Healthcare data models drive member engagement
Health Plans

Identification and stratification: A proven approach for improved outcomes

October 8, 2020
How one self-funded employer group increased referrals by 583%.
Shelley Riser

Healthcare organizations, including health plans, hospital systems and providers, are taking a page from other industries such as banking and online retailers. They are investing in patient relationship management (PRM) systems for more proactive engagement tailored and personalized to individual members and patients. The need for these investments has been driven primarily by two market dynamics – increased consumer choice and personalization, and a focus on improving patient and member satisfaction.

A PRM system is an investment and often part of a phased approach to value-based care. A recent keynote session, ‘From Volume to Value – A Paradigm Shift’, at the HIMSS & Health 2.0 European Digital Conference, discussed the “need to move from volume to value to improve patient outcomes but also increase the sustainability of the overall health system.” Not surprisingly, the European healthcare system faces some of the same challenges the U.S. system does. According to Healthcare IT News, the panelists, “agreed that striving for quality requires a fundamental shift to value-based care.” This matters because, “The proposed model would focus on value and quality of care in the interests of the patient, which according to the panelists would improve clinical outcomes and reward healthcare providers.”

A phased approach to population health management helps organizations and their people thrive while successfully transitioning to value-based care. For example, a first phase is designed to focus on a solution that addresses an immediate need. Success metrics are defined to show return on investment. This is an alternative to an all-in approach to value-based care.

A first phase might look like this:

  • First value-based contract with a healthcare provider signed
  • Data analytics to identify and risk-stratify the population
  • Off-the-shelf, easy-to-implement dashboards with actionable insights
  • Plan for acting on the insights to drive performance

Subsequent phases for implementing value-based care could include:

  • Pre-packaged, pre-configured care management workflow and clinical services for sharing referrals with providers and care coordination
  • An enterprise PRM system for greater population engagement throughout members’ healthcare journey

What to Look for in a Data Analytics Platform

The three things to look for in a data analytics platform are:

  1. Be sure the vendor understands the unique challenges of your market – your payer or provider mix, the demographics of your population and more. For example, there are similarities and common challenges among rural and independent hospitals, but perhaps more importantly, there are significant differences.
  2. Ensure the vendor practices what they preach. For example, Geneia has clinicians on the team. With input from our clinicians, we create our own analytic models that are used by clinical teams to identify, stratify and engage populations of patients who are most likely to have complications from diabetes or heart failure within the next 12 months or patients who have tested positive for COVID-19 at risk for developing severely adverse health outcomes.
  3. Patient engagement, navigation services and ultimately revenue maximization efforts need to focus on more than the chronically and catastrophically ill. There are many opportunities with healthy and rising-risk patients. As healthcare organizations emerge from the first wave of the COVID-19 pandemic and begin resumption of care and shore up revenues, there has never been a better time to focus on healthy and rising-risk patients.

Applying Data Analytics to Population Identification and Stratification

Next-generation data analytics solutions provide advanced population identification and stratification capabilities. Data science models improve identification by using multiple data sources, such as claims and clinical, to more accurately identify and group members according to similar characteristics or predicted outcomes. For example, members who are at risk for being readmitted to the hospital within 30 days, members with high expected future costs, and members likely to develop complications from type 2 diabetes or heart failure would be examples of cohorts to receive evidence-based outreach and intervention.

Look for data-analytic solutions with these capabilities:

  • Prediction and identification of high-risk members using market-leading analytics and predictive modeling
  • Care coordination and case management to engage members earlier and help manage outcomes and costs
  • Measurable savings and increased member engagement to demonstrate return on investment for employers

Geneia’s Theon® platform uses risk scores*, demographics, 100 clinical markers and gaps in care to make it easy for organizations to identify and stratify members into four categories. Members fall into one of four groups including healthy, rising risk, chronically ill and catastrophically ill.

Risk group factors

The following example illustrates how advanced predictive analytics further stratifies the chronically ill group. Members in the chronically ill category with diabetes, hypertension and heart failure – some of the highest cost chronic conditions - are grouped together. Using predictive analytics from Geneia’s data science models, this group is further stratified based on the likelihood of complications in the next twelve months. The top 10 percent are grouped and referred for interventions.

Advanced predictive analytics

Visualization and Engagement Tools

The Theon® platform applies data analytics to identify and stratify populations, uncovering insights that allow providers using a PRM to provide more personalized, patient-centered care.

  • The Theon® Platform for Population Analytics (Theon® Population Analytics) takes in multiple types and sources of member data, analyzes the data, and returns insights and information at the population and individual member levels that allows users to take specific actions and informs clinical and operational decisions.
  • The Theon® Platform for Care Management uses insights from Theon® Population Analytics and has features like pre-configured guided interactions, evidence-based assessments, care plan content and ready-to-use reports to help providers better engage members in their care.

With ready-to-use data analytics and clinical workflows, health plans and providers have the right patient insights to drive earlier interventions, avoiding chronic conditions and reducing emergency room visits and readmissions. Theon® Population Analytics and Theon® Care Management help health plans and providers better manage the entire population regardless of where they fall on the risk spectrum. By ensuring accurate and early identification, and appropriate stratification and prioritization, activities such as member outreach and engagement and care coordination are more effective, providers and health plans are more aligned, and members are more satisfied.

Success Stories

Success Story 1

A Geneia health plan client generated significant savings through the use of Geneia’s robust next generation identification and stratification models and advanced care engagement. Across its full book of business, the health plan client realized estimated cost savings of more than $7,500 per member.

For every $1 in administrative cost spent on the case management program, the health plan saved more than $3 in healthcare costs.

Estimated cost savings

Success Story 2

A Geneia client that is a large, self-funded employer group also generated significant savings by using Geneia’s robust next generation identification and stratification models and advanced care engagement. The following compares the employer group’s performance before and after implementing the Theon® platform and advanced care model. Once Geneia’s solution was implemented, referrals increased by 583 percent, and the identification and stratification models uncovered 32 percent of members who met the criteria for referral to advanced care engagement.

Referal identification breakdown for a large, self-funded employer group client

As illustrated by these success stories, healthcare organizations using data analytics to identify and stratify member populations and build better relationships with providers and members, are winning hearts, minds and wallets. Value-based care and personalized engagement are the keys to truly delivering patient-centered care.

To learn more about how Geneia helps healthcare organizations succeed in value-based care, download the white paper, How a Phased Approach to Value-Based Care Works: For Health Plans, Hospitals and their Value-Based Partners.

*Geneia can use commercially available risk models, its own risk model built internally or risk models clients already have in place.