FACTORS AFFECTING THE ADOPTION AND USE OF GENE EXPRESSION PROFILING BY ONCOLOGISTS IN CLINICAL PRACTICE

Wednesday, October 23, 2013
Key Ballroom Foyer (Hilton Baltimore)
Poster Board # P4-8
Decision Psychology and Shared Decision Making (DEC)

Amalia M. Issa, PhD, MPH and Dhaval S. Patil, University of the Sciences in Philadelphia, Philadelphia, PA
Purpose: The purpose of this study was to determine the association between specific characteristics of a gene expression profiling (GEP) assay, Oncotype DX® and oncologists’ intention to use Oncotype DX® to make treatment decisions for breast cancer patients.

Method:

A nationally representative sample of oncologists treating breast cancer were surveyed using an online questionnaire based conceptually on the Technology Acceptance Model (TAM). The TAM represents a well-validated conceptual model, having most influenced theories about human behavior in relation to factors that explain or predict the use of different technologies (and how end-users decide about and use a particular technology), and thus is useful in our quest to better understand how oncologists are adopting and utilizing Oncotype DX®. Linear regression analysis was performed to establish the association between physicians’ perceptions and intentions to use Oncotype DX®

Result: A total of 119 completed surveys were received giving a response rate of 51.11%. Of the Oncotype DX® test characteristics evaluated, `validity of the test’  (p= 0.006) and ‘use of Oncotype DX® by fellow Oncologists’ (p=0.0068) were significantly associated with oncologists’ use of Oncotype DX® Oncologists’ intention to use Oncotype DX® increased consistently with their perceived usefulness of Oncotype DX® (β =0.222). Insurance status of the patients was also significantly associated with physicians’ use of Oncotype DX® (p=0.008). 

Conclusion:

Several characteristics related to the GEP, Oncotype DX® impact oncologists’ intention to use Oncotype DX® in the clinical setting to make treatment decisions for breast cancer patients. This study has implications for knowledge translation efforts related to novel personalized genomic medicine applications.