Our client, one of the largest publicly traded hospital networks in the United States, faced operational challenges in managing their emergency room (ER) operations, including fragmented data systems, difficulties in promptly identifying patients, and inefficiencies during patient transitions from ER to inpatient care. These challenges negatively impacted decision-making capabilities, slowed operational workflows, and ultimately affected patient care quality and resource allocation.
Internally, the hospital sought to modernize its systems to better leverage data-driven insights, aiming to improve real-time patient management and operational efficiency. Recognizing these specific needs, they partnered with Emids to develop a targeted solution integrating advanced AI and cloud technologies.
In collaboration with Google Cloud and UnityAI, Emids developed a proof of concept (PoC) specifically designed to address emergency room management needs. The solution focused on enhancing patient identification accuracy and improving the operational transitions between ER and inpatient care, powered by generative AI (GenAI) to quickly and accurately process patient data.
To provide actionable, real-time insights, the solution leveraged Google’s Cloud Health Data Engine (HDE), incorporating pre-General Availability (GA) GCP features for advanced analytics and improved system responsiveness. A Fast Healthcare Interoperability Resources (FHIR) store was also integrated with Google’s BigQuery, facilitating seamless data interoperability and supporting robust analytics capabilities.
Additionally, a secure real-time data streaming pipeline was constructed using GCP tools such as PubSub and DataFlow, allowing for efficient data processing and transfer. Lastly, an HL7 MLLP adaptor was implemented to ensure effective integration of the new AI-enabled system with existing hospital technologies.
Following the solution’s deployment, the hospital’s emergency room operations saw substantial improvements. Healthcare providers gained immediate access to accurate, AI-driven insights, significantly enhancing the speed and accuracy of patient identification and ER management. This directly supported smoother patient transitions from the ER to inpatient care.
Additionally, increased data transparency allowed healthcare professionals and hospital administrators to make more informed, timely decisions. This led to measurable improvements in patient outcomes and operational performance.
Operationally, the hospital experienced improved efficiency, demonstrated by streamlined workflows and optimized resource allocation. Reduced ER wait times and better management of care pathways resulted in tangible improvement in both patient satisfaction and clinical outcomes.
This initiative provided a robust foundation to scale future AI-driven initiatives, ensuring the hospital remains equipped to adapt effectively to future healthcare technology advancements.
A prominent healthcare organization in the USA, managing diverse business lines including retail, pharmacy, health insurance, managed healthcare, and population health management, sought to modernize its data ecosystem. The goal was to transition from on-prem systems to the Google Cloud Platform (GCP) to leverage the full potential of their data, enhance scalability, and streamline operations. However, the cloud migration posed significant challenges, such as handling large datasets, ensuring data integrity, and maintaining uninterrupted business operations during the transition.
Emids executed a well-orchestrated, multi-phase migration plan. The journey began with meticulous planning, involving comprehensive collection of details about the client’s workloads, schemas, users, and source systems. This exhaustive analysis was crucial in crafting a tailored migration strategy for a smooth transition.
Migration Planning: Detailed information on workloads, schemas, users, and source systems was collected, forming the basis for a customized migration strategy.
Schema Design and Data Rationalization: The target schema was designed and data sets were rationalized to optimize performance and scalability on GCP.
Data Migration: Data was migrated from Hadoop to BigQuery, encompassing both one-time data transfers and the setup of incremental workload processes. This included data replication, transformation, and ingestion to ensure efficient and accurate data movement.
Workload and Application Migration: The migration of workloads and applications was managed by converting code from HQL to BigQuery SQL and adapting scripts using Python and PySpark. Airflow was utilized for job scheduling and monitoring to ensure seamless and continuous operations.
Application Management and Validation: Robust application management tools were set up, including cost monitoring with Apptio and application monitoring with New Relic. Extensive data validation, end-to-end testing, and a production parallel run were conducted to ensure system reliability.
Decommissioning and User Adoption: The Hadoop environment was decommissioned, on-prem data removed, scheduled jobs terminated, and end-user adoption of the new system facilitated.
YOUR PARTNER IN CLOUD TRANSFORMATION
Expert-led cloud migration services designed to optimize costs, enhance innovation, and mitigate risks for healthcare organizations.
Discover our Cloud Migration SolutionsThe project delivered transformative results for the healthcare organization:
Successful Migration: The healthcare business unit’s data was seamlessly migrated to GCP, establishing a new semantic layer that improved data accessibility and usability.
Enhanced Data Processing: The new cloud infrastructure provided enhanced data processing capabilities, supporting a broader range of use cases and enabling rapid scaling to meet business demands.
Operational Excellence and Cost Management: With modern tools and optimized processes, the organization experienced improved operational efficiency, reduced costs, and better data management. The cloud environment facilitated advanced analytics and business insights, driving growth and innovation.
A non-profit Health Maintenance Organization (HMO), wanted to modernize its IT ecosystem. This included a crucial migration to the cloud, constructing next-generation data platforms, and upskilling their workforce to support their growth trajectory. They were also driven by the need to comply with the Centers for Medicare & Medicaid Services (CMS) Interoperability and Patient Access final rule, which mandates that patients have access to their health information through standardized APIs like HL7 FHIR. The HMO faced significant challenges in ensuring seamless data migration while adhering to stringent compliance requirements and modernizing their infrastructure.
Emids was brought in to navigate these complex requirements and provide a robust solution. We began by developing a comprehensive cloud strategy that encompassed a detailed data platform strategy on AWS.
Our approach was multifaceted:
Leverage CMS Interoperability Program: Using the CMS Interoperability program as a minimum viable product, we ensured that our solution met immediate compliance needs while setting the foundation for future expansion.
Data Mapping and Architecture: We meticulously mapped data from the HMO’s source systems to the FHIR store, ensuring accuracy and completeness. Our team designed an architecture pattern tailored to the client’s needs, establishing AWS infrastructure and CI/CD pipelines for streamlined operations.
Data Migration: Utilizing tools like Sqoop, we migrated data from on-prem databases to AWS S3 buckets. We then implemented a FHIR server, converting data into the FHIR format and loading historical data into an MS SQL Server in FHIR format.
Data Pipelines and Authentication: We created data pipelines using AWS Glue, Python, and Lambda to handle incremental data loads from new systems to the cloud. Additionally, we enabled member authentication and authorization using Okta, ensuring secure access to data.
YOUR PARTNER IN CLOUD TRANSFORMATION
Expert-led cloud migration services designed to optimize costs, enhance innovation, and mitigate risks for healthcare organizations.
Discover our Cloud Migration SolutionsThe project was executed with precision, leading to several significant outcomes:
Architectural Excellence: We delivered a robust cloud architecture pattern that provided a scalable and efficient framework for the HMO’s operations.
Enhanced Compliance and Interoperability: The HMO achieved full compliance with CMS mandates, providing patients with seamless access to their health information via FHIR APIs. This not only met regulatory requirements but also enhanced internal data exchange processes.
Operational Efficiency: Data on the cloud facilitated advanced analytics, improving decision-making and operational efficiency. The new system supported rapid data access and processing, empowering the HMO to offer better services to its members.
Leveraging the AWS Cloud platform to help leading medical organization accelerate growth and cut operational costs costs
The Emids client is a leading national medical group with more than $5 billion in revenue. The group provides physician-led services, ambulatory surgery center management, post-acute care and medical transportation among other services. The client encounters more than 30 million patients annually across the U.S.
But the client faced several data challenges impeding its long-term growth.
The group’s clinical data exchange had more than 1,100 point-to-point connections to support data acquisition and had more than 600 sites reporting Medicare-Access-and-CHIP-Reauthorization-Act/Merit-based-Incentive-Payment-System data via a paper-based abstraction process. Additionally, the client was losing revenue from delayed billing caused by incomplete data as well as minimal to no internal checkpoints on data feeds.
That’s where Emids was brought on to serve as a strategic data partner.
Our team adopted a consulting-led approach to identify key stakeholders, conduct interviews, understand the state of data acquisition & ingestion, clinical flows, technology and integration tools. We carried out a detailed assessment of Health Information Exchanges (HIE), Epic App Orchid, Cerner Hub and other data sources as identified by the client.
We defined a new strategy for real-time data acquisition and developed a data-acquisition roadmap illustrating data feeds. We recommended a structured format of electronic health records data for acquisition. This included using Epic APIs and the Epic App Orchard and a Fast Healthcare Interoperability Resources (FHIR) based implementation strategy, HL7 for Cerner HUB and CCD-based strategy for HIE’s.
Emids Data Engineering
Leverage your data to unlock insights and create solutions that lead to transformative outcomes
Discover our CapabilitiesThe solution was built on the AWS cloud platform leveraging S3 for storage, RedShift for data warehousing, Athena for interactive analytics and a host of other AWS services like Lamda, Glue, and Kinesis data streams.
Emids became the client’s strategic data partner for more than two years, resulting in scalable FHIR-based solutions hosted on the AWS platform. This reduced effort and increased savings on operational costs.
The client is a global leader in coding, classification, grouping and performance management software and consulting services for 7,500 hospitals in more than 20 countries worldwide. The company provides intelligent software, data analytics and strategic expertise to help providers as well as government and commercial payers simplify health information and payment, analyze risk and manage population health as they shift from volume- to value-based care. Their innovative algorithms, software and services have saved customers millions of dollars and improved clinical performance and quality of care for thousands of healthcare organizations across the globe.
The client was working on several enterprise projects, but needed help to push them forward. One project involved building an internal natural language processing (NLP) tool to improve the automated capture of critical clinical data needed to optimize coding for billing and diagnosis purposes. Another project evolved from an idea the client had to use terabytes of data across their customer base to create a population health management platform that analyzed information on patient populations and financial performance, with the goal of providing insights to help providers improve care and reduce costs.
With their current staff busy maintaining and enhancing their existing product portfolio, the company lacked the development bandwidth to turn these ideas into realities. They needed a global partner with deep healthcare IT knowledge and Agile training that could provide rapid development resources and experience with deploying technologies in cloud-based environments. Product development for the population health platform was highly complex. Not only did the product need to be housed within the client’s next-generation platform, but the number of internal and external health information systems involved in exchanging the data posed significant integration and interoperability challenges.
The client turned to emids for help modernizing their platform and developing frameworks for these new technologies. We formed scrum teams across three cities—Nashville, Salt Lake City and Silver Spring, Maryland—to augment their internal teams, ramping up production within eight weeks.
Initially, we provided development support for the population health platform, with two self-contained teams working on user experience-based elements of the new product. But we soon began proactively helping the client’s internal teams with back-end integration so they could keep pace with completion of the front-end elements.
The client was using a third-party vendor to provide data analytics and algorithms for the product. They needed to exchange data with the vendor securely through the cloud, but lacked expertise on how to make this happen. We were able to quickly grasp and resolve these integration issues, eventually taking the lead on these more complicated elements. We worked directly with the vendor to determine how the integration and encryption should occur, experimenting with different solutions before settling on one and establishing a proof of concept.
We created a cloud environment through an 1,800-plus server farm on Amazon Web Services and established the secure transfer of the data, enabling the information to flow in an efficient, meaningful way, encrypt at the appropriate time and return analytics quickly.
Technologies Used
While our work with both of these engagements are ongoing, we have helped the client meet their initial deadlines for bringing these projects to fruition and transforming them from concepts into viable technologies ready for the first phase of internal testing. Our team of healthcare experience technologists, which included 50 people at peak, jumped into both projects quickly and have added value uniformly and quickly.
We understood what needed to be built to execute the projects and assembled teams with deep healthcare knowledge to help drive their development. With the population health project, we worked closely with the client to flesh out the engineering for the product and set its direction. We helped anticipate and resolve issues before they became problems, even taking the initiative to collaborate with the third-party analytics provider that came on board to keep the engagement proceeding smoothly. The client still raves about how the initial prototype of the product matched their vision and met their needs right out of the gate.
We have continued to deliver new functionality for these projects, overseeing production releases every two weeks. The NLP tool we are developing for the client has enabled them to quickly explore the impact of different scenarios for coding by changing the rules for the automatic capture of clinical data. This process used to take days, but we have helped the client shorten the turnaround to few hours.
