Education and electronic medical records and genomics network, challenges, and lessons learned from a large-scale clinical trial using polygenic risk scores.

Polygenic risk scores (PRS) have potential to improve health care by identifying individuals that have elevated risk for common complex conditions. Use of PRS in clinical practice, however, requires careful assessment of the needs and capabilities of patients, providers, and health care systems. The electronic Medical Records and Genomics (eMERGE) network is conducting a collaborative study which will return PRS to 25,000 pediatric and adult participants. All participants will receive a risk report, potentially classifying them as high risk (∼2-10% per condition) for 1 or more of 10 conditions based on PRS. The study population is enriched by participants from racial and ethnic minority populations, underserved populations, and populations who experience poorer medical outcomes. All 10 eMERGE clinical sites conducted focus groups, interviews, and/or surveys to understand educational needs among key stakeholders-participants, providers, and/or study staff. Together, these studies highlighted the need for tools that address the perceived benefit/value of PRS, types of education/support needed, accessibility, and PRS-related knowledge and understanding. Based on findings from these preliminary studies, the network harmonized training initiatives and formal/informal educational resources. This paper summarizes eMERGE's collective approach to assessing educational needs and developing educational approaches for primary stakeholders. It discusses challenges encountered and solutions provided.

Returning integrated genomic risk and clinical recommendations: The eMERGE study.

PURPOSE: Assessing the risk of common, complex diseases requires consideration of clinical risk factors as well as monogenic and polygenic risks, which in turn may be reflected in family history. Returning risks to individuals and providers may influence preventive care or use of prophylactic therapies for those individuals at high genetic risk. METHODS: To enable integrated genetic risk assessment, the eMERGE (electronic MEdical Records and GEnomics) network is enrolling 25,000 diverse individuals in a prospective cohort study across 10 sites. The network developed methods to return cross-ancestry polygenic risk scores, monogenic risks, family history, and clinical risk assessments via a genome-informed risk assessment (GIRA) report and will assess uptake of care recommendations after return of results. RESULTS: GIRAs include summary care recommendations for 11 conditions, education pages, and clinical laboratory reports. The return of high-risk GIRA to individuals and providers includes guidelines for care and lifestyle recommendations. Assembling the GIRA required infrastructure and workflows for ingesting and presenting content from multiple sources. Recruitment began in February 2022. CONCLUSION: Return of a novel report for communicating monogenic, polygenic, and family history-based risk factors will inform the benefits of integrated genetic risk assessment for routine health care.

A Cluster Randomized Trial of a Family Health History Platform to Identify and Manage Patients at Increased Risk for Colorectal Cancer.

BACKGROUND: Obtaining comprehensive family health history (FHH) to inform colorectal cancer (CRC) risk management in primary care settings is challenging. OBJECTIVE: To examine the effectiveness of a patient-facing FHH platform to identify and manage patients at increased CRC risk. DESIGN: Two-site, two-arm, cluster-randomized, implementation-effectiveness trial with primary care providers (PCPs) randomized to immediate intervention versus wait-list control. PARTICIPANTS: PCPs treating patients at least one half-day per week; patients aged 40-64 with no medical conditions that increased CRC risk. INTERVENTIONS: Immediate-arm patients entered their FHH into a web-based platform that provided risk assessment and guideline-driven decision support; wait-list control patients did so 12 months later. MAIN MEASURES: McNemar's test examined differences between the platform and electronic medical record (EMR) in rates of increased risk documentation. General estimating equations using logistic regression models compared arms in risk-concordant provider actions and patient screening test completion. Referral for genetic consultation was analyzed descriptively. KEY RESULTS: Seventeen PCPs were randomized to each arm. Patients (n = 252 immediate, n = 253 control) averaged 51.4 (SD = 7.2) years, with 83% assigned male at birth, 58% White persons, and 33% Black persons. The percentage of patients identified as increased risk for CRC was greater with the platform (9.9%) versus EMR (5.2%), difference = 4.8% (95% CI: 2.6%, 6.9%), p < .0001. There was no difference in PCP risk-concordant action [odds ratio (OR) = 0.7, 95% CI (0.4, 1.2; p = 0.16)]. Among 177 patients with a risk-concordant screening test ordered, there was no difference in test completion, OR = 0.8 [0.5,1.3]; p = 0.36. Of 50 patients identified by the platform as increased risk, 78.6% immediate and 68.2% control patients received a recommendation for genetic consultation, of which only one in each arm had a referral placed. CONCLUSIONS: FHH tools could accurately assess and document the clinical needs of patients at increased risk for CRC. Barriers to acting on those recommendations warrant further exploration. TRIAL REGISTRATION NUMBER: ClinicalTrials.gov NCT02247336 https://clinicaltrials.gov/ct2/show/NCT02247336.

Does genetic testing offer utility as a supplement to traditional family health history intake for inherited disease risk?

CONTENT: This study examines the potential utility of genetic testing as a supplement to family health history to screen for increased risk of inherited disease. Medical conditions are often misreported or misunderstood, especially those related to different forms of cardiac disease (arrhythmias vs. structural heart disease vs. coronary artery disease), female organ cancers (uterine vs. ovarian vs. cervical), and type of cancer (differentiating primary cancer from metastases to other organs). While these nuances appear subtle, they can dramatically alter medical management. For example, different types of cardiac failure (structural, arrhythmia, and coronary artery disease) have inherited forms that are managed with vastly different approaches. METHODS: Using a dataset of over 6,200 individuals who underwent genetic screening, we compared the ability of genetic testing and traditional family health history to identify increased risk of inherited disease. A further, in-depth qualitative study of individuals for whom risk identified through each method was discordant, explored whether this discordance could be addressed through changes in family health history intake. FINDINGS: Of 90 individuals for whom genetic testing indicated significant increased risk for inherited disease, two-thirds (66%) had no corroborating family health history. Specifically, we identify cardiomyopathy, arrhythmia, and malignant hyperthermia as conditions for which discordance between genetic testing and traditional family health history was greatest, and familial hypercholesterolaemia, Lynch syndrome, and hereditary breast and ovarian cancer as conditions for which greater concordance existed. CONCLUSION: We conclude that genetic testing offers utility as a supplement to traditional family health history intake over certain conditions.

Critical components of genomic medicine practice for non-genetics healthcare professionals: Genetic counselors' perspectives and implications for medical education.

Genetic services are increasingly provided by non-genetics healthcare professionals (NGHPs) with minimal formal training in genetics/genomics. Research demonstrates gaps in knowledge and clinical practices in genetics/genomics among NGHPs, but there is a lack of consensus on the specific knowledge needed by NGHPs to effectively provide genetic services. As clinical genetics professionals, genetic counselors (GCs) have insight into the critical components of genetics/genomics knowledge and practices needed by NGHPs. This study explored GCs' beliefs regarding whether NGHPs should provide genetic services and identified GCs' perceptions of the components of knowledge and clinical practice in genetics/genomics that are most critical for NGHPs providing genetic services. Two hundred and forty GCs completed an online quantitative survey with 17 participating in a follow-up qualitative interview. Descriptive statistics and cross-comparisons were generated for survey data. Interview data were analyzed using an inductive qualitative method for cross-case analysis. Most GCs disagreed with NGHPs providing genetic services, but beliefs varied widely, ranging from disagreement due to perceived gaps in knowledge or clinical skills to acceptance of NGHPs providing genetic services due to limited access to genetics professionals. Across survey and interview data, GCs endorsed the interpretation of genetic test results, understanding implications of results, collaboration with genetics professionals, knowledge of the risks and benefits to testing, and recognizing indications for genetic testing as critical components of knowledge and clinical practice for NGHPs. Several recommendations for improving the provision of genetic services were provided by respondents including educating NGHPs to provide genetic services through case-based continuing medical education and increasing collaboration between NGHPs and genetics professionals. As GCs are healthcare providers with experience and vested interests in educating NGHPs, their perspectives can help inform the creation of continuing medical education to ensure patients' access to high-quality genomic medicine care from providers of varying backgrounds.

Conducting inclusive research in genetics for transgender, gender-diverse, and sex-diverse individuals: Case analyses and recommendations from a clinical genomics study.

A person's phenotypic sex (i.e., endogenous expression of primary, secondary, and endocrinological sex characteristics) can impact crucial aspects of genetic assessment and resulting clinical care recommendations. In studies with genetics components, it is critical to collect phenotypic sex, information about current organ/tissue inventory and hormonal milieu, and gender identity. If researchers do not carefully construct data models, transgender, gender diverse, and sex diverse (TGSD) individuals may be given inappropriate care recommendations and/or be subjected to misgendering, inflicting medical and psychosocial harms. The recognized need for an inclusive care experience should not be limited to clinical practice but should extend to the research setting, where researchers must build an inclusive experience for TGSD participants. Here, we review three TGSD participants in the Family History and Cancer Risk Study (FOREST) to critically evaluate sex- and gender-related survey measures and associated data models in a study seeking to identify patients at risk for hereditary cancer syndromes. Furthermore, we leverage these participants' responses to sex- and gender identity-related questions in FOREST to inform needed changes to the FOREST data model and to make recommendations for TGSD-inclusive genetics research design, data models, and processes.

The Genomic Medicine Integrative Research Framework: A Conceptual Framework for Conducting Genomic Medicine Research.

Conceptual frameworks are useful in research because they can highlight priority research domains, inform decisions about interventions, identify outcomes and factors to measure, and display how factors might relate to each other to generate and test hypotheses. Discovery, translational, and implementation research are all critical to the overall mission of genomic medicine and prevention, but they have yet to be organized into a unified conceptual framework. To fill this gap, our diverse team collaborated to develop the Genomic Medicine Integrative Research (GMIR) Framework, a simple but comprehensive tool to aid the genomics community in developing research questions, strategies, and measures and in integrating genomic medicine and prevention into clinical practice. Here we present the GMIR Framework and its development, along with examples of its use for research development, demonstrating how we applied it to select and harmonize measures for use across diverse genomic medicine implementation projects. Researchers can utilize the GMIR Framework for their own research, collaborative investigations, and clinical implementation efforts; clinicians can use it to establish and evaluate programs; and all stakeholders can use it to help allocate resources and make sure that the full complexity of etiology is included in research and program design, development, and evaluation.

Implementation-effectiveness trial of systematic family health history based risk assessment and impact on clinical disease prevention and surveillance activities.

BACKGROUND: Systematically assessing disease risk can improve population health by identifying those eligible for enhanced prevention/screening strategies. This study aims to determine the clinical impact of a systematic risk assessment in diverse primary care populations. METHODS: Hybrid implementation-effectiveness trial of a family health history-based health risk assessment (HRA) tied to risk-based guideline recommendations enrolling from 2014-2017 with 12 months of post-intervention survey data and 24 months of electronic medical record (EMR) data capture. SETTING: 19 primary care clinics at four geographically and culturally diverse U.S. healthcare systems. PARTICIPANTS: any English or Spanish-speaking adult with an upcoming appointment at an enrolling clinic. METHODS: A personal and family health history based HRA with integrated guideline-based clinical decision support (CDS) was completed by each participant prior to their appointment. Risk reports were provided to patients and providers to discuss at their clinical encounter. OUTCOMES: provider and patient discussion and provider uptake (i.e. ordering) and patient uptake (i.e. recommendation completion) of CDS recommendations. MEASURES: patient and provider surveys and EMR data. RESULTS: One thousand eight hundred twenty nine participants (mean age 56.2 [SD13.9], 69.6% female) completed the HRA and had EMR data available for analysis. 762 (41.6%) received a recommendation (29.7% for genetic counseling (GC); 15.2% for enhanced breast/colon cancer screening). Those with recommendations frequently discussed disease risk with their provider (8.7%-38.2% varied by recommendation, p-values ≤ 0.004). In the GC subgroup, provider discussions increased referrals to counseling (44.4% with vs. 5.9% without, P < 0.001). Recommendation uptake was highest for colon cancer screening (provider = 67.9%; patient = 86.8%) and lowest for breast cancer chemoprevention (0%). CONCLUSIONS: Systematic health risk assessment revealed that almost half the population were at increased disease risk based on guidelines. Risk identification resulted in shared discussions between participants and providers but variable clinical action uptake depending upon the recommendation. Understanding the barriers and facilitators to uptake by both patients and providers will be essential for optimizing HRA tools and achieving their promise of improving population health. TRIAL REGISTRATION: Clinicaltrials.gov number NCT01956773 , registered 10/8/2013.

Genomic medicine implementation protocols in the PhenX Toolkit: tools for standardized data collection.

PURPOSE: The PhenX Toolkit ( www.phenxtoolkit.org ), an online catalog of recommended measurement protocols, facilitates cross-study analyses for research with human participants. The PhenX Steering Committee recommended genomic medicine implementation as a new research domain, with the following scope: genomic knowledge and education (both patients and providers); implementation science; changes in management and treatment; return of results; patient outcomes; and ethical, legal, and social issues (ELSI) associated with genomic research. METHODS: A seven-member expert Working Group convened in October 2019 to identify well-established measurement protocols for a new genomic medicine implementation domain and used the established PhenX consensus process to select measurement protocols for inclusion in the PhenX Toolkit. RESULTS: The Working Group recommended 15 measurement protocols for inclusion in the PhenX Toolkit, with priority given to those with empirical evidence supporting validity. Consortia funded by the National Institutes of Health, and particularly the National Human Genome Research Institute, proved critical in identifying protocols with established utility in this research domain, and identified protocols that were developed through a rigorous process for scope elements that lacked formally validated protocols. CONCLUSION: Use of these protocols, which were released in September 2020, can facilitate standard data collection for genomic medicine implementation research.

Establishing the value of genomics in medicine: the IGNITE Pragmatic Trials Network.

PURPOSE: A critical gap in the adoption of genomic medicine into medical practice is the need for the rigorous evaluation of the utility of genomic medicine interventions. METHODS: The Implementing Genomics in Practice Pragmatic Trials Network (IGNITE PTN) was formed in 2018 to measure the clinical utility and cost-effectiveness of genomic medicine interventions, to assess approaches for real-world application of genomic medicine in diverse clinical settings, and to produce generalizable knowledge on clinical trials using genomic interventions. Five clinical sites and a coordinating center evaluated trial proposals and developed working groups to enable their implementation. RESULTS: Two pragmatic clinical trials (PCTs) have been initiated, one evaluating genetic risk APOL1 variants in African Americans in the management of their hypertension, and the other to evaluate the use of pharmacogenetic testing for medications to manage acute and chronic pain as well as depression. CONCLUSION: IGNITE PTN is a network that carries out PCTs in genomic medicine; it is focused on diversity and inclusion of underrepresented minority trial participants; it uses electronic health records and clinical decision support to deliver the interventions. IGNITE PTN will develop the evidence to support (or oppose) the adoption of genomic medicine interventions by patients, providers, and payers.

Clinical implementation of an oncology-specific family health history risk assessment tool.

BACKGROUND: The presence of hereditary cancer syndromes in cancer patients can have an impact on current clinical care and post-treatment prevention and surveillance measures. Several barriers inhibit identification of hereditary cancer syndromes in routine practice. This paper describes the impact of using a patient-facing family health history risk assessment platform on the identification and referral of breast cancer patients to genetic counselling services. METHODS: This was a hybrid implementation-effectiveness study completed in breast cancer clinics. English-literate patients not previously referred for genetic counselling and/or gone through genetic testing were offered enrollment. Consented participants were provided educational materials on family health history collection, entered their family health history into the platform and completed a satisfaction survey. Upon completion, participants and their clinicians were given personalized risk reports. Chart abstraction was done to identify actions taken by patients, providers and genetic counsellors. RESULTS: Of 195 patients approached, 102 consented and completed the study (mean age 55.7, 100 % women). Sixty-six (65 %) met guideline criteria for genetic counseling of which 24 (36 %) were referred for genetic counseling. Of those referred, 13 (54 %) participants attended and eight (33 %) completed genetic testing. On multivariate logistic regression, referral was not associated with age, cancer stage, or race but was associated with clinical provider (p = 0.041). Most providers (71 %) had higher referral rates during the study compared to prior. The majority of participants found the experience useful (84 %), were more aware of their health risks (83 %), and were likely to recommend using a patient-facing platform to others (69 %). CONCLUSIONS: 65 % of patients attending breast cancer clinics in this study are at-risk for hereditary conditions based on current guidelines. Using a patient-facing risk assessment platform enhances the ability to identify these patients systematically and with widespread acceptability and recognized value by patients. As only a third of at-risk participants received referrals for genetic counseling, further understanding barriers to referral is needed to optimize hereditary risk assessment in oncology practices. TRIAL REGISTRATION: NIH Clinical Trials registry, NCT04639934 . Registered Nov 23, 2020 -- Retrospectively registered.

Family health history: underused for actionable risk assessment.

Family health history (FHH) is the most useful means of assessing risk for common chronic diseases. The odds ratio for risk of developing disease with a positive FHH is frequently greater than 2, and actions can be taken to mitigate risk by adhering to screening guidelines, genetic counselling, genetic risk testing, and other screening methods. Challenges to the routine acquisition of FHH include constraints on provider time to collect data and the difficulty in accessing risk calculators. Disease-specific and broader risk assessment software platforms have been developed, many with clinical decision support and informatics interoperability, but few access patient information directly. Software that allows integration of FHH with the electronic medical record and clinical decision support capabilities has provided solutions to many of these challenges. Patient facing, electronic medical record, and web-enabled FHH platforms have been developed, and can provide greater identification of risk compared with conventional FHH ascertainment in primary care. FHH, along with cascade screening, can be an important component of population health management approaches to overall reduction of risk.

Building evidence and measuring clinical outcomes for genomic medicine.

Human genomic sequencing has potential diagnostic, prognostic, and therapeutic value across a wide breadth of clinical disciplines. One barrier to widespread adoption is the paucity of evidence for improved outcomes in patients who do not already have an indication for more focused testing. In this Series paper, we review clinical outcome studies in genomic medicine and discuss the important features and key challenges to building evidence for next generation sequencing in the context of routine patient care.

Correction: Developing a common framework for evaluating the implementation of genomic medicine interventions in clinical care: the IGNITE Network's Common Measures Working Group.

An amendment to this paper has been published and can be accessed via a link at the top of the paper.

Correction: Opportunities to implement a sustainable genomic medicine program: lessons learned from the IGNITE Network.

An amendment to this paper has been published and can be accessed via a link at the top of the paper.

At the intersection of precision medicine and population health: an implementation-effectiveness study of family health history based systematic risk assessment in primary care.

BACKGROUND: Risk assessment is a precision medicine technique that can be used to enhance population health when applied to prevention. Several barriers limit the uptake of risk assessment in health care systems; and little is known about the potential impact that adoption of systematic risk assessment for screening and prevention in the primary care population might have. Here we present results of a first of its kind multi-institutional study of a precision medicine tool for systematic risk assessment. METHODS: We undertook an implementation-effectiveness trial of systematic risk assessment of primary care patients in 19 primary care clinics at four geographically and culturally diverse healthcare systems. All adult English or Spanish speaking patients were invited to enter personal and family health history data into MeTree, a patient-facing family health history driven risk assessment program, for 27 medical conditions. Risk assessment recommendations followed evidence-based guidelines for identifying and managing those at increased disease risk. RESULTS: One thousand eight hundred eighty-nine participants completed MeTree, entering information on N = 25,967 individuals. Mean relatives entered = 13.7 (SD 7.9), range 7-74. N = 1443 (76.4%) participants received increased risk recommendations: 597 (31.6%) for monogenic hereditary conditions, 508 (26.9%) for familial-level risk, and 1056 (56.1%) for risk of a common chronic disease. There were 6617 recommendations given across the 1443 participants. In multivariate analysis, only the total number of relatives entered was significantly associated with receiving a recommendation. CONCLUSIONS: A significant percentage of the general primary care population meet criteria for more intensive risk management. In particular 46% for monogenic hereditary and familial level disease risk. Adopting strategies to facilitate systematic risk assessment in primary care could have a significant impact on populations within the U.S. and even beyond. TRIAL REGISTRATION: Clinicaltrials.gov number NCT01956773 , registered 10/8/2013.

Implementation, adoption, and utility of family health history risk assessment in diverse care settings: evaluating implementation processes and impact with an implementation framework.

PURPOSE: This paper describes the implementation outcomes associated with integrating a family health history-based risk assessment and clinical decision support platform within primary care clinics at four diverse healthcare systems. METHODS: A type III hybrid implementation-effectiveness trial. Uptake and implementation processes were evaluated using the Reach, Effectiveness, Adoption, Implementation, and Maintenance (RE-AIM) framework. RESULTS: One hundred (58%) primary care providers and 2514 (7.8%) adult patients enrolled. Enrolled patients were 69% female, 22% minority, and 32% Medicare/Medicaid. Compared with their respective clinic's population, patient-participants were more likely to be female (69 vs. 59%), older (mean age 57 vs. 49), and Caucasian (88 vs. 69%) (all p values <0.001). Female (81.3% of females vs. 78.5% of males, p value = 0.018) and Caucasian (Caucasians 90.4% vs. minority 84.1%, p value = 0.02) patient-participants were more likely to complete the study once enrolled. Patient-participant survey responses indicated MeTree was easy to use (95%), and patient-participants would recommend it to family/friends (91%). Minorities and those with less education reported greatest benefit. Enrolled providers reflected demographics of underlying provider population. CONCLUSION: Family health history-based risk assessment can be effectively implemented in diverse primary care settings and can effectively engage patients and providers. Future research should focus on finding better ways to engage young adults, males, and minorities in preventive healthcare.

Opportunities to implement a sustainable genomic medicine program: lessons learned from the IGNITE Network.

PURPOSE: While there is growing scientific evidence for and significant advances in the use of genomic technologies in medicine, there is a significant lag in the clinical adoption and sustainability of genomic medicine. Here we describe the findings from the National Human Genome Research Institute's (NHGRI) Implementing GeNomics In pracTicE (IGNITE) Network in identifying key constructs, opportunities, and challenges associated with driving sustainability of genomic medicine in clinical practice. METHODS: Network members and affiliates were surveyed to identify key drivers associated with implementing and sustaining a genomic medicine program. Tallied results were used to develop and weigh key constructs/drivers required to support sustainability of genomic medicine programs. RESULTS: The top three driver-stakeholder dyads were (1) genomic training for providers, (2) genomic clinical decision support (CDS) tools embedded in the electronic health record (EHR), and (3) third party reimbursement for genomic testing. CONCLUSION: Priorities may differ depending on healthcare systems when comparing the current state of key drivers versus projected needs for supporting genomic medicine sustainability. Thus we provide gap-filling guidance based on IGNITE members' experiences. Although results are limited to findings from the IGNITE network, their implementation, scientific, and clinical experience may be used as a road map by others considering implementing genomic medicine programs.

Correction: Opportunities to implement a sustainable genomic medicine program: lessons learned from the IGNITE Network.

The original version of this Article contained an error in the spelling of the author Geoffrey S. Ginsburg, which was incorrectly given as Geoffrey Ginsburg. This has now been corrected in both the PDF and HTML versions of the Article.

Qualitative study of system-level factors related to genomic implementation.

PURPOSE: Research on genomic medicine integration has focused on applications at the individual level, with less attention paid to implementation within clinical settings. Therefore, we conducted a qualitative study using the Consolidated Framework for Implementation Research (CFIR) to identify system-level factors that played a role in implementation of genomic medicine within Implementing GeNomics In PracTicE (IGNITE) Network projects. METHODS: Up to four study personnel, including principal investigators and study coordinators from each of six IGNITE projects, were interviewed using a semistructured interview guide that asked interviewees to describe study site(s), progress at each site, and factors facilitating or impeding project implementation. Interviews were coded following CFIR inner-setting constructs. RESULTS: Key barriers included (1) limitations in integrating genomic data and clinical decision support tools into electronic health records, (2) physician reluctance toward genomic research participation and clinical implementation due to a limited evidence base, (3) inadequate reimbursement for genomic medicine, (4) communication among and between investigators and clinicians, and (5) lack of clinical and leadership engagement. CONCLUSION: Implementation of genomic medicine is hindered by several system-level barriers to both research and practice. Addressing these barriers may serve as important facilitators for studying and implementing genomics in practice.