Family health history (FHH), a critical component of genomic medicine that is essential for both identifying individuals at risk for hereditary conditions and for contextualizing results of genetic testing, continues to be broadly underutilized and underappreciated in clinical care. Barriers to adequate data collection and synthesis are numerous and cross all clinical stakeholders: patients, providers, and health systems. Significantly, they include the pervasive view that FHH is unimportant except in select cases and that it rarely contributes to clinical decision making. With this perspective, few providers have been willing to allocate precious time to collect detailed FHHs or to learn the complex algorithms required to synthesize FHH data into actionable care plans. However, in studies of systematic FHH-based risk assessments in unselected populations, 25% of patients meet risk criteria for (actionable) hereditary conditions. FHH-based risk assessment programs have emerged to address these barriers, but as designed do not meet the needs of low literacy, low resource populations. The goal of this proposal is to develop a scalable end-to-end solution for risk assessment and management that meets the needs of low resource settings. Our central hypothesis is that combining FHH- driven risk assessment, a literacy-enhanced interface using voice-to-text response capture (like ?Siri?), family engagement (through social networking platforms for data gather and risk sharing), and a genetic testing delivery system, will create a solution that engages and increases the proportion of diverse patients who are identified as at increased risk, who undergo testing, and, when appropriate, who initiate cascade screening among relatives. In this proposal we will define and deploy this new care delivery model as the ?Genomic medicine Risk Assessment Care for Everyone? (GRACE). To this end we will 1) develop and deploy the model using pre-implementation assessments at clinical sites with highly diverse patient populations to select the most appropriate integration options and pathways for both patients and providers; and 2) perform a randomized implementation-effectiveness pragmatic hybrid trial to assess implementation and effectiveness outcomes relevant to these diverse populations. Outcomes will include reach, uptake, clinical utility, accessibility, genetic testing frequency, genetic testing results, and cost-effectiveness. In addition we will convene an advisory panel of stakeholders from industry (laboratories, insurers), providers, patients, and health system to understand sustainability and address knowledge gaps that will promote access when the trial is over.

Public Health Relevance

Systematic risk assessment in primary care populations is critical to identifying those at increased risk of disease and initiating appropriate preventive care. Currently a high proportion of high risk patients (25%) are going undetected due to barriers affecting both patients and providers. This proposal seeks to address this problem by developing and end to end solution for a family health history based genomic risk assessment model that will meet the needs of diverse populations.

Agency
National Institute of Health (NIH)
Institute
National Human Genome Research Institute (NHGRI)
Type
Research Project--Cooperative Agreements (U01)
Project #
5U01HG010231-02
Application #
9789920
Study Section
Special Emphasis Panel (ZHG1)
Program Officer
Volpi, Simona
Project Start
2018-09-24
Project End
2023-06-30
Budget Start
2019-07-01
Budget End
2020-06-30
Support Year
2
Fiscal Year
2019
Total Cost
Indirect Cost
Name
Duke University
Department
Internal Medicine/Medicine
Type
Schools of Medicine
DUNS #
044387793
City
Durham
State
NC
Country
United States
Zip Code
27705