Study Results
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Basic Information
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ACTIVE_NOT_RECRUITING
NA
1868 participants
INTERVENTIONAL
2022-01-01
2025-09-30
Brief Summary
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Detailed Description
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The practice of genetic medicine is changing as genetic discoveries are translated into new tests for an increasing number of health indications. In fact, the prevalence of high-risk individuals who are at risk for hereditary cancer has been rising due to new testing strategies. This has placed enormous pressure on the hospitals and clinics providing care for high-risk patients. Coupled with the healthcare systems need for greater efficiency, the traditional genetic clinic-based practice has become untenable. Barriers and challenges include low numbers of trained genetic workforce, lack of integrated FHH tools for patients and physicians, and long wait times for available clinic appointments. Further, while cancer syndromes are seen across all groups, gaps in care exist as underserved populations are often not recognized and referred for care.
Investigators propose that these barriers can be overcome by using innovations in informatics and telecommunications to develop a sustainable and scalable genomic care delivery model that can be replicated by other health systems. Such a program would need to integrate FHH applications that collect and analyze family data, SMART-on-FHIR capabilities that can link third party apps with the electronic medical record (EMR), and clinical decision support modules to assist providers and patients. MeTree is one such system with all these capabilities -- a validated and flexible patient-facing FHH collection tool that supports SMART-on-FHIR technology. This platform was the backbone of the Implementing Genomics in Practice (IGNITE) network's FHH clinical utility study that showed clear improvements in the quality and quantity of FHH collected in 5 geographically diverse primary care practices. Furthermore, MeTree was highly acceptable to patients and providers, and was able to properly identify participants at risk for 23 hereditary cancer syndromes for genetic counseling referral.
Our re-submission for this Beau Biden Moonshot grant opportunity is based on the hypothesis that an implementation science approach will improve the identification and management of high-risk patients from diverse clinical setting by systematically integrating FHH driven evidence-based guidelines into the EMR. Investigators plan to improve ascertainment of high-risk patients by imbedding MeTree in the workflow of primary and cancer care clinics. This will improve identification for genetic counseling, facilitate patient education about genetic testing, and risk management for at risk patients, as well as facilitate engagement of patients, family members, and providers with telegenetic and telephone counseling options. This collaborative effort from genetic, genomic, biomedical informatic, and implementation science researchers at Vanderbilt University Medical Center (VUMC), Meharry Medical Center (MMC) and Duke University is highly responsive to the five required elements in RFA-CA-19-017. The proposal has the following specific aims:
SA1. Deploy a care delivery model that will facilitate systematic risk assessment for hereditary cancers in diverse clinical environments.
* 4000 participants will be enrolled and randomized to usual care or MeTree FHH risk assessment
* Deploy in academic medical center (VUMC) and a medical center (MMC) that serves underserved populations
* Assess participants perceptions using online survey and qualitative semi-structured interviews
SA2. Improve access to genetic healthcare providers for participants at risk for hereditary cancer syndromes.
* 300 high risk participants in the VUMC Hereditary Cancer Clinic will be enrolled and randomized
* Extend clinic capacity by lessening the need for in-clinic family history collection and basic counseling
* Expand reach of clinic by using telephone and video genetic counseling, referral to specialists
SA3. Explore the feasibility of our care delivery model to improve family engagement for cancer risk assessment
* Participants extend invitations to MeTree's family resource center to share results of genetic tests
* Assist with education and referral needed for cascade testing for pathogenic variants
Conditions
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Study Design
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NA
SINGLE_GROUP
SCREENING
NONE
Study Groups
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High Risk / MeTree
High risk for hereditary cancer and completes the MeTree questionnaire
MeTree Questionnaire
MeTree is a patient driven risk assessment program with Clinical Decision Support (CDS) that enables collection of a three plus generation family health history (FHH) on 128 conditions. CDS is provided in a report with a pedigree and tailored evidence-based guidelines. While patient drive, MeTree also includes a provider-facing report with additional references. These reports promote engagement by both patients and providers and enhance shared decision-making.
MeTree first generates information imported from the participant's EHR record. These data include basic demographic information, any recent lab results, and any listed diseases or conditions from the EHR. Next, MeTree gives the participant an opportunity to fill out a family history tree. The more information the participant provides on their own health and their family member's health, the better MeTree can provide recommendations from current literature.
Interventions
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MeTree Questionnaire
MeTree is a patient driven risk assessment program with Clinical Decision Support (CDS) that enables collection of a three plus generation family health history (FHH) on 128 conditions. CDS is provided in a report with a pedigree and tailored evidence-based guidelines. While patient drive, MeTree also includes a provider-facing report with additional references. These reports promote engagement by both patients and providers and enhance shared decision-making.
MeTree first generates information imported from the participant's EHR record. These data include basic demographic information, any recent lab results, and any listed diseases or conditions from the EHR. Next, MeTree gives the participant an opportunity to fill out a family history tree. The more information the participant provides on their own health and their family member's health, the better MeTree can provide recommendations from current literature.
Eligibility Criteria
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Inclusion Criteria
* Able to read and communicate in English
* Willing to use the Internet
* Currently enrolled in the patient portal, or willing to enroll (VUMC-specific)
Exclusion Criteria
* Diagnosed with a terminal illness
* Unable to speak/read English
* Unable/unwilling to use the Internet
* Previous genetic testing and/or counseling from the VUMC Hereditary Cancer Clinic
18 Years
ALL
Yes
Sponsors
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National Cancer Institute (NCI)
NIH
Vanderbilt University Medical Center
OTHER
Responsible Party
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Georgia Wiesner
Professor of Medicine
Principal Investigators
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Georgia Wiesner, MD
Role: PRINCIPAL_INVESTIGATOR
Vanderbilt University Medical Center
Locations
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Meharry Medical College
Nashville, Tennessee, United States
Vanderbilt University Medical Center
Nashville, Tennessee, United States
Countries
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References
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Mittendorf KF, Bland HT, Andujar J, Celaya-Cobbs N, Edwards C, Gerhart M, Hooker G, Hubert M, Jones SH, Marshall DR, Myers RA, Pratap S, Rosenbloom ST, Sadeghpour A, Wu RR, Orlando LA, Wiesner GL. Family history and cancer risk study (FOREST): A clinical trial assessing electronic patient-directed family history input for identifying patients at risk of hereditary cancer. Contemp Clin Trials. 2025 Jan;148:107714. doi: 10.1016/j.cct.2024.107714. Epub 2024 Oct 10.
Provided Documents
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Document Type: Study Protocol
Document Type: Informed Consent Form
Other Identifiers
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201202
Identifier Type: -
Identifier Source: org_study_id
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