title: Personalized Medicine's Bottleneck: Diagnostic Test Evidence and Reimbursement.
abstract: BACKGROUND
  Personalized medicine is gradually emerging as a transformative field. Thus far, seven co-developed drug-diagnostic combinations have been approved and several dozen post-hoc drug-diagnostic combinations (diagnostic approved after the drug). However, barriers remain, particularly with respect to reimbursement. Purpose, methods: This study analyzes barriers facing uptake of drug-diagnostic combinations. We examine Medicare reimbursement in the U.S. of 10 drug-diagnostic combinations on the basis of a formulary review and a survey.
  
  
  RESULTS
  We found that payers reimburse all 10 drugs, but with variable and relatively high patient co-insurance, as well as imposition of formulary restrictions. Payer reimbursement of companion diagnostics is limited and highly variable. In addition, we found that the body of evidence on the clinical- and cost-effectiveness of therapeutics is thin and even less robust for diagnostics. Conclusions, discussion: The high cost of personalized therapeutics and dearth of evidence concerning the comparative clinical effectiveness of drug-diagnostic combinations appear to contribute to high patient cost sharing, imposition of formulary restrictions, and limited and variable reimbursement of companion diagnostics. Our findings point to the need to increase the evidence base supportive of establishing linkage between diagnostic testing and positive health outcomes.
authors.affiliation: Tufts Center for the Study of Drug Development (Tufts CSDD), Tufts University Medical School, 75 Kneeland Street, Suite 1100, Boston, MA 02111, USA. joshua.cohen@tufts.edu.
authors.forename: Joshua P
authors.initials: JP
authors.lastname: Cohen
authors.affiliation: Tufts Center for the Study of Drug Development (Tufts CSDD), Tufts University Medical School, 75 Kneeland Street, Suite 1100, Boston, MA 02111, USA. abigail.felix@tufts.edu.
authors.forename: Abigail E
authors.initials: AE
authors.lastname: Felix