Personalized and precision medicine (PPM) has the potential to reduce the incidence of heart disease by 50 percent and save $607 billion over a span of 50 years, but reimbursement concerns stand in the way, according to a “Personal View” article featured in The Lancet.
"Preventive, personalized, and precision medicine interventions targeted at reducing heart disease would have the greatest societal benefit, because heart disease is very common and has a relatively large effect on life expectancy," Dr. Victor Dzau, president of the U.S. Institute of Medicine, said in a statement.
Dzau and his colleagues used a health simulation model to predict the impact that PPM interventions would have in the future. They focused on PPM interventions that improve screening and risk prediction technologies and determine the individuals at highest risk of developing certain diseases.
They found that these interventions can decrease the occurrence of cancer, diabetes, heart disease, high blood pressure, lung disease and stroke by 10 to 50 percent in the U.S. between 2012 and 2060. If the interventions reduced the incidences by 10 percent, it would lead to $96 billion in savings for diabetes and $70 billion for cancer.
Despite the potential PPM innovations have for making a positive impact, the current reimbursement environment is not conducive to them. The U.S. health care system currently prefers treatments that generate greater returns in the short-term instead of maximizing overall value, according to Dzau.
But Dzau and his colleagues believe that if reimbursement was based on a test's value instead of cost, that would encourage manufacturers to develop preventive PPM diagnostic tests and bring them to market faster.
They added that private insurers favor interventions with immediate benefits and short payback periods but that the benefits of PPM innovations accumulate over a long period of time. They believe that their predictions demonstrate that developing a model that produces positive returns for private payors can benefit everyone.
