The Precision Health Research Program, led by Drs. Caitlin G. Allen and Lori Orlando, applies implementation science methods to develop, deliver, and evaluate precision health and genomic interventions alongside our community partners in the following areas:
- Implementation of genomic medicine
- Population-based genomic screening
- Communication of genomic information
- Workforce development
Projects
- 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, 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. - The Veterans Health Administration of the Department of Veterans Affairs (VA) is the largest and most diverse learning health system (LHS) in the US, caring for more than 9 million patients annually in every state and US territory. A full quarter of VA healthcare enrollees nationally live in HRSA-designated Health Professional Shortage Areas (HPSAs). VA patients also have a greater burden of physical and mental health comorbidities than the general US population. Nonetheless, a focus on performance measurement and improvement has kept the quality of VA care as high or higher than in the private sector. This quality has been achieved by VA’s innovation in implementation science and embodiment of LHS attributes, leveraging its vast clinical electronic health record (EHR) data, robust informatics infrastructure, and patient-centered focus to continually evaluate and improve patient care based on real-time monitoring and feedback. The VA is also a national leader in clinical genomic medicine, including telegenetics, pharmacogenomics, and precision oncology.
VA innovations in genomic medicine have been driven by its LHS ecosystem of data-informed continuous quality improvement (CQI), innovation, and national dissemination of implementation strategies found to be effective at local and regional levels. In this project, VA will bring its national LHS infrastructure and genomic medicine implementation strategies to a network of other genomics-enabled LHS. The network will conduct implementation projects centered on a mainstream model for delivery of genomic medicine that promotes the use of evidence-based, guideline-concordant genetic testing by frontline clinicians. The VA genomics-enabled LHS will contribute to this network effort by 1) identifying and sharing with the network an implementation approach and strategies with high potential for implementation across diverse healthcare systems, including under-resourced settings; 2) proposing three implementation trials for network-wide conduct (pharmacogenomic testing to optimize pharmacotherapy, germline testing to inform cancer treatment, and EHR identification and germline testing to diagnose unrecognized monogenic disease); and 3) working with the network to conduct implementation projects of genomic medicine interventions across a spectrum of clinical conditions and patient characteristics within the VA genomics-enabled LHS and its community, recruiting underserved populations and geographic areas. Through participation in this network, the VA will disseminate its deep LHS expertise to other clinical sites and in turn bring the learnings from the larger network to improve the genomic health care and outcomes of the nation’s military veterans, their families, and communities. - From the earliest recognition of families with a high rate of cancer over 100 years ago, researchers have been focused on the genetic underpinnings of inherited cancers; however, identification remains a significant challenge due to persistent barriers across patient, provider and health system stakeholders, despite recent advances in the development of electronic medical records (EMR) and risk prediction tools that use family health history (FHH) information. Innovations in bioinformatic technology hold great promise in overcoming many of these barriers, particularly with the development of FHH applications that collect and analyze family data, and SMART-FHIR capabilities that can integrate third party apps with the EMR. MeTree, a patient facing risk assessment platform for 23 hereditary cancer syndromes with integrated education and evidence-based clinical decision support, is one such program that served as the backbone of the Implementing Genomics in Practice (IGNITE) network’s FHH clinical utility study, where it demonstrated improvements in the identification of those at risk, yet, also highlighted ongoing challenges particularly around undergoing genetic counseling and testing, and awareness of risk.
We submit that these barriers can be overcome and that we can significantly improve identification and management of those at risk for hereditary cancer syndromes by bringing together a single clinical care model that contains: a patient-facing risk assessment platform integrated into the EMR, automated risk calculation with clinical decision support for patients and physicians for multiple hereditary cancer syndromes, systematic assessment of risk across a variety of clinic settings, guidance and education on family health history, genomics, risk management, and cascade screening, and an implementation sciences framework to allow us to build a novel and scalable clinical care paradigm for hereditary cancer risk assessment and risk management. To do this we will: 1) deploy a care delivery model that will facilitate systematic risk assessment for hereditary cancers in diverse clinical environments (in primary care and cancer care clinics at two different medical centers ) in a randomized controlled trial of 4000 patients; 2) improve access to genetic healthcare providers who provide counseling, testing and follow up management for participants at risk for hereditary cancer syndromes by deploying the care delivery model in the cancer genetic counseling clinics in a randomized controlled trial of 300 patients; and 3) explore the clinical implementation of two potentially potent emerging methods for case ascertainment in hereditary cancer: a) Family engagement with cascade testing after genetic testing and b) Cancer patients with germline variants identified by clinical tumor genome sequencing. - 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. - Facilitating the Implementation of Population-based Genomic Screening Across Diverse Populations and Settings (FOCUS): We apply implementation mapping to conduct a needs assessment of population-based genomic screening programs, create an implementation guide (FOCUS toolkit), and evaluate the utility of the implementation guide using a stepped wedge cluster randomized trial design (R01HG013851).
- Scalable Clinical Decision Support for Individualized Cancer Risk Management (GARDE): Evidence supports individualizing cancer screening based on each person’s risk. We propose to enhance and disseminate software that scans electronic health records of target patient populations to: 1) automatically identify those at high risk to develop hereditary cancers according to national cancer guidelines, and 2) reach out to patients via automated “chatbots” offering patient education and the opportunity to receive at home genetic testing for hereditary cancers. Through wide dissemination, the GARDE platform has the potential to enable evidence-based, individualized cancer screening to reduce cancer burden (5U24CA274582-02).
- PaRtnEring to build understanding oF gEnomics Responsibly (PREFER) CHW Genomics Research Education Program (PREFER CHW): The PREFER CHW program is designed to fill the gap in available resources to train CHWs in basic competencies related to genomics. We are working with CHW training programs in North Carolina, South Carolina, Tennessee, and Mississippi to develop and implement the program (1R25HG013479-01).
- Precision Public Health Network: Established in 2019, the Precision Public Health Network is made of hundreds of early-stage investigators focused on precision health research. We provide training from leaders in the field and develop collaborations to advance precision health research. We host conferences as part of this network (R13CA261073).
