Personalized Medicine: what is the added value to healthcare systems?

Posted by ELSI Contributor on October 8, 2009

This commentary in the Genomics Law Report’s ongoing series What ELSI is New? is contributed by Katherine Payne, The University of Manchester.

The Issue

Personalized medicine can potentially offer benefits to patients by targeting the safe and effective use of medicines by using DNA-based ‘companion’ diagnostic tests to inform prescribing decisions. These potential benefits are not costless. To understand the added value of personalized medicine it is necessary to identify and quantify the true costs and benefits of introducing such companion diagnostics and medicines into healthcare systems.

Response

My raison d’etre as a health economist is to apply the concept of opportunity cost, which drives health policy-makers to consider the benefits forgone if one healthcare intervention is chosen as a treatment over the other available options. My challenge is to provide information about how to allocate scarce healthcare resources such that maximum patient benefit is obtained from every pound (dollar/euro) spent. One aim of personalized medicine is to target medicines only to patient populations that will derive a positive benefit (health improvement). In theory, it is the perfect solution to this challenge of getting value for money. Targeting (or personalizing) medicines in this way should stop scarce healthcare resources being wasted. The reality is that we know companion diagnostics are not ‘perfect’ and such tests provide ‘probabilistic information’ to prescribers.

The current regulatory climate for DNA-based diagnostics expects manufacturers to provide information on the analytical accuracy of the test. However, this information does not tell healthcare policy-makers about the added value of linking a medicine with a companion test. To be clear whether personalized medicine does add value it is necessary to understand the difference in costs and benefits of using a companion diagnostic compared to current prescribing practice. The benefits should be measured in terms of whether using the test to target the medicine does show increased health gain for the population of patients who are prescribed the medicine. Depending on the chosen viewpoint of the evaluation, the costs are those for the healthcare system but may also include patient costs. Evidence must therefore be collated, using robust research methods, on how the test affects the referral of patients to care pathways, subsequent services and treatments compared to the status quo. An important challenge remains. How, and who, to fund the research to generate sufficient evidence for policy-makers deciding how best to commission personalised medicine to gain maximum benefit from the available healthcare budget?