Type 2 Diabetes is a major health problem in the US.

  • The disease affects ~30 million Americans at an annual cost of ~$250 billion.
  • It is the leading cause of death in the U.S., as well as the leading cause of kidney failure, stroke, heart disease, loss of toes, feet or legs and blindness.
  • In addition to the Diabetes, nearly 1 of 3 adults in the US have pre-diabetes.
  • 10% of pre-diabetics progress to type 2 diabetes within a year and 15-30% progress within 5 years (CDC Diabetes Report, 2014).

Early diagnosis and effective care have been shown to prevent progression, but counseling 1/3 of the population can be prohibitively expensive and the benefits may not be seen immediately. This leads to low to negative ROIs on broad based coaching programs. Effective use of analytics can help mitigate this problem. Some of the key questions that need to be addressed are:

1) What is the cost of progression to diabetes?

Knowing the cost of progressing is crucial to understanding the potential financial benefits of implementing a diabetes management program. Fischer Jordan’s analysis has shown out the initial increase in claims cost for a member who is recently diagnosed with diabetes is $550/year. In subsequent years (for individuals who have had Diabetes for more than 1 year), the cost difference between pre-diabetics and Diabetics averages ~$1,100 /year. Apart from the increased claims costs, there may be additional costs due to lost productivity.

 

2) How do we reduce the incidence of undiagnosed pre-diabetes and diabetes?

1 of 3 diabetics do not know they have diabetes. 9 of 10 pre-diabetics are not aware that they are pre-diabetic.

Health Assessments and Biometric Screenings are powerful tools for driving early identification. Our analysis has shown that the lift in identification is nearly 15x for individuals taking a health assessment. Companies have implemented expensive incentive programs to drive members to take health assessments. Our analysis has shown that while the incentive programs are effective, implementing an analytics based strategy has the potential save tens of millions of dollars without affecting outcomes. Some key questions that need to be answered are:

1) What is the right level of incentives to offer?

2) Do we need to offer incentives every year?

3) How do we split out budget between awareness/education and incentives?

4) Incentives drive engagement, but do they drive outcomes?

 

3) Does our diabetes management program work?

Experienced nurses and coaches engage people through multiple channels to educate them on their health. These programs provide health coaching via multiple channels such as in person coaching sessions, phone based coaching, digital coaching, and group sessions.

However, telephonic and in person coaching sessions can be very expensive to implement, thus having a robust program in place to measure effectiveness is crucial.

 

4) How do we identify the highest priority individuals for coaching?

Since the population of pre-diabetics is so large, it is often cost prohibitive to engage the entire population via nurses or wellness coaches. It thus becomes important be focused on using expensive channels to engage individuals who want to engage and on individuals that are most at risk for disease progression.

 

Conclusion

Disease progression from a pre-condition stage to chronic condition is becoming a major health focus area for population health management because of rising health costs associated with progression. Data driven strategies can be specifically designed to support preventive health initiatives by healthcare companies. Stratification and identification of at-risk patients as well as focused patient engagement to promote patient centric engagement all contribute to improved clinical outcomes and financial results.

Learn how our solutions for risk and engagement stratification and strategies for population health management can maximize $ savings: Talk to Us

 

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