Situation

We have been working with a corporate wellness provider that has a challenge demonstrating its value and return to a particular client they serve.  The client could not put all the data in one place. The biometrics data is there, but the client does not know how to use it to bring out the best results. They do not know about risk factors such as program ineffectiveness, declining population health, gaps in preventive care, unmanaged chronic conditions etc. affecting their population. We were called to help create a solution to help this provider go at risk with its client, and continue to show ongoing value by identifying the risk factors in the population that are driving costs.

Approach

On our initial data load, we took 2 years worth of claims data and processed it through our analytics platform (z5).  Out of approximately 7,000 members in the population, there were 1,315 members that were suffering from chronic conditions, including arthritis, asthma, diabetes, depression, hypertension, CAD, CHF and COPD. Many members exhibited co-morbidities as well (multiple chronic conditions). For example, 169 members manifesting 3 chronic conditions cost the employer approximate $2 million.

In 2015, the employer paid approximately $19 million in healthcare costs, and in 2016 our client introduced a new series of coaching programs for their client.

Outcome

Using our models, we have stratified the risk of the member population in order to help our client engage with the member population most in need of intervention. With a goal of attaining 10% realization of spend reduction, the predicted savings represent almost a 3:1 return on the coaching investment for this population. Using our platform, our client we can understand  the actual disease conditions driving costs, pinpoint which members to target for intervention, and predict savings if risks are mitigated.

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