Hello everyone. My name is Simon. Welcome to conference 42, goal line 2025. Today we'll be discussing about the topic transforming payer operations with realtime data integration. How. Healthcare payer landscape is undergoing the performed transformation and how that can be used to transform payer operations with realtime data integration. So in today's world, the healthcare payer landscape is undergoing a performed transformation through the integration of real time data processing. And middleware solutions. So these solutions are dramatically improving the claims processing, eligibility verification, and statistics, while ensuring the regulatory complaints. So organizations which are implementing these technologies have seen remarkable results. Like example, 40% faster claim processing, 60% fewer denials and reduction in integration development time with, 50%. And also the data accuracy. Maintaining the data accuracy in today's world is a big challenge for every industry. So 99.9% data accuracy can be achieved using this transformation. Advanced solutions like cloud-based message brokers can process over 10,000 messages per second, enabling faster claim resolution and improved fraud deduction. So let's get into the challenges of payer operations. Current challenges in payer operations, like one is manual processing bottlenecks. Traditional claim processing relies on manual intervention, creating bottlenecks that slow down the operation and increase administrative cost, which is like studies shows that manual crime processing can take up to 30 days to complete the processing. and the second challenge, what we have today is data S and fragmentation healthcare data exist in disparate systems, making it difficult to access complete page and information. This fragmentation leads to eligibility errors and delayed claim resolutions. And the third challenge that what we see is regulatory compliance burden. So payers face increasingly complex. Compliance requirements like hipaa, a CA, and interoperability mandates without integrated systems. Maintaining the compliance becomes resource intensity and error problem. So these are the challenges like, current payer industries, healthcare industry, and bay operations are undergoing. So let's get into your topic. Like what is the power of realtime data integration? How can it bring down or bring value to the processing claims processing like 40% of faster claims processing can be achieved using realtime data integration, accelerate claim processing, and reducing resolution times and improving your payer efficiency. and also. reduce claim denials, so which reduces 60% claim denials using the enhanced data security and realtime verification. Significantly decrease the costly claim, rejections and rework, and it also increases 50% integration efficiency. Middleware solutions like Del Boomi cut the development time in half, which is 50% as we discussed. Speeding implementation and return of investment. And the last but not least, it's very important, which is data integrity. 99.9% data integrity can be achieved using modern integration platform. Ensure near perfect data accuracy, minimizing the error and comprehensive risk. So these are the, things that we can achieve using the real time data integration. This is the power of, real time data integration in the middleware sector. So when it comes to how it can be a backbone of modern payer system, so today business applications like claim processing engines, eligibility verification system. And interactive member quotas. And when it comes to a p, a management layer, so second, restful a PA services, secure restful services, which can be achieved using and comprehensive, a PA governance. And the third one is like middleware integration layer, real time data transformation, intelligent message routing, complex data, workflow orchestration. So this is going to be a pivotal role that is going to play in the middle middleware integration layer and data storage and processing, right? So distributed databases, cloud-based data warehouses and predictive analysis and engines, infrastructure that is going to be elastic cloud resources, legacy on-premises system, and scalable hybrid architecture. All these things combined can be a backbone of modern payer system. Enterprise middleware system solution function as a critical and connectivity issue between connectivity issue between the heterogeneous systems in the healthcare ecosystem. These integrations right platforms enable seamless bidirectional and data flow while enforcing the robust. Security protocol and regulatory compliance requirements. So this all, not only doing the seamless bidirectional data flow, but also, protects the security protocol, regulatory compliance requirements, which is very important for the payer industry by creating a unified architecture, a middleware, bridges legacy systems with a cutting edge applications providing the technical foundation necessary. For realtime healthcare operating and, innovations. And, when it comes to revolutionizing the claim processing, this is a very good concept that, I want to bring. So how the claims processing can be happened while from the submission to the status communication. So one is like submission status when the claims are submitted electronically, immediately validated against the member data. And also provider contracts. How the provider's contracts are established. Real time data integration allows the instant format verification and initial error detection format Verification is very important in the payer industry, so they maintain the different formats for each sector. So like that, so payer industry has its own format. That format verification is very important, which is going to. have the initial error detection also, and adjudication, right? When you, when it comes to the second part is adjudication. Middleware ate the complex adjudication process, applying business rules, benefit calculations, provider contract terms in real time, reducing the paper, reducing the processing time in from days to minutes. and the third payment determination. Integrated system calculate accurate payment amounts based on the realtime contract and benefit data drastically, dramatically reducing the overpayments and underpayments status. Communication, providing the provide, providing the members and providers, in, with the status. Communication is going to help a lot. Like providers and members receive instant status updates through the integrated protocols and messaging systems, improving satisfaction and reducing the inquiry volume, real time eligibility verification, which is very important and very useful for all the members and providers. Member data access, seamless verification of coverage status, whether the particular member is eligible. Can be done instantaneously. Benefit validation. Immediate service authorization, provider confirmation. Instantaneous results. Delivery. Financial responsibility, precise cost Sharing determination that can happen. Using this real time eligibility verification. Revolutionizes both provider workflow and the member experiences by eliminating uncertainty, reducing administrative burden, and preventing the delays. When integrated directly with the practice management system, it enables instant benefit verification during the appointment scheduling at the point of service sustainability, reducing the climate, and also optimizing the entire revenue cycle management process. So it is going to help in all aspects like service eligibility, revenue management process. And also state of the art verification system, process eligibility request in millisecond instead of the minutes or hours. So seamlessly handling the event, even most of the volume, extreme volumes are going to happen during the open enrollment. So at that point of time, also, the system will not be degraded and in the perform in the aspect of performance or accuracy. When it comes to event driven architecture for claim statistics, so checking a claim status is a very important aspect of, real time. This thing, real time publishing and notification. When a claim status changes, the system instantaneously publish an event that triggers notification and updates across all the connected systems, reducing the eligibility check processing time from 1.5 hours to. Just 0.3 seconds. Similarly, message brokers and scaling advanced message broker process over 10,000 messages per second during the peak periods will help maintaining the system responsiveness and data integrity, handling the claim status updates in just 0.5 seconds versus three to four hours traditionally prior authorization efficiency. Event driven systems reduce preauthorization process time generally takes 48 hours from to just five seconds. Enabling immediate clinical decision and which supports dramatically improving provider workflow as well as member it, it helps members to get the immediate clinical decision and also accelerated claims adjudication. The complete claim adjudication process is transformed from a. 72 hour way to just 30 seconds. Maintaining the data integrity while enabling the realtime updates for all stakeholders is not easy thing that can be achieved using the event driven architecture claim status, checks. So finally, event driven architecture enables realtime. Claim statistics tracking through a system of publishers, subscribers, and message broker dramatically reducing the lag between the status change and stakeholder notification. So cloud-based message brokers enabling scalability, so scalability, security integration, seamless integration are the wonderful features that can be, achieved using this concept. So cloud-based message brokers automatically scale to handle very transaction volumes. So from routine daily processing to month end surges, this eliminates the need for over provisioning on-premises infrastructure, while ensuring the consistent performance as well and security. So enhanced security. Modern cloud brokers implement advanced encryption, access control compliance features. That meet or exceed HIPA requirement. This feature protects sensitive patient data through the messaging process from origin to the destination. So security is a matter. So seamless integration, prebuilt connectors, and standardized APAs enable rapid integration with both legacy systems and modern application. This reduces implementation from months to weeks. Which is very important. Drastic red use of the time processing from months to week while maintaining the data integrity across the platform. Okay. AI and machine learning. The next front are how a and machine learning can be useful, using this middleware technologies, real time data so we can predict the claim processing. Our AI algorithms analyze the historical claims data, predict outcomes, identify potential issues before they occur, and suggest optimal processing path. How, which way, which path that it has to take? This proactive approach reduces the manual view requirements up to by 30%. So we are going to, with the predictive claim processing, the manual effort is going to be reduced by 35%, 30% intelligent fraud detection. Machine learning models continuously analyzes the claims patent to identify the anomalies and potential fraud in real time. So machine learning can eliminate the frauds in the real time scenarios. This system can detect the sophisticated fraud schemes that could in be invisible to system. We can avoid the fraud detect, fraud transactions, fraud claims. And when it comes to natural language processing, NLP extracts meaningful data from unstructured clinical notes and documentation, enhancing the claim adjudication process with relevant clinical content that would otherwise require a manual review. So here also, it is going to save the manual time. And autonomous resolution. Advanced AI systems can autonomously resolve routine claim issues without human intervention, allowing staff to focus on the complex cases that require clinical expertise and also advertisement. So edge computing. So the most training technology, which is the edge computing processing at the point of care. So distributed processing reduces the bandwidth requirements. Continuous operation, real time clinical integration. So how edge computing is going to help us. So dis distributed processing edge computing moves data processing closer to the source of data generation, such as a hospital's clinics. The distributed approach reduces the latency by processing the eligibility at simple eligibility and simple claims directly at the healthcare facility. Before even submission, or transforming to the transmission, to the central systems so we don't have to process the data to the transmission, to the central system to identify whether this particular processing is really required. The central system. So this distributed processing can take care of that at the source level itself by saving so much. Time and processing, eligibility and latency also. So reduced bandwidth requirement. So it is going to save the, bandwidth, which is in process, like by processing the filtering and locally data. Locally it's competing, reduces the amount of information that must be transmitted to the central system. These particularly valuables for rural and are undeserved areas. So where the limited connectivity is there. There, the reduced bandwidth requirement is going to help a lot. Continuous Operation Edge systems can continue to function during the network. Outages are central system maintenance, storing the transactions locally until the connectivity is stored. This ensures that patient care continues uninterrupted, even though even during the technical disruptions also. Real time clinical integration edge processing enables real time integration between clinical system and payer system, supporting value based care models that require immediate feedback on care decision and their financial implications. So let's see how the roadmap looks like, for a future outlook. Short term actions like zero to six months. Access to current integration architecture and identify local gaps. Implement middleware connectors for high volume transactions. Deploy cloud-based message brokers for eligibility verification. So train the staff on new real time capabilities and workflows. So this is the short term goal, like from zero to six months how we can access the integration. Architecture and, critical gaps and how we can, use the middleware connector for high volume transactions. How can we deploy the cloud-based message brokers for eligibility verification? So whether the person is eligible at or not instantaneously get the eligibility verification when it comes to medium term goals, which is six to 18 months. Transition to fully event driven architecture from claim processing. Implement AI assisted claims adjudication for routine claims. Develop, provide provider facing APAs for direct system integrations. So provider facing integrations are going to be very helpful and implementing the AI assisted claim Education also at the facility is going to be very helpful and it's going to give the instantaneous decisions. And establish the edge computing pilots at major provider partners, which is going to save, longer, processing time for instantaneous decisions. So long term vision, 18 placements achieve near instantaneous claim processing. For standard claims, instantaneous claim processing can be achieved. In the long term vision, implement predictive analytics for proactive intervention, and this can be achieved using the edge computing implementation of predictive analysis for proactive intervention, deploy auto autonomous exception handling for common issues, transition to blockchain for select high value transactions. So these are the long-term visions that what we are going to achieve. Using the payer transformation healthcare, using the realtime data integration. Thank you. Thanks, Sue. Thank you for your.