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
Related Citations
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
Related Citations
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
Related Citations
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
Related Citations
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
Related Citations
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
Related Citations
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
Related Citations
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
Related Citations
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
Related Citations
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
Related Citations