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Abstract - Draft

Computer-based Clinical Decision Support (CDS) Tools for Gene-based Tests Used in Breast Cancer

Topic Abstract

The project will develop and test four clinical decision-making support (CDS) tools regarding gene-based tests for breast cancer susceptibility, prognosis, and treatment.

The first pair of tools will assess a woman’s suitability for testing for BRCA1 and BRCA2 gene mutations, which are associated with familial forms of breast cancer. One tool (Patient BRCA tool) will be designed for use by patients and the other tool (Integrated BRCA tool) will be designed for use by primary care providers.

  • The Patient BRCA Tool will: 1) assist in collection of family history of cancer to assess the risk of carrying the BRCA1 or BRCA2 gene mutations; and 2) assist in making decisions for appropriate follow up. The tool will be completed by women in their homes prior to their office visit to a primary care provider.
  • The Integrated BRCA Tool will use family history information to guide primary care providers through the process of discussing the woman's family history, cancer risk, and the recommendation for or against genetic counseling and BRCA testing.

The second pair of tools will: 1) assist in determining which breast cancer patients are eligible for a Gene Expression Profiling (GEP) test; 2) assist in making appropriate treatment decisions based on GEP test results, risks and benefits of adjuvant chemotherapy, and patient preferences. One tool (Provider Only GEP Tool) will provide passive decision support to the clinician and the other tool (Shared Decision-making Tool) will provide active decision support to the patient and the clinician.

  • The Provider Only GEP Tool will synthesize patient-specific factors and facilitate oncologists’ identification of general clinical guidelines about GEP testing and recommendations for adjuvant chemotherapy.
  • The Shared Decision-making GEP Tool will: 1) provide information customized for the individual patient; and 2) guide the patient and oncologist through the testing and treatment decision-making process.

A focused literature search and input from experts will guide development of the tools. The accuracy and usability of each tool will also be assessed. In addition, we will assess the feasibility of integrating these tools into electronic medical records and their impact on clinical work flow.

We will evaluate the impact of these tools on short-term outcomes using a cluster randomized control trial design.