Laying the proper foundation for analytic capabilities requires quality data, which directly impacts the success of value-based contracts for Accountable Care Organizations like Summit Health. Dr. Jamie Reedy, Chief of Population Health, and Dr. Ashish Parikh, Chief Quality Officer, shares Summit's foundation for ACO analytics, ensuring data quality, and how data can drive ROIs.
About a decade ago, Summit Medical Group–now known as Summit Health after a recent merger– learned that it offers care with better outcomes and lower costs for Medicare patients. This is because Summit is a multi-specialty outpatient structure, featuring over 80 specialties and comprehensive, coordinated care. Understanding this, the organization began its ACO (Accountable Care Organization) journey.
As the group progressively added value-based agreements, they controlled the number of contracts and the overall level of risk. According to Parikh, as the number of patients in the ACO increased, the group added to its physician team and invested in its population health management infrastructure.
The key to successful ACOs or any value-based care is accessibility to lots of data. When Summit started assessing its analytics options and potential vendor partners, it first needed specific foundational capabilities.
The first of these capabilities is creating an expansive dataset, which allows for integrating disparate data sets. The organization grew in contracts and population, transitioning beyond limited clinical data within its EHR. They began incorporating medical and pharmacy claims data from health plan partners and clinical alerts of encounters beyond the organization's walls.
Another foundation is creating data-driven workflows, Reedy explained. Use case data was a priority for the clinics in their workflow journey. The group invested in FTEs to support coding, quality, and patient management.
The third component is ensuring analytics teams have direct access to normalized sets. This allows teams to calculate the performance in critical areas of value-based success. Summit’s care teams can better use data to inform workflows by developing enhanced and predictive analytics to grow in sophistication.
Data comes from various sources across healthcare ecosystems, Reedy explained. In the beginning, Summit integrated common data sources like health plan eligibility and claims data, clinical EHR and practice management data, and information from core facility partners.
The organization continues its data journey by progressing deeper into its risk journey, where adding risk adjustment data and coding gaps are critical. Additionally, pursuing telehealth, remote physiologic monitoring, and socio-demographic data is necessary for coordinated and comprehensive virtual patient care.
The data sources chosen for integration are driven by the organization's business news and prioritized by considering technical challenges associated with accessing its data.
Obtaining medical and pharmacy claims data from health plan partners is critical for mutual success. Complete claims data presents full visibility, Reedy explained. It aids with managing financial risks in ACOs, as they require insights on patients, patterns of care, and utilization beyond organizations.
Pharmacy claims data, for example, helps calculate providers and generic prescribing rates, so providers are held accountable within Summit's incentive program. Other types of claims data assess where patients receive specific care and educate physicians about cost differentials.
Organizations need quality data to build out their analytics infrastructure, which is why Reedy recommends incorporating quality into the overall strategy of data integration.
Reedy further explained how organizations must consider the consequences of data quality. If care teams find flaws and are not confident with the data, they disengage with analytics. Care teams will further disengage if the data is inaccurate or efficient for its intended purpose.
Summit desires strong data engagement, which is why the organization is hyper-focused on building data-driven workflows. Building a strong data quality review process ensures all integrated data sets are dependable.
According to Reedy, several key signs bring end-user confidence in data quality–correctness, completeness, integrity, validity, and data relevance.
Providing education for providers regarding the data sources and how they are validated is critical to successful data use. While variances are possible, the key is minimizing them upfront through strong data quality processes.
While claims data is integral to managing financial risks and outcomes, it is necessary to assess the common data issues with claims.
Privacy regulations require sensitive diagnoses and procedures to be masked or hidden and result in knowledge gaps about longitudinal care. Reedy explained that some health plans offer selective or exclusion criteria, which leave pharmacy claims files useless for clinical teams.
Another challenge is how health plans change file formats or alter data elements. These changes are frequent and result in failure of automation and delays in data access.
With these issues in mind, Reedy recommends that organizations develop proactive strategies for managing claims data quality. Summit regularly educates the health plans it partners with about how data guides members.
"When the health plan understands the importance of the data to the care of their patients, there's so much better cooperation with us," she said.
To reduce complications with data, the organization builds language into its contracts to require the timely and complete provision of claims-based data feeds.
Summit has three areas of priority for driving value from data. The first of these is for data to inform daily workflows–immediately impacting patient outcomes.
Another area is using expanded data sets to give providers real-time visibility in performance and opportunities to improve care. This informs incentive programs for both physicians and care team members.
Thirdly, Summit heavily invests in resources and infrastructure for best-of-breed population and health management. The goal is to assess the impact of investments and create ROI analyses to inform future strategic decisions, Reedy explained.
This data infrastructure is the foundation, which is why Summit prioritizes value in these specific categories. The organization refined these priorities upfront, which informs key questions internally.
"Revisiting the value question is what helped us to make sure that we had the right expertise internally to use and understand all of the data sources," Reedy said.
A significant decision for quickly driving data value is partnering with experienced vendors. Summit works with Arcadia to learn how to best utilize data for these priorities.
Creating better outcomes should be the driving factor for prioritization, Parikh explained.
Summit desired to use its analytics platform and data to improve patient outcomes, bringing success with value-based contracting.
According to Parikh, spending more on patients in ambulatory settings alleviates the costs in expensive care settings like hospitals and emergency rooms. This is why the organization focuses on reducing hospitalizations.
"Whenever we think of value, and we try to convert all of our stakeholders into value-based believers, we always use the value formula–improve outcomes, which is basically better quality, better patient experience," she said.
Summit leads its providers and clinical teams, explaining that value-based care will be better for patients and bring better outcomes. However, the organization also aligns incentives with it.
The Universal Provider Incentive Program (UPIP) is for specialty physicians where 20% of their compensation is tied to value-based outcomes. These outcomes include quality measures, patient experience, and acute disease burden capture.
"For our primary care physicians, we wanted to really move that one step further and tie panel-based outcomes and performance and its impact on our value-based contracts," Parikh said.
Summit's vendor partner, Arcadia, works to help create multiple bonus measures for primary physicians, such as risk-adjusted admission and quality impact score.
"With these elegant measures, we were able to give primary care providers data that shows them how well they're doing on their panel, how it impacts our value-based contracts, and how then, secondarily, it will impact their incentives," she explained.