CDA 16-206
Improving the Use of Tumor Genetic Testing with Decision Science
Daniel J Becker MD New York, NY Funding Period: March 2020 - February 2025 |
AbstractBackground: Recent advances in cancer care have come from identifying the genetic mutations in an individual’s cancer, and focusing on those abnormalities with “targeted therapy,” i.e. precision medicine. Available genetic information is expanding rapidly and initial research suggests that oncologists struggle to order the correct tests at the correct times and use the results effectively to choose medication. We sought to study the scope of variation in the use of molecular testing and targeted therapy (MT/TT), the barriers to guideline concordant care, and to create an intervention to improve the use of guideline concordant MT/TT. Significance/Impact: More than 10,000 VA patients were diagnosed with lung and colorectal cancers in 2010, creating a pressing need to ensure that guideline concordant MT/TT are implemented rapidly and effectively. The Cancer Moonshot Initiative funded the Precision Oncology Program (POP) to increase access to MT/TT throughout the VA, but recent reports indicate that only 1/3 of VA medical centers (VAMC) are participating, and benefits are inconsistent among those hospitals. Research is needed to ensure that all veterans with cancer receive state of the art MT/TT via POP or other mechanisms. Innovation: This is among the first studies to use a mixed methods approach, combining both quantitative and qualitative research methods to address the complicated problem of implementing cancer MT/TT. The qualitative portion includes interviews of patients to understand their frequently neglected perspective. Specific Aims: Specific aim 1 uses national VA data from the VA Corporate Data Warehouse (CDW), and molecular testing data from contracted vendors and the VA POP to understand the patterns and predictors of guideline concordant care. Specific aim 2 seeks to conduct semi structured interviews with both patients and providers at centers with low guideline concordant MT/TT, high guideline concordant MT/TT, and centers implementing the POP program. The interviews are designed to elicit the barriers to guideline concordant care. Specific aim 3 is designed to use the data gathered in the quantitative and qualitative studies, along with behavior change theory, to design a behavior change strategy that empowers both patients and providers to improve care. Methodology: The quantitative portion of the mixed methods approach will study the national database of approximately 70,000 veterans diagnosed with either lung or colorectal cancer between 2010 and 2017, to identify patients at high risk for not receiving guideline concordant MT/TT. The qualitative phase of the study will interview 18 providers and 18 patients representing VAMC’s with high guideline concordant care, low guideline concordant care, and sites participating in the POP. The data from the quantitative and qualitative phases will form the basis for a multifaceted intervention to improve the use of guideline concordant MT/TT. The intervention will be further refined by a panel of patients, clinicians, behavior change experts, and operations stakeholders prior to testing it in VAMC’s. Next Steps/Implementation: The behavior change strategy will be tested in first a single site, and then multi- site clinical trials to examine effectiveness. The rapidly expanding knowledge about molecular drivers of cancer presents not only great promise for cancer patients, but also significant challenges for oncologists and patients trying to ensure that these advances are rapidly incorporated into care. The proposed research is designed to help VAMC’s implement effective evidence based strategies to incorporate cancer MT/TT, positioning the VA as a leader in precision medicine.NIH Reporter Project Information: https://reporter.nih.gov/project-details/9837225 PUBLICATIONS: Journal Articles
DRA:
Cancer
DRE:
Genomics, Technology Development and Assessment
Keywords:
Career Development
MeSH Terms:
None at this time.
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