Seeing the complete picture also requires bringing in de-identified data from health plans and other sources to create personas that represent different employee types. These personas deliver additional insights into who the employees are, using data such as their income and education levels, where they live (zip+4), family situation, ethnicity, co-morbid conditions, lifestyle choices and other factors to better understand the overall employee population, as well as the most appropriate use of healthcare services.

Developing risk scores

With this information in hand, brokers and employers can use the analytics to create risk scores for each covered member (employees and their families) that help them set priorities on plan design based on two factors: impactability and intervenability.

Impactability is the likelihood that the member will achieve a positive outcome by closing a care gap. With dollars limited, and the goal of improving outcomes while lowering or at least controlling spiraling costs, it makes little sense to pursue interventions or introduce health plans that will not have an impact on the member's health.

Intervenability is the likelihood that the member will become engaged in and follow a care plan, and eventually close the care gap. Health plans that invest in incentives or programs such as care management for members who are deemed unlikely to follow them are a waste of time, energy, and resources. It would be better to redirect those limited resources to areas where members will make the effort so positive changes can be achieved.

By creating health plan options that take into account the highest scores for impactability and intervenability (as well as the highest risk), brokers and employers can address outcomes and cost more effectively.

Extended value

The use of personas and risk scores extends beyond identifying whom to target. They also provide guidance on how to approach those members to make the changes.

For example, suppose the data indicates that a care management program should be included as part of a plan to address diabetes. Care managers at the payer can match the persona to specific, re-identified member profiles that include income, education, and other social determinants, and use that information to design a plan of care that is achievable. They can also see where obstacles exist, such as a lack of access to healthy foods in a particular neighborhood or town, so they can work with members to create alternatives that will work for their situation.

Meaningful reports

The final advantage next-generation behavioral analytics offers brokers is the ability to create comprehensive reports. These reports can be used to detail the progress the program is creating and the overall impact it is having. They can also be used to demonstrate where additional improvements can be made, or where a new issue has appeared that should be addressed, keeping employers ahead of the cost curve.

Demonstrating the value-add

Brokers that show employers how to reduce absenteeism and reduce “presenteeism” (preoccupied by non-work activities at work) elevate themselves from being just another “vendor” to a position of trusted advisor. They also move the focus of the conversation away from premium costs to a much larger picture.

Creating well-tailored, effective health plans that help improve outcomes while reducing the skyrocketing cost of managing chronic condition for employers and their employees is the key. Next-generation behavioral analytics make it happen.

David Hom is Chief Evangelist at SCIO Health Analytics®, an organization dedicated to using healthcare analytics to improve clinical outcomes, operational performance and business results. He is an internationally-recognized expert in the field of consumer engagement through programs such as Value Based Benefits and Employee Wellness.