Experimental care model discourages "unnecessary" tests

January 12th, 2015

Reuters just published a report on a two-year experiment in value-based insurance being run by San Luis Valley Health in CO. The self-insured health system is using the experiment for its 725 employees and their dependents to discourage use of unnecessary, invasive, or potentially harmful diagnostic and imaging tests and other procedures (such as endoscopies or MRIs), referred to as “red” procedures. Physicians then recommend less expensive, more effective alternatives, called “green” procedures. If a patient still wants the tests performed, he or she will have to pay the whole cost. For example, a patient complaining of back pain may request an X-ray or MRI. As X-rays may often be unnecessary and not useful in diagnosing back pain, the physician then would suggest the patient try physical therapy and stretching exercises to alleviate the pain (a “green” option). If the patient still insists on diagnostic tests, he or she would shoulder the full cost. (It is worth noting that the penalty would not apply to diagnostic tests deemed medically necessary.)

With Affordable Care Act provisions aimed at cutting healthcare costs and eliminating waste (estimated to be between $490 billion and $992 billion per year), it’s no surprised that health systems and insurance companies are looking at alternative methods. While accountable care organizations are slowly gaining steam – Modern Healthcare reports that half of US hospitals plan to enter an ACO by 2013 -- value-based insurance is a newer idea, and insurers and employers are uncertain whether consumers would go for -- or understand – the carrot-and-stick approach. An expert quoted by Reuters says the idea could be attractive to employers as employees would use fewer services, and the design could get a good mix of incentives. The ACA gives Medicaid plans room for value-based care, and Michigan and South Carolina are trying it out.

The San Luis Valley experiment will wrap up at the end of the year, and data will be analyzed in 2014.