Risk adjustment relies on a long list of health and demographic data points to estimate the cost of patient care across a specific population. Getting it right is critical for ensuring that reimbursements accurately reflect the cost of value-based care.
As the data picture becomes more complete, the promise of risk adjustment processes to deliver near-real time insights for improving financial performance and patient care is within reach.
But it is a complex process, and many payer organizations struggle to achieve the data aggregation and analytic capabilities needed to ensure a complete picture.
Optimized risk adjustment relies on integrated claims and medical records, the ability to analyze large – and growing – volumes of data, meticulous coding and documentation, and careful collaboration between payers and providers.
It is a lot of detail with a lot of room for error in an undertaking where precision is key. Among the challenges payers face in managing their risk adjustment efforts are:
- Fragmented and ambiguous data
- Provider abrasion
- Inaccurate coding and risk scoring
- Lack of next generation analytics and AI capability
- Normalizing and scaling vast amounts of available data
- Shrinking margins for MA plans
- Tightened CMS criteria for Star ratings
Solutions for harnessing the data
The increasing amount of data available is both a challenge and an opportunity. Before it can be used to create a robust picture of population health, data must be captured from a broad array of sources so that patient care can be tracked across time and across multiple providers. It must be standardized for ease of use and analysis and validated for accuracy. And it must be compared to key benchmarks to identify opportunities to close care gaps and improve utilization.
Achieving all of this requires a sophisticated data analytics strategy and key components that include:
An advanced analytics engine and scalable cloud infrastructure for processing large volumes of data quickly, identifying trends and anomalies and providing real-time data for better and more timely healthcare decisions
Integration of claims and clinical data, including pharmacy data, with benchmarking against industry standards
AI-enabled workflows for automated coding with fewer errors, streamlined workflows and predictive analytics to identify risk factors and opportunities for intervention.
The Milliman MedInsight Risk Adjustment Suite
At Milliman MedInsight, our risk adjustment suite was built to empower payers with the tools and analytics needed to take risk adjustment processes to the next level. With advanced algorithms and predictive modeling capabilities that both optimize and simplify the process, the Milliman MedInsight Risk Adjustment Platform and industry-leading population health analytics tools enable payers to quickly identify sources of risk and opportunity with unmatched precision and customization.
Capabilities:
- Amenable to all types of business including Medicare, MA and REACH plans
- Provides data in near real-time, down to member level
- Seamless integration of claims and medical records that streamlines workflows, improve accuracy and enhances response tracking
- Proactive identification of members who may benefit from additional care and interventions to improve health outcomes and Star ratings
- Enhanced coding compliance
- Timely collaboration for many different perspectives
- Peer comparison ability via access to comprehensive CMS data
- Leverages Milliman MedInsight actuarial expertise
- AI-driven risk workflows and clinical documentation
To learn more about our risk adjustment tools and analytics, including the Milliman MedInsight Risk Adjustment Platform, watch our webinar: Integrated Risk Adjustment Solutions: Enhancing Reimbursement and Patient Care
Among other things, you will see a live demo of the risk adjustment platform’s ability to drill down into plan performance, revenue and patient care.
You can also contact a member of our team.