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By CHRISTIAN BIRKMEYER, senior vice president, medical data management and analytics for SCIOinspire Inc., and IAN DUNCAN, FSA, FIA, FCIA, MAAA, president and founder of Solucia, Inc., a SCIOinspire, Inc. company.

Like it or not, the bleak economic outlook dominates headlines these days. While certainly not "new news," the crisis remains the lead story because it exerts significant pressure over all facets of business and industry. Healthcare is hardly immune, with the government, insurers and corporate America accelerating strategies to control costs.

Particularly vulnerable to this economic squeeze are corporations striving to offer adequate yet fiscally responsible health benefits to employees. More and more, they are demanding that health plans demonstrate value and return on investment with programs they propose, particularly care management initiatives.

SEEKING BOTTOM-LINE PROOF

Traditionally, this has been difficult to accomplish. While logic and common sense suggest that improved educational and outreach efforts, wellness and prevention programs, and disease intervention strategies improve care and outcomes, there has been little bottom-line proof. Emerging tools and technologies, however, are now available that allow insurers to quantify the potential effectiveness of care management efforts by incorporating risk profiling and predictive modeling as they design each program.

The most successful approach to measuring the effectiveness of disease management allows insurers and benefits managers to answer three questions:

1. Which members of an identified population group are most likely to require costly medical attention?

2. Which members are the best candidates for intervention programs designed to reduce the number of medical events and related costs?

3. What level of intervention is required to achieve maximum effect?

Often, insurers invest the majority of resources in high-risk, high-cost members. This may not represent the most effective or economical approach, however. The damage has already been done in a life-time smoker suffering from advanced emphysema, for instance. Care management efforts established to enhance disease control in these instances are largely limited to slowing the progression of disease and reducing complications.

On the other hand, care management programs designed to identify individuals at risk for future obesity may provide greater opportunity for ROI. Interventions could be designed to offer diet and exercise support and, in the process, reduce the likelihood that expensive complications will develop (e.g., hypertension, hyperglycemia, etc.).

In other words, technology that promotes risk profiling and predictive modeling enables insurers to isolate members of a group whose behavior is most likely to be altered through interventions. Programs can be designed specifically to engage these members at early stages of disease--or before risk factors become symptoms--to avoid or lessen associated medical expense.

IDENTIFYING PRODUCTIVE INTERVENTIONS

Likewise, these technology models deliver valuable information about the level of intervention that will be most effective--both in terms of cost and outcome. Let's say, for example, that a member of a specific population within a health plan is at moderate risk for back injury based on age and occupation. Yet no incident has occurred and the member is not currently under a provider's care.

It would not be economical to involve this member in a nurse-based outbound calling program. Instead, the health plan could involve less costly outreach and education efforts. Conversely, nursing resources would be well justified in a program directed at young adults dealing with diabetes. Without consistent and proper disease management efforts, these members may neglect dietary requirements that will lead to expensive co-morbidities like renal failure or circulatory complications.

Just as new technology allows disease management programs to be customized for specific population groups, the solutions themselves can likewise be tailored to health plan needs. Some available offerings can be adopted and integrated with existing in-house operations. Others can be completely outsourced, and many are conducive to a hybrid, co-sourced environment.

No matter how they are constructed, however, technology and software platforms that employ prospective analysis and measure the actual performance of specific interventions will equip insurers to:

-- Identify opportunities and gaps in care management based on under- and overutilization of benefits.

-- Promote transparency and accountability in care management programs by demonstrating where dollars are being spent, why they are being directed towards specific health plan members and what results are anticipated.

-- Shift the evaluation of care management efforts from unsubstantiated perception to measurable results.

Ultimately, by assessing opportunity, performance and effectiveness of care management, insurers will be able to demonstrate ROI to their customers and, in the long run, help improve the health of the American population while better controlling costs.

June 1, 2009

Copyright 2009© LRP Publications