Computational disease state modeling adds value

Mar 01, 2010

Our current system puts private, third-party payers in a key position, because they provide the financial incentives that drive behavior through a large portion of the healthcare system.

Our current system puts private, third-party payers in a key position because they provide the financial incentives that drive behavior through a large portion of the healthcare system. Because of their relatively sophisticated understanding of the system as a whole, they are in a position to advocate for specific interventions on the basis of clinical value and financial cost and to shape clinical practice through the incentives they offer.

To do this effectively in an environment in which data is plentiful but clear conclusions are rare, new tools will be needed, such as computational disease state modeling, which can improve payers' ability to rationally and successfully achieve cost-effectiveness and clinical value.

Even with healthcare costs reaching unsustainable levels, getting more value is clearly desirable. What has changed, though, is the set of incentives that govern payer behavior from one that follows the decisions made by Centers for Medicare and Medicaid Services (CMS) to one in which acceptable cost-benefit tradeoffs is the appropriate strategy.

Offering better value means differentiating. The incremental value of yet another combination of deductible, copayment and premium is virtually nothing. Structure incentives for more cost-effective treatment by encouraging specific preventive, diagnostic and treatment choices and discouraging less cost-effective ones.

How can a payer determine which care path to encourage and how to do this while minimizing concerns about restricting the right of physicians and patients to determine the treatment?

One approach that has been tried is the panel of experts: a group of practicing physicians who agree on a set of treatment guidelines. This approach, however, has several problems, including getting the physicians to agree, lack of consideration for cost-effectiveness, and the fact that guidelines produced by a panel of experts are often disregarded because doctors often have more confidence in their own clinical judgment.

Computational Disease State Modeling

A tool that can help is computational disease state modeling, which is the creation and use of mathematical and statistical models that:

In some ways, disease state models are similar to the more familiar pharmacoeconomic models used to assess the cost-effectiveness of an intervention.

Disease state modeling has a number of potential uses. It can be used to improve estimates of treatment cost-effectiveness, which can be validated through clinical studies or advocated without additional evidence. This opens up the potential to create health plans that are tailored to be cost-effective for specific groups. Because of the way such models are constructed, the salience of specific impacts to customers (whether patients or employers) can be incorporated directly into the model.

More generally, disease state modeling can be used to create a system of differential incentives that encourages behavior on the part of patients and physicians leading to maximally cost-effective outcomes. It offers payers a coherent and defensible methodology for addressing the complexity of the health status of the insured and provides interaction with lifestyle and clinical choices to find more value for healthcare expenditures.

A number of examples of disease state modeling are already in practice including the use of the cardiovascular "polypill" (an ACE inhibitor, aspirin, metformin, and a generic statin), which was found to reduce the risk of heart disease in diabetics.

Disease state modeling is a new tool in the arsenal for those interested in delivering the best care at the lowest cost. It is in its infancy, but has already begun to prove its worth, and will become a more powerful tool as techniques and models improve. For payers, it represents a potential point of competitive differentiation as fundamental as value for money itself.

Mark T. Morgan, M.S.(R) is a Senior Analyst, and Michael N. Abrams, M.A. is Managing Partner at Numerof & Associates, Inc. (NAI), a strategic management consulting firm focused on organizations in dynamic, rapidly changing industries.

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