There are many factors that determine the financial investment employers make in employee healthcare, but one in particular has a significant impact on the bottom line: unexpected care utilization. Enhanced data science capabilities can help plan for and manage these costs and improve the health of employee populations.
Eliminating the unexpected
Chief Data and Analytics Officer, Teri Kaslow, leads a team of data scientists at Blue Cross and Blue Shield of Minnesota. Her team identifies data points that indicate how members will — or will not — utilize care options before costly health events occur.
One goal of the data science team is to proactively identify potential gaps in care for Blue Cross members. Using a combination of historical medical and pharmacy claims data, risk scores, and social needs data, the team provides a targeted list of members to the care management team for outreach. Being able to predict the individuals who have the highest needs helps ensure the efficient use of resources. In addition, connecting care managers to the right members at the right time helps reduce the total cost of care by as much as $19,000 per engaged member per year.*
“No longer can businesses make decisions by looking in the rearview mirror,” says Kaslow. “We must look ahead to solutions like predictive analytics, which drive outcomes for our members and our businesses to further improve quality, costs and timing of healthcare.”
Beyond the doctor's office
Research shows that social determinants can be more important than healthcare or lifestyle choices in influencing the quality of overall health.
Financial stress, social isolation, food insecurity, transportation challenges and more can ultimately influence the care a member seeks. Blue Cross is using social data points, such as where employees live, work and learn, to help predict unmet social needs.
By understanding systemic issues and the associated risks that accompany them, Blue Cross can create programs and personalized next best actions that are designed to specifically help these populations. For example, knowing a member is at risk for financial stress helps us understand why they may not be taking a prescribed medication. By leveraging this data, we can offer assistance and programs that address barriers and improve health.
Insights to action: Guidance goes a long way
The recently introduced Blue Care Advisor engagement solution leverages collected data to gather insights and communicate prioritized next best actions for each member based on their personal healthcare journey. Next best actions are presented through the app, computer or via email, creating a meaningful and relevant experience for the member while also helping close gaps in care.
For example, a Blue Care Advisor member identified as low risk may get a push notification on their app that it’s time to update their child’s routine immunizations, with the goal of preventing the need for downstream care later. Whereas a member identified with a high-risk chronic condition may benefit from periodic calls from a care manager to make sure they’re taking their blood pressure medicine and scheduling follow-up cardiology appointments.
“Blue Care Advisor is one way we are moving from a reporting-only discipline to a predictive and prescriptive discipline that benefits members and employers to improve health and control costs,” says Kaslow.