Benefits consultants use data as a part of the consulting services provided to employers. The consulting strategy includes looking at health claims throughout the benefits year, creating reports and reviewing the reports with the benefits administration team.
“But this approach of simply ‘keeping score’ of data doesn’t accomplish the goals of every employer, which is to drive down the costs of a health insurance program,” says Michael Galardini, director of sales at JRG Advisors. “The next generation benefits consultant uses predictive modeling and data analytics to lower the largest cost of a health insurance program: emerging claims.”
Smart Business spoke with Galardini about how employers can get better results with emerging claims to lower the costs of a health insurance program.
How can predictive modeling and data analytics software identify risks andimprove a health insurance program?
Predictive modeling and data analytics software is a population health management service that can identify the high-risk members of a health insurance program.
Once identified, these members are ranked by severity and gaps in care. A web-based reporting system will provide access to the actionable information to target these high-cost and high-risk members. The system reveals the members who are noncompliant with preventive care — and members who require disease management, prescription drug maintenance or health coaching intervention.
Managing this data properly can ensure that these high-risk members don’t fall through the cracks.
Once properly identified, the next step in the risk management strategy is to evaluate the actual cost and forecast the cost in the next 12 months for each member. These include things like the number of emergency room and inpatient stays for each member in the next year. By identifying and evaluating these emerging claims, consultants can now get ahead of the costs that are driving the increases in premiums.
What’s the benefit for employers?
Identifying and managing these claims helps stabilize or lower the premium costs. The old process of reviewing claims data after the claim already occurs doesn’t allow the benefits consultant to provide a strategy to mitigate the costs to the employer.
Using predictive modeling and data analytics to identify high-risk members gives time to develop a population health management strategy to better manage the emerging claims.
What is population health management?
A significant component of reducing the identified health risk is using care managers to work with high-cost and high-risk members. Benefits consultants partner with care managers to review the data provided by the predictive modeling and data analytics software to motivate these members to manage their health care. Care managers can work directly and confidentially with the members to ensure the proper medical care is being provided for their specific medical conditions. These members will be guided through actions, such as timely preventive care, prescription drug adherence and coordination of care.
How do employees benefit?
The goal of the care managers is to teach the high-cost and high-risk members to self-manage their health care, comply with care instructions and pursue ways to improve their health status. Care managers can also use cost transparency tools to guide the member to find the best price for medical services. This not only keeps the claims costs lower for the health insurance plan, but also can help lower out-of-pocket costs the member has in the form of a deductible or co-insurance.
Incorporating predictive modeling and data analytics with a population health management strategy can produce the result that every employer expects from a benefits consultant — disrupting the current distribution model to move the needle of the emerging claims to lower the costs of a health insurance program.