“Hurdle rate” is a business school term for the minimum rate of return on investment (ROI) on a given project that an organization is willing to accept before financing it.

 

The hurdle rate is usually determined by evaluating the risks and potential returns of the project itself and the cost of forgoing other projects.

 

I first heard this term when I spoke on enterprise fraud control at the HIMSS conference last year and immediately understood how important it was. The key to measuring a hurdle rate accurately is, of course, dependent on accurately measuring ROI. Do we really have an accurate way to measure the return on implementing an enterprise fraud control project, particularly in a pre-pay environment? The short answer is no.

 

More traditional IT project hurdle rates can be measured fairly accurately. The fact that pre-payment fraud analytics and enterprise fraud control are newer concepts in the healthcare world creates a “hurdle” to getting these kinds of projects funded.

 

I actually think the answer to the problem is straightforward. Whenever fraud control in healthcare is discussed the credit card industry is held up as the model. Losses to improper payments are generally agreed to be well under 1 percent in the credit card industry – as opposed to approximately 10 percent in our industry. It is also agreed that the credit card industry makes much more serious investments in fraud control. The problems in financial services and healthcare are very different, so the solutions are also different, something that has been underestimated by technology vendors, but I would still argue the formulas for investing in fraud control are quite similar.

 

It is common for a healthcare enterprise that deals with millions of patients, members and/or providers to have a paltry dozen people working with 10-year-old, incomplete, outdated technology to try to detect improper payments – after they are paid – and recover the funds. This solution is inadequate on its face.

 

Even under these circumstances ROIs on the order of 4 to1 are common. The green space for analytics in our 2.5 trillion dollar industry is tremendous.

 

What IT professionals who want to move their enterprise toward maximizing pre-pay fraud control need to do is understand the investment and incremental steps taken in other industries to achieve the levels of fraud control they now maintain. By comparing relevant metrics – transactions, payments, and customers – we should be able to come up with a defensible business case for IT investment even though cost savings will often be difficult to measure directly. Property and casualty insurance is well ahead of healthcare in this regard and is perhaps the first place to look for lessons.

 

Innovative IT professionals and technology vendors need to be carefully building the business case for applying the right analytics at the right point in the payment workflow. This is the only way we can bend the cost curve and achieve the real goals of healthcare reform, which are ultimately quality care and lower cost for all.