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Grant Details

Grant Number: 5U01CA232826-05 Interpret this number
Primary Investigator: Kaphingst, Kimberly
Organization: University Of Utah
Project Title: Leveraging an Electronic Medical Record Infrastructure to Identify Primary Care Patients Eligible for Genetic Testing for Hereditary Cancer and Evaluate Novel Cancer Genetics Service Delivery Models
Fiscal Year: 2022


Abstract

PROJECT SUMMARY Identifying individuals with inherited cancer susceptibility is critical for targeted cancer prevention, screening, and treatment. Strategies to assess the genetic risk of unaffected individuals are needed. Scalable and sustainable methods to automatically extract and analyze family history information routinely captured in the electronic health record (EHR) can identify primary care patients appropriate for cancer genetic services. Increased patient ascertainment needs to be paired with implementation studies to compare models of delivering genetic services, including patient-directed models. Because access to services continues to be a barrier for those from minority racial and ethnic groups and rural areas, examining responses to different delivery models across population subgroups is essential. This study will employ an implementation science framework to test a replicable EHR-based clinical decision support (CDS) infrastructure to: (i) automatically identify unaffected patients from 48 primary care clinics in two healthcare systems, University of Utah and New York University, who qualify for cancer genetic services (Aim 1); and (ii) compare two models of genetic services delivery for 1,920 primary care patients using a randomized trial design with clinic-level randomization (Aims 2 and 3). We hypothesize that the CDS infrastructure will identify additional patients who have not been previously referred (Aim 1) and that uptake of genetic testing (Aim 2) and adherence to management recommendations (Aim 3) will be equivalent between the models. To address Aim 1, we will evaluate whether the CDS approach identifies patients who have not previously been referred, and whether this varies by race/ethnicity and rurality. To address Aim 2, we will compare: a patient-directed model in which those identified by the CDS infrastructure as meeting testing criteria will be informed of their cancer risks, provided with educational resources, and offered the option to select genetic testing through a patient portal to an enhanced standard of care model in which providers and patients are notified through CDS when criteria are met and of the availability of standard of care genetic counseling. We will compare uptake of genetic testing by model and whether this differs by race/ethnicity and rurality. In Aim 3, we will compare the effects of the two delivery models on adherence to recommendations 12 months after return of results, examining differences in effects by race/ethnicity and rurality. Innovative features include implementation of population-based CDS assessment of family history information available in the EHR; comparison of outcomes of patient-directed and enhanced standard of care delivery models; and focus on impact of race/ethnicity and rurality. This highly impactful translational research builds on our unique strengths in cancer genetics, clinical informatics, and population sciences, and addresses issues of immediate clinical significance, including increasing hereditary cancer genetic testing in appropriate patients and improving access for underserved groups.



Publications

Social vulnerability and genetic service utilization among unaffected BRIDGE trial patients with inherited cancer susceptibility.
Authors: Bather J.R. , Goodman M.S. , Harris A. , Del Fiol G. , Hess R. , Wetter D.W. , Chavez-Yenter D. , Zhong L. , Kaiser-Jackson L. , Chambers R. , et al. .
Source: Bmc Cancer, 2025-01-31 00:00:00.0; 25(1), p. 180.
EPub date: 2025-01-31 00:00:00.0.
PMID: 39891096
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Identification of Individuals With Hereditary Cancer Risk Through Multiple Data Sources: A Population-Based Method Using the GARDE Platform and The Utah Population Database.
Authors: Del Fiol G. , Madsen M.J. , Bradshaw R.L. , Newman M.G. , Kaphingst K.A. , Tavtigian S.V. , Camp N.J. .
Source: Jco Clinical Cancer Informatics, 2024 Nov; 8, p. e2400142.
EPub date: 2024-11-21 00:00:00.0.
PMID: 39571109
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Applying theories, models, and frameworks to help genetic counselors and students achieve clinical and professional goals.
Authors: Cragun D. , Victoria L. , Bradbury A.R. , Dean M. , Hamilton J.G. , Katz M.L. , Rahm A.K. , Mack J.W. , Resnicow K. , Kaphingst K.A. .
Source: Journal Of Genetic Counseling, 2024-10-27 00:00:00.0; , .
EPub date: 2024-10-27 00:00:00.0.
PMID: 39462976
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Uptake of Cancer Genetic Services for Chatbot vs Standard-of-Care Delivery Models: The BRIDGE Randomized Clinical Trial.
Authors: Kaphingst K.A. , Kohlmann W.K. , Lorenz Chambers R. , Bather J.R. , Goodman M.S. , Bradshaw R.L. , Chavez-Yenter D. , Colonna S.V. , Espinel W.F. , Everett J.N. , et al. .
Source: Jama Network Open, 2024-09-03 00:00:00.0; 7(9), p. e2432143.
EPub date: 2024-09-03 00:00:00.0.
PMID: 39250153
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Determinants of Breast Cancer Screening Adherence During the COVID-19 Pandemic in a Cohort at Increased Inherited Cancer Risk in the United States.
Authors: Harris A. , Bather J.R. , Kawamoto K. , Fiol G.D. , Bradshaw R.L. , Kaiser-Jackson L. , Monahan R. , Kohlmann W. , Liu F. , Ginsburg O. , et al. .
Source: Cancer Control : Journal Of The Moffitt Cancer Center, 2024 Jan-Dec; 31, p. 10732748241272727.
PMID: 39420801
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Enhanced Family History-Based Algorithms Increase the Identification of Individuals Meeting Criteria for Genetic Testing of Hereditary Cancer Syndromes but Would Not Reduce Disparities on Their Own.
Authors: Bradshaw R.L. , Kawamoto K. , Bather J.R. , Goodman M.S. , Kohlmann W.K. , Chavez-Yenter D. , Volkmar M. , Monahan R. , Kaphingst K.A. , Del Fiol G. .
Source: Journal Of Biomedical Informatics, 2023-12-09 00:00:00.0; , p. 104568.
EPub date: 2023-12-09 00:00:00.0.
PMID: 38081564
Related Citations

Barriers to family history collection among Spanish-speaking primary care patients: a BRIDGE qualitative study.
Authors: Liebermann E. , Taber P. , Vega A.S. , Daly B.M. , Goodman M.S. , Bradshaw R. , Chan P.A. , Chavez-Yenter D. , Hess R. , Kessler C. , et al. .
Source: Pec Innovation, 2022 Dec; 1, .
EPub date: 2022-09-27 00:00:00.0.
PMID: 36532299
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Association of Disparities in Family History and Family Cancer History in the Electronic Health Record With Sex, Race, Hispanic or Latino Ethnicity, and Language Preference in 2 Large US Health Care Systems.
Authors: Chavez-Yenter D. , Goodman M.S. , Chen Y. , Chu X. , Bradshaw R.L. , Lorenz Chambers R. , Chan P.A. , Daly B.M. , Flynn M. , Gammon A. , et al. .
Source: Jama Network Open, 2022-10-03 00:00:00.0; 5(10), p. e2234574.
EPub date: 2022-10-03 00:00:00.0.
PMID: 36194411
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Identifying Patients Who Meet Criteria for Genetic Testing of Hereditary Cancers Based on Structured and Unstructured Family Health History Data in the Electronic Health Record: Natural Language Processing Approach.
Authors: Shi J. , Morgan K.L. , Bradshaw R.L. , Jung S.H. , Kohlmann W. , Kaphingst K.A. , Kawamoto K. , Fiol G.D. .
Source: Jmir Medical Informatics, 2022-08-11 00:00:00.0; 10(8), p. e37842.
EPub date: 2022-08-11 00:00:00.0.
PMID: 35969459
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Motivational interviewing for genetic counseling: A unified framework for persuasive and equipoise conversations.
Authors: Resnicow K. , Delacroix E. , Chen G. , Austin S. , Stoffel E. , Hanson E.N. , Gerido L.H. , Kaphingst K.A. , Yashar B.M. , Marvin M. , et al. .
Source: Journal Of Genetic Counseling, 2022-07-30 00:00:00.0; , .
EPub date: 2022-07-30 00:00:00.0.
PMID: 35906848
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GARDE: a standards-based clinical decision support platform for identifying population health management cohorts.
Authors: Bradshaw R.L. , Kawamoto K. , Kaphingst K.A. , Kohlmann W.K. , Hess R. , Flynn M.C. , Nanjo C.J. , Warner P.B. , Shi J. , Morgan K. , et al. .
Source: Journal Of The American Medical Informatics Association : Jamia, 2022-02-28 00:00:00.0; , .
EPub date: 2022-02-28 00:00:00.0.
PMID: 35224632
Related Citations

Patient Interactions With an Automated Conversational Agent Delivering Pretest Genetics Education: Descriptive Study.
Authors: Chavez-Yenter D. , Kimball K.E. , Kohlmann W. , Lorenz Chambers R. , Bradshaw R.L. , Espinel W.F. , Flynn M. , Gammon A. , Goldberg E. , Hagerty K.J. , et al. .
Source: Journal Of Medical Internet Research, 2021-11-18 00:00:00.0; 23(11), p. e29447.
EPub date: 2021-11-18 00:00:00.0.
PMID: 34792472
Related Citations

Contemporary clinical decision support standards using Health Level Seven International Fast Healthcare Interoperability Resources.
Authors: Strasberg H.R. , Rhodes B. , Del Fiol G. , Jenders R.A. , Haug P.J. , Kawamoto K. .
Source: Journal Of The American Medical Informatics Association : Jamia, 2021-06-08 00:00:00.0; , .
EPub date: 2021-06-08 00:00:00.0.
PMID: 34100949
Related Citations

Comparing models of delivery for cancer genetics services among patients receiving primary care who meet criteria for genetic evaluation in two healthcare systems: BRIDGE randomized controlled trial.
Authors: Kaphingst K.A. , Kohlmann W. , Chambers R.L. , Goodman M.S. , Bradshaw R. , Chan P.A. , Chavez-Yenter D. , Colonna S.V. , Espinel W.F. , Everett J.N. , et al. .
Source: Bmc Health Services Research, 2021-06-02 00:00:00.0; 21(1), p. 542.
EPub date: 2021-06-02 00:00:00.0.
PMID: 34078380
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