OBJECTIVES: Personalized medicine tests (PMT) are increasingly available in the healthcare marketplace.  The diffusion of such technologies is in part a function of the collective preferences of patients, providers, and payers. The objective of our study was to identify the attributes of PMTs most important to patients and thus likely to impact individual decisions and population level adoption. METHODS: We used a mixed methods study design to identify the attributes of PMTs that impact patient decision-making. We recruited patients with and without prior PMT experience to participate in focus groups and interviews via flyers, provider contacts, and disease support groups. Patients completed an attributes ranking exercise and a payment card scenario to estimate willingness-to-pay (WTP) for PMTs. Analysis of transcripts was performed using thematic coding, analysis of attribute ranking used a rank-ordered logit model, and payment card data was conducted using interval regression. RESULTS: We contacted 32 patients of which 20 ultimately participated (focus groups: 14; interviews: 6). Analysis of the attribute rankings indicated that the most important attributes were: 1) ability to select the appropriate treatment, 2) benefit to family members, and 3) quality of life after testing. The rankings for these characteristics were all statistically significant. The average willingness-to-pay for a PMT was $1,528 (95%CI: $361-2,694). Patients making less than $25K/year had a statistically significant lower WTP ($373) compared to the population average.  CONCLUSIONS: Patients showed a strong preference for the ability to select the appropriate treatment based on test results as well as the impact of test results on their family and their quality of life.  Patients were willing to pay more than would typically be required in an insured population but less than the full cost of some commonly used PMTs. This work will ultimately be used to inform the development of a discrete choice experiment.