps, and nutrition and diet apps. While payers may not want to compete to replace these platforms, it is imperative that they consider how their wellness platforms can integrate with them to provide members with an even better experience.  

Interoperability in a wellness platform allows payers to consolidate data from external sources to create a better understanding of each member and provide an elevated, personalized wellness experience. This also gives payers the ability to track and monitor changing member behaviors and health realities, so their wellness platforms can continue to deliver personalized value to their end users using real-time data.   

Keeping Pace with Wellness Tech 

The most comprehensive wellness platforms are meaningless if members struggle to use them. A seamless user experience with intuitive navigation is essential.  

Our survey found that across all digital functions, usability was scored at 3 out of 5 – presenting significant opportunities for improvement. What’s more, members rated usability as one of the most important factors influencing their engagement with digital tools.  

User Experience (UX) 

The level of competition in the wellness arena complicates payers’ navigation of the role they play within the landscape. It sets the standard for UX. Wellness leaders such as Strava or Apple Health understand the standards for UX and design for their platforms. A platform can feature valuable tools, but a poor user experience will likely have the user immediately downloading a different app that offers the same functionality.   

It’s good practice to invest in UX at the foundational level of wellness platforms. This not only ensures intuitive navigation, and ease-of-use throughout the platform, but also avoids costly redesign later on – which can frustrate users as they may continually need to learn to navigate a changing experience.  

Delivering Equitable Wellness 

UX ensures a positive interaction with digital tools, but for wellness tools to support everyone, it needs to be accessible. Improving access to the preventative health supports that wellness platforms provide is especially important for older members as well as members with disabilities and those with chronic conditions. These groups hold strategic importance for payers, as they tend to have higher costs of care and are more likely to benefit the most from preventative support like condition management, medication reminders, and customized treatment plans.  

Health insurance plans must take a proactive, structured approach to meet the HHS mandate, requiring all federally funded digital tools to conform to WCAG 2.1 Level AA standards. This begins with a comprehensive accessibility audit of all digital assets—websites, mobile apps and portals to identify and prioritize gaps. Accessibility should then be embedded into every stage of the development lifecycle, supported by team training on WCAG standards and inclusive design. Payers should also engage users with disabilities in usability testing to ensure real-world effectiveness and implement both automated and manual testing for ongoing monitoring. In addition, implementing a structured governance framework for accessibility and maintaining thorough documentation of compliance activities demonstrates a strong commitment to federal standards and helps mitigate potential legal and financial liabilities.  
 

Driving Better Health Outcomes Through User-Centered AI and Behavioral Design 

According to a Harvard University School of Public Health study, wellness programs have made an impact on member health, with medical costs falling, while absenteeism costs fell by about $2.73 for every dollar spent on wellness programs.  

Behavioral science principles can transform wellness applications into more than just informational tools. Understanding factors that influence behavior can help encourage members towards better health outcomes. Incorporating behavioral design to help members make better health decisions, form long-lasting habits, and meet their personal health goals.  

At Emids, our approach to behavioral design integrates insights from cognitive sciences, health behavior change theory, gameful design, and gamification. Design decisions for wellness platforms are thus made based on evidence-based principles known to encourage healthy behavior and promote sustained behavior change.  

As with accessibility, behavioral design is also becoming standard when it comes to wellness platforms. Each new app might have a flavor of education, goal setting, and feedback mechanisms. However, to truly stand out, it’s important to look beyond standard principles of behavior change, as sometimes, often overlooked mechanisms can have a powerful impact on member engagement. Those that pursue a level of human connection – that feeling that others like you are also on a similar journey – have proven to have an impact if implemented correctly. Often overlooked is how the wellness platform might adjust according to a user’s constantly evolving environment. Finally, keep in mind that as a member progresses through their health journey, their needs and expectations for a platform will also change. 

For more information on behavioral design and Emids’ BxD Framework, read our featured insight, Behavior Change is the New Frontier in Healthtech.  

AI for a Personalized Approach 

There is an entire spectrum of how AI can enhance personalization, customization, and individualization – ranging from targeted tone/voice/motivating language all the way to health journey decisions, treatment recommendations and prioritization of health goals. 

While it’s still important to give the user autonomy in their digital experience through customized options such as health journeys and actions, incorporating increased personalization through content, where users are presented with information that is best for their individual needs, can lead to the ideal state of an ‘individualized’ service. 

Take the Next Step Toward Member-Centric Wellness 

Wellness platforms are becoming an increasingly valuable tool for payers looking to improve member retention, satisfaction, and overall competitiveness. Success depends on knowing how to leverage their unique role within the wellness ecosystem—by implementing best practices across UX, accessibility, and behavioral design, and by using AI responsibly with the end user in mind. 

Our WellXD framework is built to support this kind of thoughtful, strategic approach. Are you ready to transform your wellness strategy? Talk to a WellXD expert today and learn how we can help you design innovative solutions to keep your members engaged, empowered, and healthy. 

If you’d like to learn more ways to improve your digital member engagement, be sure to read our Definitive Member Engagement Playbook. 

The successful implementation of AI in healthcare presents several key hurdles that enterprises must overcome to unlock their full potential. This is especially true for sectors like healthcare, where data security and integrity are paramount. 

Enterprises face a few primary hurdles when embarking on AI initiatives, which can include securing buy-in and willingness to invest from leadership, identifying if and how existing processes can integrate AI, and the availability of skilled professionals to develop and manage AI systems.  

While all these points impact the success of AI implementation, the truth is that it is your data readiness for AI (or lack thereof) that can bring progress to a screeching halt. 

Challenges to Healthcare AI Data Readiness 

In sensitive industries such as healthcare, the stakes of being data-ready are exceptionally high. Data integrity is crucial to essential requirements such as patient safety and diagnostic accuracy – as any data-related error can have serious consequences to patient outcomes.  

In fact, as per our recent Survey, only 5% of healthcare payers rated their data as truly ready for AI, and 68% described their data as average to poor in quality for AI use. 

The healthcare industry faces unique challenges to ensuring good data. Patient data is scattered across various platforms in the healthcare ecosystem who don’t all speak the same language, so to speak. Differing standards and formats across labs, imaging, EHRs, payer systems, etc. can result in fragmented data. This absence of a Single Source of Truth for healthcare data results in data inaccuracies and inconsistencies which leaves providers and payers with unreliable data, impacting the reliability of AI-driven tools and outputs.  

Further complicating matters, 75% of payers report persistent data quality issues in core workflows like claims, enrollment, and fraud detection. And a third of organizations still lack data integration across critical workflows. These gaps not only produce sub-par AI outcomes but also increase compliance and cybersecurity risks. 

These challenges are complex and shouldn’t be ignored. Addressing them is critical to not only realizing the full potential of AI, but so that your AI initiatives don’t create new or worsen existing problems, ensure regulatory compliance and increase vulnerability against cyber threats.  

Complete, uniform, accurate data that can flow between systems and tools, supports the promise of improved patient records, improving administrative efficiencies, and diagnostic support. 

Building Trust in Your Data 

Trust is a subjective yet vital component to effective AI practices and while it takes years to build trust in brands and people, there’s a prescribed method to improve trust in data: 

1. Strengthen the Data Foundation: Only 5% of payers surveyed have a mature AI roadmap, and 80% are still in the early stages of adoption. Ensure a robust and well-organized data infrastructure as the strategic backbone of your data ecosystem. This includes scalable storage for structured and unstructured data, data models and architecture, and more.  

2. Improve Reliability: Implement processes to enhance data accuracy and consistency. By implementing interoperability frameworks, investing in data integration platforms, and applying governance models to define ownership and access rights, your data will be ready to produce reliable AI-powered support. Without these, data silos persist—especially when 41% of payers cite data governance as their top challenge, encompassing issues like access control, data quality, and metadata management. 

3. Secure Your Data: Only 27% of payers surveyed have fully enforced governance policies to ensure compliance. Protect data integrity and confidentiality through robust security measures such as role-based access control, data encryption and regular monitoring and risk assessments.  

4. Make it Easily Accessible: Ensure that trusted data is readily available to authorized users and systems in order for it to perform at its full potential. Incorporate UX in user interfaces and consider creating dashboards and visualizations to help present complex data in easily digestible mediums.  

The Stakes Are High 

AI represents a significant opportunity – a potential goldmine – for your business. However, without a foundation of high-quality, trusted data, this goldmine can quickly become a landmine. 

Emids Can Help 

At Emids, we help healthcare organizations unlock the power of AI by starting at the source: your data. From designing enterprise-wide data strategies to implementing governance frameworks and quality engineering, we help you build the trust your AI depends on. 

Talk to us about how to turn your data into a foundation for trusted, transformative AI, and strike gold. 

It’s no secret amongst payer executives that digitally engaged members are more likely to schedule preventive care appointments, adhere to prescribed treatments, and are more likely to avoid costly emergency interventions and experience better health outcomes, overall. This enables payers to also reap substantial benefits – particularly in efficiency, cost management, and long-term profitability. 

As healthcare payers continue to prioritize digital transformation, ensuring accessibility is essential, not just as a compliance measure, but as a cornerstone of equitable healthcare delivery.  

Cognitive, communication and motor decline make it more difficult for older members or those with disabilities to use digital tools designed for the general population. So, when creating digital tools or functions, it’s critical that they be accessible by all members. However, the reality of accessibility across members can vary depending on various demographics such as age and health status. Members of an older demographic may not have the technological skills foundation to navigate digital tools like the general population and the presence of chronic health conditions or disabilities could impact how they use digital tools.  

Discovering Unique Member Needs 

In a recent Member Engagement survey, we found that overall, 20% of members do not engage with their health insurance plan via digital tools. Amongst the leading reasons for not engaging with their plans’ digital tools include usability issues and technical barriers, which was expressed by 10% and 11% of members, respectively.  

These findings indicate that plans are not doing enough to ensure their tools are accessible to those with lower technical experience or those who may have health conditions that limit their ability to utilize digital tools. By understanding their members, payers can improve accessibility and usability of digital tools to improve overall engagement and ensure all members can experience the benefit of digital engagement functions.  

Embedding Accessibility in Digital Transformation 

Accessibility must be embedded at the design stage of digital tools and account for the diverse needs of all members from the outset. By adhering to the Web Content Accessibility Guidelines, payers can create digital experiences that are perceivable, operable, and understandable for everyone. This includes providing text alternatives, sufficient color contrast, keyboard navigation, plain language, simplified navigation, and accessible multimedia content. Regular accessibility testing throughout the design, development, and post-launch phases ensures ongoing usability for members with disabilities. 

Consider how you can improve usability to meet these unique needs. Offer simplified portals, with easy access to most used functions, such as claims management, provider searches, and plan details. Incorporating accessibility elements such as screen readers in apps, simplified language, ASL-friendly video tools and voice-activated support to meet varied user preferences.  

Most importantly, ensure your digital tools have taken accessibility UX considerations in their design and functionality so that members with limited technical experience or health conditions that limit their abilities have equal ability to utilize digital functions and experience their benefit. 

Digital Functions for Equitable Healthcare Delivery  

Payers can take accessibility to the next level by tailoring digital tools to accommodate members’ specific needs. For instance, members with transportation challenges could benefit from easy-to-use transportation arrangement functions, a tool to arrange for home delivery of prescriptions, or improving access to telehealth.  

Members are more likely to express loyalty to their plan provider when they perceive them as supportive partners in their health journey. By tailoring members’ toolsets to accommodate their specific needs would not only improve digital engagement, it could improve member retention.  

By knowing what your members need, you can build digital tools that empower them to take charge of their health care and realize the value their plan provides.  

The ROI of Accessibility in Digital Engagement  

Healthcare payers can gain significant benefits by incorporating accessibility into their digital engagement strategies. Accessible platforms improve overall member satisfaction, reduce churn, and expand the reach of engagement tools to a broader audience. Coupled with omni-channel solutions, accessibility ensures payers achieve their goals of delivering equitable, proactive, and personalized care experiences.  

Accessibility also drives trust. By demonstrating a genuine commitment to inclusivity, payers solidify their reputations as member-focused organizations invested in the well-being of the communities they serve.  

Final Thoughts  

Accessibility is not only a legal and ethical responsibility but also a strategic advantage in expanding digital engagement for healthcare payers. By prioritizing user-centric design principles, adopting omni-channel engagement, and implementing ongoing evaluation systems, payers can create a seamless, inclusive experience for all members.  

For organizations looking to assess the accessibility of their existing digital tools or seeking expert guidance in redesigning their UX, reach out to learn how we can help you achieve compliance and create meaningful engagement at every touchpoint. Together, we can build a future where accessibility is central to digital health innovation.  

HealthTech leaders today face a growing set of pressures: shorter product cycles, increasing compliance demands, and the constant push to innovate while ensuring system resilience and scalability. In this environment, engineering teams are not just building software—they’re driving business performance. 

That’s where high-efficiency engineering becomes critical.  

What Is High-Efficiency Engineering? 

High-efficiency engineering is an end-to-end methodology designed to maximize impact at every stage of the development lifecycle. By prioritizing streamlined, goal-oriented workflows, it eliminates the bottlenecks that slow down progress and dilute value delivery. 

With an emphasis on automation, modular design, data-driven optimization, and built-in quality, this approach enables HealthTech providers to build faster, smarter, and safer—meeting market demand in real-time without compromising compliance or user trust. 

The Pillars of High-Efficiency Engineering 

Automation and GenAI 

Generative AI tools are transforming the way engineering teams operate. They automate repetitive tasks, accelerate debugging, and assist in code generation—cutting down development cycles while enhancing consistency. 

“AI enablement will become table stakes across solutions rather than a core differentiator.” 
— HealthTech Trends 2025 eBook, Emids 

Domain-Aligned Microservices 

Replacing complex, monolithic systems with domain-driven microservices brings modularity, flexibility, and speed. These components integrate easily into existing architectures and scale with evolving requirements—whether for patient data exchange, claims workflows, or provider systems. 

Data-Driven Decision Making 

With advanced analytics embedded into the engineering process, organizations can track engineering performance in real time, identify bottlenecks, and reduce risk. Metrics offer clear visibility into what’s working—and what needs to improve. 

Integrated Quality and Compliance 

High-efficiency engineering ensures quality is not a separate checkpoint—it’s embedded throughout. Continuous testing, automated validation, and compliance checks reduce manual errors and help teams stay ahead of regulatory requirements like HIPAA, GDPR, and FHIR. 

Why It Matters Now 

As outlined in the HealthTech Trends 2025 eBook, the sector is shifting toward a performance-first mindset. Organizations that fail to modernize their engineering approach risk: 

High-efficiency engineering is not just a way to reduce costs—it’s how leading HealthTech firms are building durable, scalable solutions that meet rising expectations. 

Moving Toward Efficiency and Innovation  

The HealthTech sector sits at the intersection of urgency and opportunity. Challenges like rising costs, inefficiency, and complex regulation may seem like barriers, but high-efficiency engineering provides a clear path forward. By adopting this approach, your organization can deliver cutting-edge digital solutions while achieving scalability, speed, and measurable ROI.  

Take the first step toward transforming your operations. Download our exclusive HealthTech Trends eBook to discover the latest innovations, emerging tools, and practical strategies for long-term success. 

Autonomous AI in healthcare is steadily transforming the industry by enhancing patient outcomes, optimizing operations, and strengthening security and privacy. As the technology evolves, HealthTech leaders are continuously refining their applications to unlock new opportunities and enhance existing solutions. 

Last week, my colleagues at Emids and I met with HealthTech leaders to explore best practices, insights, and opportunities in autonomous AI. The discussions underscored AI’s growing impact across the healthcare ecosystem. 

Key Areas Where Autonomous AI is Driving Value 

Patient Engagement & Digital Front Door Strategies 

AI-powered virtual assistants, chatbots, and intelligent automation are reshaping patient engagement. These digital front door strategies enhance appointment scheduling, streamline patient outreach, and provide real-time support—improving accessibility and experience. 

Clinical Workflow Optimization 

AI-driven healthcare tools are addressing serious clinician capacity challenges by optimizing clinical workflows, automating healthcare data integration management, and providing AI-driven diagnostic support. By reducing administrative burdens, autonomous AI allows healthcare professionals to focus on patient care. 

Revenue Cycle Management (RCM) 

AI-driven revenue cycle management solutions are beginning to impact healthcare financial operations by reducing human errors in medical billing, coding, and collections. Intelligent automation enables faster claim processing and provides actionable insights for revenue forecasting and financial optimization. 

Challenges to Overcome 

Healthcare Data Integration & Quality 

The effectiveness of autonomous AI in healthcare depends on high-quality, well-integrated data. However, as AI expands, integrating structured and unstructured data from multiple sources remains a significant challenge. Ensuring data interoperability and standardization is critical for AI reliability. 

Maintaining the Human Touch 

While AI-driven healthcare enhances efficiency, successful AI adoption requires balancing automation with meaningful patient-provider interactions. Technology should augment—not replace—the human element in patient care delivery.

Trust & Adoption Among Providers 

Healthcare AI adoption depends on trust, which requires transparent and explainable AI models. Clinical validation, regulatory alignment, and clear communication about AI’s role in decision-making are essential to overcoming skepticism—especially regarding AI-generated diagnoses and treatment recommendations. 

The Path Forward or Autonomous AI in Healthcare

Autonomous AI has immense potential to reshape healthcare, but successful adoption requires a thoughtful, strategic approach. Trust, transparency, and responsible implementation will be key to ensuring AI’s full impact while maintaining integrity in patient care delivery. 

If you’re in the early stages of exploring AI in healthcare, start by identifying where it can drive the most value for your business and clients. Partnering with healthcare AI experts who understand the healthcare landscape can accelerate adoption and ensure meaningful outcomes. 

Explore AI Solutions Tailored for Healthcare

At Emids, we specialize in harnessing the power of Generative AI to revolutionize healthcare product development. Our platform, EPulseAI, accelerates product engineering by up to 50%, ensuring faster time-to-market and enhanced accuracy.

Discover how EPulseAI can transform your healthcare solutions.

Healthcare payers face the dual challenge of enhancing member services while reducing operational costs in an ever-evolving tech landscape. While many turn to digital solutions, such transformations can be costly and time-consuming. At Emids, we help you leverage low-code platforms to unlock AI’s potential, streamlining operations and improving care delivery—faster and at a fraction of the cost. 

The Power of Low-Code and AI in Healthcare 

Low-code platforms are a game changer in the digital transformation landscape, offering healthcare payers the means to develop applications quickly and cost-effectively. Low-code solutions utilize pre-built modules and drag-and-drop interfaces, significantly reducing development time and cost while increasing quality. This has enabled healthcare organizations to deploy services at unprecedented speed, allowing them to adapt swiftly to changing market demands and regulatory landscapes. 

The integration of AI with low-code platforms allows healthcare payers to harness advanced technologies without the complexity typically associated with AI deployment. AI capabilities can be built into low-code applications, so payers can automate routine processes, derive insights from vast datasets, and deliver personalized member experiences. This synergy between low-code and AI helps payers optimize their operations and improve care delivery, while streamlining AI governance. 

Improving Claims Processing 

AI-powered claims processing systems built on a low-code platform can save time and minimize errors. One Emids client saw a 40% reduction in processing time and a 25% decrease in errors. This allowed them to reduce their cost margins and enhance member satisfaction through faster claim resolutions. Furthermore, low-code enabled them to deliver the solution in 33% of the original time and cost. 

Personalizing Member Engagement 

AI can create personalized health engagement plans, tailor recommendations based on member health data. This led to a 30% increase in member participation in wellness programs and a corresponding decrease in chronic condition incidents for an Emids client. Low-code resulted in half the cost and half the time to market than originally forecast. 

Automating Fraud Detection 

With AI-driven analytics integrated into a low-code framework, fraud detection processes can be automated to identify and mitigate fraudulent activities more effectively. This approach safeguards financial assets and preserves member trust and integrity. By deploying AI within Low-Code based solutions, AI governance is built-in. 

Low-code platforms, when combined with AI, offer healthcare payers a powerful toolkit for automation and enhanced care delivery. By streamlining processes, optimizing services, and deploying AI solutions with ease, payers can address operational inefficiencies while meeting the evolving needs of their members. This approach not only drives immediate benefits in terms of cost savings and efficiency but also paves the way for sustainable growth and innovation in the healthcare sector while safely leveraging AI. 

To unlock the full potential of low-code and AI in your operations, consider partnering with experts like Emids. With over 20 years of experience transforming healthcare for leading payers, we provide customized solutions tailored to your unique needs. Over just three years, we’ve delivered more than USD 50 million in savings to our customers by deploying intelligent automation. Let us help you bridge the gap between cost optimization and innovation through low-code solutions. Together, we can craft a strategic approach that meets your cost-effective care goals, enhances member care and supports sustainable growth for your plan. 

For payers, the balance between operational efficiency and rapid innovation has always been a delicate one. Traditional development approaches can be slow, costly, and inflexible, creating a gap between what payers aspire to deliver and what current processes allow. Low-code platforms, however, offer a transformative solution—an approach that promises not only to close this gap but also to empower payers with unprecedented flexibility, speed, and cost savings. By embracing low-code, payers can meet today’s demands and position themselves for tomorrow’s challenges. 

Low-Code Solutions Enable Cost Efficiency for Payers 

In the healthcare payer industry, maintaining and enhancing legacy systems requires substantial resources, while responding to regulatory changes demands continual innovation.  

Here’s where low-code solutions shift the paradigm. Unlike traditional development, low-code accelerates application creation through visual workflows, pre-built components, and model-driven logic, all of which reduce the need for extensive coding. Whether small work-group apps or mission-critical systems of record serving millions of customers, Low-Code can make the impossible, possible.  This results in reduced development and maintenance costs, faster deployment cycles, and greater financial flexibility. 

Consider the case of claims adjudication, a process central to payer operations. Low-code platforms can automate the claims adjudication workflow, allowing real-time adjustments and reducing manual interventions. By automating claims processing, payers cut administrative costs while delivering faster, more accurate service, enhancing both efficiency and member satisfaction. 

Accelerating Time to Market and Innovation 

For payers, innovation is not just a competitive advantage; it’s necessary to meet regulatory demands and evolving member expectations. Low-code platforms empower payers to build, test, and launch applications far faster than traditional methods. This acceleration enables payers to pilot new services, deploy member-focused applications, and adapt to market changes with agility. 

Data integration is critical for payers, coordinated care. Using low-code, a payer can create interoperable solutions that connect with FHIR and EMR/EHR systems seamlessly. This enables data sharing across the care ecosystem and supports compliance while providing a unified view of member health, helping payers drive faster, more informed decision-making. 

Using Low-Code to Deliver AI-Powered Care Insights and Boost Member Engagement 

One of the most exciting aspects of low-code is its ability to integrate AI seamlessly into applications. Payers can use low-code platforms to create tools that leverage AI-driven insights, enabling proactive and personalized member engagement. 

With low-code, a payer could develop a self-service portal where members receive AI-generated recommendations tailored to their health needs. These insights allow for proactive outreach, such as medication reminders or preventive care suggestions, improving member engagement and supporting better health outcomes. 

Scalable, Multi-Device Solutions for Members and Employees  

Today’s healthcare members and employees expect flexible, multi-device solutions. Low-code offers payers the ability to design scalable applications that deliver a consistent experience across devices—from desktop to mobile—without requiring extensive development resources. Rather than having a web, iOS, and an Android team, low-code enables a single team to generate device-native experiences with one solution. 

For example, A low-code-built member portal provides accessible, on-demand information, enabling members to view plan details, track claims, and manage personal health information seamlessly. Similarly, employee dashboards streamline operational processes by offering insights into service requests, claims status, and member inquiries, all in real-time. This flexibility supports both member satisfaction and operational efficiency. 

Streamlining Operational Efficiency through Automation  

Low-Code empowers payers to automate repetitive tasks, enhancing operational efficiency and reducing human error. Automated workflows streamline everything from compliance management to HR processes, freeing up resources for strategic initiatives. 

By automating document management, low-code helps payers maintain compliance more efficiently, ensuring that audits and quality checks happen without manual intervention. This reduces processing time and ensures that staff focus on high-value tasks, not repetitive manual labor. 

The Strategic Value of Low-Code for Payers 

Beyond immediate operational benefits, low-code brings lasting strategic value. By reducing dependence on traditional development and freeing up budgets, payers can reinvest in priority areas. Furthermore, with AI and automation capabilities integrated into low-code applications, payers are better equipped to support value-based care models, delivering proactive and personalized member services at scale. 

Low-code is not just a faster way to develop applications; it’s a strategic enabler that helps payers close the gap between traditional challenges and future-ready solutions. Embracing low-code allows payers to drive innovation, reduce costs, and enhance member satisfaction. As healthcare’s digital transformation accelerates, low-code provides the foundation for payers to lead with agility, efficiency, and a member-centered approach, ensuring they stay competitive in a rapidly evolving landscape. 

As health plans look to implement, optimize, or modernize their core administrative platforms and integrated systems, Generative AI presents a compelling opportunity to drive efficiency and elevate customer satisfaction. But what exactly is Generative AI, and how can payers harness its capabilities to enhance their operations? 

Once considered a cautious tech adopter, healthcare today is now at the forefront of a transformative tech boom. Both health systems and health plans are increasingly turning to advanced tools like automation, artificial intelligence, and machine learning to improve efficiencies, cut costs, and enhance the member experience. 

Among these innovations, Generative AI is emerging as a powerful solution for payers, offering the ability to reimagine business processes and deliver operational improvements. By automating manual, labor-intensive tasks and processing vast data sets, Generative AI reduces errors, speeds up workflows, and generates insights that improve decision-making. Whether you’re focused on optimizing claims processes, predicting and managing risk in member populations, or enhancing the overall member experience, Generative AI can help streamline operations, deliver faster and more accurate results, and lower costs. 

Here are three business areas where Generative AI can enhance efficiencies and deliver real value for your organization: 

Enhance Claims Adjudication with GenAI for Faster Processing and Reduced Costs

When a claim is submitted, it either processes through the rules engine based on its configuration or is flagged and pended due to a system edit such as a high dollar amount or other qualifying condition. Claims may also be pended for reasons such as being out-of-network or validation requirements around coordination of benefits. These rules determine whether the claim is automatically processed or routed into a work queue for further review. Generative AI can play a pivotal role by assessing whether there is sufficient medical necessity to continue to hold a pended claim and can even trigger correspondence to validate other payer coverage. 

Generative AI enhances the claims review process by pulling claims from work queues and applying an additional layer of analysis before manual intervention is necessary. This not only improves auto-adjudication rates and boosts throughput but also reduces the costs associated with manual intervention and claims that linger, potentially accumulating interest. 

By leveraging Generative AI, your organization can streamline the claims process through automatic verification of clinical eligibility and benefits, identification of anomalies like coding errors or fraud, and review of new claims against historical data to determine if additional medical management is needed. This approach enhances efficiency and accuracy in authorization decisions, ultimately decreasing the number of claims requiring manual review and minimizing penalties from delayed processing. 

Transform Customer Experience with GenAI for Faster Resolutions and Better Satisfaction

Generative AI can also transform the customer service experience for health plans by providing faster, more accurate responses to member inquiries. As a customer service agent working in a contact center, handling complex benefit questions can often be time-consuming. For example, when a member calls to ask about their remaining physical therapy (PT) visits, the traditional approach requires manually navigating the claims system to check their plan details. With Generative AI, this process becomes far more efficient. 

AI can instantly analyze the member’s claims history and benefit plan, quickly providing information such as how many PT visits have been used and how many remain. This allows agents to deliver insights to the member faster, enhancing the overall experience. Instead of spending time manually searching through records, agents are automatically fed relevant data, enabling them to be proactive rather than reactive. 

This improvement in efficiency leads to faster resolutions, better call throughput, and the potential to reduce call volume altogether. Members receive the information they need more quickly, leading to higher customer satisfaction (CSAT) scores and an overall positive experience with the health plan. In turn, this helps payers strengthen their member relationships and improve operational efficiency. 

Revolutionize Care Management and Population Health with GenAI

You can also greatly optimize your approach to care management and population health by leveraging Generative AI to implement proactive, data-driven strategies targeting chronic diseases like diabetes, COPD, asthma, and more. The primary goal in care management is to support sicker populations and effectively manage complex, chronic conditions. By integrating Generative AI with care management platforms and population health tools, health plans can monitor and address these conditions more efficiently. 

For example, in diabetes management, health plans often begin by establishing clear benchmarks for a target cohort, such as identifying members with both diabetes and obesity. Once these benchmarks are set, Generative AI can conduct disease surveillance by analyzing claims histories and population health data. This enables AI to identify patterns not only in members already diagnosed with diabetes but also in those at risk, allowing care managers to intervene proactively before issues escalate into more serious and costly conditions. 

Additionally, by examining claims histories and identifying trends in members’ health, Generative AI can uncover factors that contribute to complex diagnoses like diabetes combined with obesity. Armed with this information, health plans can implement preventative measures, such as outreach and coaching for pre-diabetic members. This proactive strategy can enhance health outcomes and reduce overall care costs by preventing the progression of chronic conditions. Moreover, health plans can track the impact of Generative AI in preventing these diagnoses among at-risk populations, ultimately improving population health outcomes. 

Getting Started: Using Generative AI to Create Actual Insights

These are just a few examples of the numerous business cases where Generative AI can significantly enhance your operations, elevate member satisfaction, and drive cost savings. The potential applications of Generative AI are vast, spanning from member outreach and onboarding to pricing and benefits design. As a health plan, your immediate challenge is determining where to begin your journey with Generative AI. 

To tackle this challenge effectively, it’s essential to focus on use cases that can deliver immediate, measurable benefits. Every health plan operates with its own unique, customized systems, so the first step is to identify areas where Generative AI can address high-cost, high-volume challenges. For instance, if your organization processes tens of thousands of claims annually in specific categories like coordination of benefits for member coverage, these manual interventions may be costing significant time and money. Such repetitive, labor-intensive processes are prime candidates for AI-driven optimization. 

Once you’ve identified the problem area, the next step is to partner with an expert team like Emids. We can help you explore how Generative AI can drive operational efficiency and improve your bottom line. From discovery to implementation and ongoing support, we’ll guide you through each phase to ensure the technology is seamlessly integrated and delivers lasting results. 

Contact Emids today to learn how Generative AI can streamline your payer operations and boost member satisfaction. 

Healthcare payers face mounting challenges as they strive to meet regulatory requirements, manage costs, and maintain quality service. Regulatory changes and the recalibration of Star ratings by CMS directly impact revenue streams and reputational standings. Meanwhile, healthcare costs continue to rise due to medical inflation and increased service demand, putting further strain on operational budgets. 

According to Gartner’s 2024 Hype Cycle for U.S. Healthcare Payers, 67% of payers rank margin improvement as a top three priority, and investments in AI and automation are expected to reduce industry costs by 15-20%. Operational inefficiencies—such as manual processing of claims, slow member service responses, and outdated systems—drive up Per Member Per Month (PMPM) costs and hinder margin improvement. 

To address these pressures, payers must move beyond short-term cost-cutting measures and adopt sustainable solutions. Automation offers a strategic approach to streamline operations, eliminate inefficiencies, and free up resources for innovation and member engagement. By automating manual processes, payers can enhance their operational efficiency and future-proof their businesses. 

Unlock Efficiency with Intelligent Automation in Healthcare 

Intelligent automation goes beyond simple task automation; it involves the integration of advanced technologies like artificial intelligence (AI) and machine learning (ML) into business processes. This approach enables healthcare payers to automate complex tasks, improve accuracy, and enhance decision-making. 

By eliminating manual interventions, payers can achieve faster response times, reduced errors, and improve compliance with regulatory standards. For example, intelligent automation can significantly increase claims auto-adjudication rates, reduce medical management costs, and enhance member and provider experiences. Here are some of the top ways that intelligent automation can optimize operations. 

Streamline Claims Processing with Automation  

Traditional claims processing is often labor-intensive and prone to errors, leading to delays and increased costs. Automation can streamline claims adjudication by automatically verifying eligibility, processing claims, and detecting potential fraud. This reduces the time and resources required for manual review, while increasing accuracy. 

Automate Member Enrollment and Enhance Member Service  

Automating member enrollment processes can simplify onboarding and enhance member experiences. Intelligent automation can also improve self-service capabilities, allowing members to access information and services quickly and easily. This leads to increased member satisfaction and reduced administrative costs. 

Provider and Network Management Automation 

Managing provider networks involves complex tasks such as credentialing, contract management, and network adequacy assessments. Automation can streamline these processes by automating data collection, verification, and analysis, ensuring compliance and improving provider relationships. 

Making Automation Intelligent for Healthcare Payers 

Implementing automation requires careful planning and strategic execution. Here are the essential steps healthcare payers need to take to successfully automate their operations: 

1. Assess Current Processes: Begin by conducting a comprehensive assessment of existing manual processes. Identify areas that are labor-intensive, error-prone, and time-consuming. This analysis will help prioritize automation initiatives and determine where automation can deliver the most significant impact. 
2. Define Automation Goals: Clearly define the goals and objectives of automation. Determine what specific outcomes you want to achieve, such as reducing costs, improving accuracy, or enhancing member experiences. Align these goals with your organization’s strategic priorities to ensure successful implementation. 
3. Select the Right Automation Tools: Choose automation tools and technologies that fit your organization’s needs and capabilities. Consider factors such as scalability, integration capabilities, and ease of use. Collaborate with technology partners and vendors to identify solutions that align with your automation strategy. 

Building Resiliency with Automation to Future-Proof Your Business 

Automation is not just about addressing current challenges, it’s about building resilience and preparing for the future. In an industry characterized by rapid changes and increasing complexity, healthcare payers need flexible and scalable solutions. Automation provides the agility required to adapt to changing regulations, emerging technologies, and evolving member expectations. 

By automating manual processes, payers can create a sustainable foundation for growth, innovation, and continuous improvement. Automation enables organizations to scale their operations efficiently, expand service offerings, and deliver high-quality care to members. It empowers payers to stay ahead of the competition and meet the demands of a dynamic healthcare environment. 

Partnering with Technology Providers for Successful Automation 

Partnering with experienced technology providers can significantly enhance the success of automation initiatives. Technology partners bring specialized expertise, industry insights, and proven methodologies to the table. They can guide healthcare payers through the entire automation life cycle, from strategy development to implementation and optimization. 

Collaborating with trusted partners allows payers to leverage cutting-edge technologies, access industry best practices, and accelerate their automation journeys. By tapping into the knowledge and resources of technology partners, payers can achieve faster results and realize the full potential of automation. 

In a project with a leading Blues Health Plan, our automation project led to 500,000+ hours over the last 3 years with 375+ automations, delivering a 3X ROI. 

Keep in mind that automation is just one powerful tool in the arsenal for optimizing payer operations. If you are interested in learning more about automation or discovering other opportunities for payers to achieve significant cost optimization within your operations, download our comprehensive free eBook. This resource offers insights and strategies tailored to help you navigate the complexities of cost management. Connect with us for personalized advice and support tailored to your specific needs.