Premise Health provides primary care services for large organizations, including self-insured employers, labor unions and health plans. It faced several challenges working with claims data.
THE PROBLEM
First, it wanted to provide clients with a greater level of data. It knew it was creating positive outcomes based on encouraging anecdotes, positive member testimonials and high customer satisfaction scores, but the organization wanted a meaningful way to quantify the impact.
Second, when members came to Premise Health for a primary care visit, Premise often did not know what their care journey looked like leading up to the visit. Knowing members’ recent healthcare experiences helps Premise providers ask the right questions to get them the appropriate care.
Similarly, Premise needed a reliable way to track its members after they left a clinic. Perhaps members came to Premise for a primary care visit and ended up in the hospital the next week. Preventing readmissions is a major driver of success in value-based care arrangements, and Premise needed that data.
Finally, the provider organization wanted to improve its ability to use data for customized marketing to better reach and engage members. By starting with data, it could understand which member segments might share similar experiences and which would allow Premise to tailor content to their unique needs.
“In short, we could provide care to members who actively engaged with our services, but we knew there was more we could do if we had more comprehensive insights into the broader needs of our clients’ populations,” said Wes Whitaker, associate vice president of growth strategy at Premise Health.
PROPOSAL
Premise Health was looking for a vendor that offered both software development expertise and data ingestion services.
“First, we required capabilities for data cleansing, file standardization and data enhancements, such as procedure and diagnosis groupers, risk scores and care gap assessments,” Whitaker explained. “This was essential to ensure data accuracy and usability for analysis.
“Additionally, our diverse user base meant we needed a system that catered to different levels of technical expertise,” he continued. “Non-technical users needed an easy-to-use interface to consume information efficiently, while our data analysts preferred to interact directly with raw data tables and generate custom queries.”
Second, it was crucial to work with a vendor that had extensive experience with large payers and third-party administrators, Whitaker added.
“This expertise was vital in negotiating data-sharing agreements and aligning on file specifications, thus filling our gaps and ensuring smooth data integration,” he said. “An added benefit of scale would be the ability to benchmark across tens of millions of lives covered by commercial health plans.
“Finally, we needed a data extract system that allowed us to ingest information into our own systems seamlessly,” he continued. “This would enable us to integrate data within our front-end and clinical workflow applications, ensuring data was readily available for analysis and actionable insights.”
Premise Health selected vendor Cedar Gate Technologies, which it believed could help it bridge the gaps in its data capabilities and enhance its ability to deliver high-quality, data-driven healthcare services.
MEETING THE CHALLENGE
After implementing the new technology, Premise Health had to ask its clients to share their members’ health data with it. Clients initially shared data in a trickle, with only a handful signing up in the first year. Most of those clients wanted Premise merely to prove the ROI of the services on their health plan expenses.
“As our capabilities with the data grew, we were able to drive more impact with those early client adopters,” Whitaker noted. “Those successes led to case studies, which we shared with other clients considering sharing their data. The platform grew quickly from there, and we now have about 40 clients enrolled, representing more than 300,000 member lives.
“As the number of claims-sharing clients grew, we also started investing in better methods to work with the data,” he continued. “At this point, we needed to start taking data extracts and integrating them into other data systems. These include our Epic EHR, SQL environment and Mesh data warehouse, powered by Databricks and Microsoft Azure cloud services.”
As use cases expanded, Premise Health also began opening access to additional users, including doctors, nurses, marketers and operators – sharing PHI only on an as-needed basis, per HIPAA guidelines. According to industry research and validated by Premise internal studies, members often withhold pertinent information from providers to the detriment of their health.
“My team of data analysts and data scientists worked with clinicians and operators to decide what claims data elements would be most impactful at the point of care,” Whitaker said. “For this, we landed on nearly 90 discrete data points we pulled out and made available to care managers at the point of care.
“We chose a subset of the most impactful measures – for example, number of ER visits in the past 12 months – to show on the main display of the patient record in the EHR for doctors to see as they interact with members,” he continued. “Now, providers are actively using this information to enhance the care they provide to members. They can ask smarter questions and get to the root causes of issues faster.”
Additionally, Premise is using data to power tailored member outreach. For example, it may use data to identify and reach out to members in the population who are not engaging with a primary care provider. Alternatively, it may promote its primary care services to members with certain impactable conditions, such as diabetes or hypertension.
“By working with a secure system, we can develop and test tailored messaging to find the one that appeals to members and encourages them to focus on their health, while maintaining the highest standards for data security and privacy,” Whitaker said.
“Finally, by improving our ability to leverage claims data, we have significantly enhanced our reporting capabilities,” he continued. “This comprehensive data allows us to generate detailed insights into healthcare utilization patterns and costs. Clients gain a clearer understanding of their population’s health dynamics, enabling them to make informed decisions on care strategies and resource allocation.”
With the ability to track metrics such as ER visit frequency, chronic condition management and preventive care adherence, Premise empowers clients to identify areas for improvement and implement targeted interventions. This data-driven approach not only improves care quality but also fosters cost efficiency and better health outcomes for the populations served, he added.
RESULTS
Three success metrics stand out – first is the growth in demand from clients for data-driven healthcare services, second is the ability to measure member attribution to Premise Health thus ensuring interventions target the right individuals, and third is significant cost savings from identifying and acting on key healthcare utilization patterns ultimately leading to improved care management and financial efficiency, Whitaker stated.
“We now have claims data on more than 300,000 lives in the system,” he reported. “This monumental task involved the meticulous extraction, transformation and loading of vast amounts of data. Our data management technology standardizes and cleanses the data, making it accessible and usable for deeper insights. This foundational step is crucial in identifying patterns, trends and anomalies within our population.
“With the claims data loaded into the system, we are now able to measure how many members use Premise Health for the majority of their primary care,” he continued. “We call this ‘claims-based attribution,’ to distinguish it from ‘member-designated attribution.'”
In 2023, Premise attributed 58% of engaged members in claims, or 17% of overall eligible members. In other words, nearly six out of 10 members who set foot in a Premise clinic used Premise for the majority of their primary care. By leveraging relatively complicated algorithms, the technology enabled Premise to accurately attribute members to Premise services and care programs.
“This precise attribution ensures we measure outcomes for the right members,” Whitaker explained. “The technology’s ability to match and align member data across various sources was key to achieving this level of accuracy.
“Finally, for those members attributed to Premise, we have proven savings of $2,434 per member for primary care and more than $10,693 per high-risk member in our care management program,” he reported. “Claims data analysis technology allowed us to scrutinize healthcare utilization patterns and identify cost-saving opportunities.”
By tracking metrics such as emergency room visits, hospital admissions and chronic condition care gaps, Premise Health developed targeted strategies to reduce unnecessary expenses. The actionable insights derived from the data empowered care managers to intervene early, provide appropriate care, and ultimately drive down costs for both primary care and high-risk populations.
ADVICE FOR OTHERS
“When implementing any data integration or healthcare analytics technology, it is vital to determine your precise data needs initially, but also remain flexible,” Whitaker advised. “As you delve deeper into data analysis, you will inevitably uncover new and increasingly valuable use cases. This adaptability will allow you to maximize the potential of your data assets.
“Additionally, it is essential to thoroughly understand the workflow tools your providers use and evaluate the integration capabilities of your systems,” he continued. “Seamless integration ensures that data flows efficiently across various platforms, enhancing the overall effectiveness of your technology. We learned early on that our providers needed a way to view information within the EHR, without requiring ‘swivel-chairing’ into other applications.”
Be prepared to advocate for proper data ownership and understand data needs, he added. Carriers may assert control over the data if one does not proactively establish the employers’ rights. In data negotiations with payers, identify the specific data fields necessary for your operations, he said.
“For instance, if you are engaging in care navigation, provider NPIs will be crucial,” he asserted. “Conversely, if you are focused on managing total cost of care, financial data will be indispensable, while NPIs may be less critical. This will help you understand which fields are must-haves and which are nice-to-haves.
“In healthcare, data security and privacy are critical,” he added. “Understanding HIPAA requirements is important. For example, at Premise Health, we are typically considered a provider-type covered entity in the eyes of HIPAA, which means we are entitled to the PHI of our own patients.”
To make the shift toward performing population health services for clients, Premise Health needed new legal paperwork to convert from covered entity to business associate. In this case, the client is a plan-type covered entity. This was new legal territory for Premise, and it had to become more intimately familiar with the regulatory requirements of being a business associate versus a covered entity.
“The successful adoption of healthcare analytics technology hinges on a clear understanding of your data requirements, a flexible approach to discovering new applications, robust integration with provider workflows and assertive data ownership practices,” Whitaker concluded. “By adhering to these principles, you can unlock significant value and drive meaningful improvements in care quality and cost efficiency.”
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