Case Study

UST helped a health insurance association and its affiliated plans automate provider data submissions with HL7 FHIR compliance

An association of independent, locally operated health plans wanted to replace its cumbersome file-based provider data submission system with a real-time, automated process. UST implemented an AWS Cloud solution with a health level 7 (HL7) fast healthcare interoperability resources (FHIR) API, using the Smile CDR clinical data repository server. The solution improved provider experiences, increased operational efficiency, and positioned the association and its affiliated plans for growth.

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OUR CLIENT

This national health insurance association is a federation of more than 30 independent health insurance companies that collectively insure more than 100 million people in the US. The association and its affiliated plans provide insurance process management services and have operations in all 50 states, several US territories, and some additional countries. It also administers primary health insurance for US federal employees, retirees, and their families, providing comprehensive medical, prescription drug, and other benefits, like dental and vision.

THE CHALLENGE

Outdated data infrastructure and processes caused scalability and data integrity issues

The national health insurance association used an outdated file-based system for its provider data submission and consumption processes. This system wasn’t designed for real-time data exchange and followed a weekly or monthly data transfer schedule. The situation caused a range of issues, including scalability to keep pace with increasing provider data volumes, difficulty integrating new data sources, potential data errors, and delayed decision-making.

Extensive manual data manipulation

Providers submitted healthcare data to the insurance company in the FHIR JSON format. FHIR is an international standard API for exchanging electronic health records. Once the association received provider data, analysts had to convert each data set from the FHIR JSON format to a flattened, relational format for analysis. This complex, time-consuming conversion process required significant manual interventions and created risks that the resulting information may not comply with healthcare data governance standards.

Lacking sophisticated analytics capabilities

The existing system also couldn’t easily process complex data sets. Therefore, the association couldn’t fully leverage modern analytics to gain actionable insights to monitor provider performance and compliance, which are critical checkpoints to ensure high-quality healthcare. This situation also negatively impacted communication and collaboration between the association and affiliated plans and made it difficult for the association to launch initiatives to enhance provider engagement. Decisions were made with outdated information and the lag hindered operational responsiveness, preventing the association and its affiliated plans from adapting to changes in the healthcare industry.

These data processing inefficiencies also led to frequent service level agreement (SLA) breaches and jeopardized the association’s ability to meet critical timelines and commitments to stakeholders. The company was at risk of falling behind competitors who could manage provider data more effectively and needed a transformational data management solution with robust processing and analytics capabilities that ensured healthcare data compliance.

THE TRANSFORMATION

Scalable healthcare data lake makes FHIR provider data more accessible for downstream consumption and analysis

UST transformed the company's provider data submission and consumption processes by deploying a real-time, FHIR-based, automated data exchange solution with a centralized data lake in an AWS Cloud infrastructure.

A modern data lake

Our solution utilized the Smile CDR server, a clinical data repository for storing health records designed with the HL7 FHIR API standard, to process and validate provider data transfers, ensuring compliance with industry standards. The server was deployed on AWS Elastic Compute Cloud (EC2) because of its flexible, scalable nature and used a REST API to facilitate seamless data transmission. For data persistence, Amazon PostgreSQL RDS offered a reliable, secure database to store provider information. Apache Kafka provided efficient, real-time data streaming and integration while Amazon API Gateway and AWS Lambda handled incoming requests in the FHIR format efficiently.

To automatically convert data, AWS Glue, a serverless massive parallel processing platform combined with PySpark, transformed the multi-nested FHIR JSON-formatted data sets into flattened files. This conversion process made data easier to work with and prepared it to be integrated with other systems.

To enhance data integrity, UST developed additional business rule validations on top of the built-in FHIR validation rules, enabling the association and its affiliated plans to implement more stringent checkpoints as necessary to address specific business and market needs. This customization ensured only accurate, compliant data is processed and shared, reducing the likelihood of data transfer or manual manipulation errors.

The real-time data ingestion functionality enabled the company to generate tailored data outputs for processing by downstream systems, making it readily available for analysis as soon as it’s collected, addressing SLA adherence issues. The final data lake generated approximately 100 GB of organized data in various file formats.

Data access and consumption

To facilitate efficient, secure access to data, AWS Athena-based tables enabled direct querying of data stored in Amazon S3, allowing the company to perform daily analytics and reporting to gain insights without the need for extensive data movement. Users can access the prepared data using S3 pre-signed URLs, which are temporary links allowing users to access private Amazon S3 objects securely.

Meanwhile, Google Cloud’s Apigee Gateway was deployed to manage and expose APIs to providers, giving them a secure, reliable data access interface. This gateway allowed the insurance company to control access and monitor API usage, enhancing overall security and performance. Additionally, AWS’ Elastic Load Balancing service distributes network traffic to ensure optimal performance and availability.

The association now has a modern, efficient ecosystem for seamless data transfers, processing, and analysis. Combining a scalable data infrastructure, real-time ingestion, efficient automated transformation, and flexible sharing of democratized provider data enables company leaders and business users to make informed decisions with greater speed and accuracy—with peace of mind that data complies with industry standards. This digital transformation positions the company to meet the demands of a dynamic healthcare environment, achieve its provider engagement goals, and forge ahead with an innovative mindset.

THE IMPACT

Boosting operational efficiency and enabling real-time data analysis to drive informed business decisions

Upon completion of this healthcare data transformation engagement, the association achieved these significant business benefits:

A better provider experience—Individual health plans can submit accurate data from providers and third-party vendors seamlessly, thanks to the automated FHIR validations. This new process has eliminated manual interventions and rework.
Streamlined processes—The association can process and analyze large datasets much more efficiently, a task that used to overwhelm its legacy systems and IT staff.
Real-time, on-demand access to critical provider data—The immediate access to healthcare information, including demographics, quality metrics, and analytical insights, enables the association and its affiliated plans to monitor and manage provider performance more effectively and make more informed decisions.
Operational efficiencies—The new solution has replaced the weekly and monthly data transfer schedule with a real-time submission process, allowing the association and its affiliated plans to respond swiftly to changes and make timely decisions. The automated system also minimizes error risks associated with manual data entry and batch processing, enhancing data integrity.

We can help your company enhance data processing capabilities by streamlining and automating processes. Learn more here.

RESOURCES

https://www.ust.com/en/industries/healthcare/interoperability

https://www.ust.com/en/industries/healthcare/interoperability/data-pipeline

https://www.ust.com/en/insights/accelerating-healthcare-interoperability