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Research Studies is a compilation of published research articles funded by AHRQ or authored by AHRQ researchers.
Results
1 to 2 of 2 Research Studies DisplayedRichesson RL, Sun J, Pathak J
Clinical phenotyping in selected national networks: demonstrating the need for high-throughput, portable, and computational methods.
The authors sought to use electronic health records data to advance understanding of disease risk and drug response, and to support the practice of precision medicine on a national scale. They found that machine learning approaches that generate phenotype definitions from patient features and clinical profiles will result in truly computational phenotypes, as it comes from data rather than experts. They suggested that research networks and phenotype developers cooperate to develop methods, collaboration platforms, and data standards that will enable computational phenotyping and modernize biomedical research.
AHRQ-funded; HS023921; HS023077.
Citation: Richesson RL, Sun J, Pathak J .
Clinical phenotyping in selected national networks: demonstrating the need for high-throughput, portable, and computational methods.
Artif Intell Med 2016 Jul;71:57-61. doi: 10.1016/j.artmed.2016.05.005.
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Keywords: Data, Electronic Health Records (EHRs), Genetics, Patient-Centered Healthcare
Roberts MC, Bryson A, Weinberger M
Patient-centered communication for discussing oncotype DX testing.
The researchers identified patient-centered communication strategies/gaps for discussing Oncotype DX testing (ODX) results. They applied a patient-centered communication framework to analyze qualitative interviews with oncologists about how they communicate about ODX with patients. Overall, providers discussed four patient-centered communication domains: exchanging information, assessing uncertainty, making decisions and cross-cutting themes.
AHRQ-funded; HS019468; HS022189.
Citation: Roberts MC, Bryson A, Weinberger M .
Patient-centered communication for discussing oncotype DX testing.
Cancer Invest 2016 May 27;34(5):205-12. doi: 10.3109/07357907.2016.1172637.
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Keywords: Cancer, Cancer: Breast Cancer, Communication, Clinician-Patient Communication, Decision Making, Genetics, Patient and Family Engagement, Patient-Centered Healthcare, Women