Closing the gap between knowledge and clinical application: challenges for genomic translation.
ABSTRACT: Despite early predictions and rapid progress in research, the introduction of personal genomics into clinical practice has been slow. Several factors contribute to this translational gap between knowledge and clinical application. The evidence available to support genetic test use is often limited, and implementation of new testing programs can be challenging. In addition, the heterogeneity of genomic risk information points to the need for strategies to select and deliver the information most appropriate for particular clinical needs. Accomplishing these tasks also requires recognition that some expectations for personal genomics are unrealistic, notably expectations concerning the clinical utility of genomic risk assessment for common complex diseases. Efforts are needed to improve the body of evidence addressing clinical outcomes for genomics, apply implementation science to personal genomics, and develop realistic goals for genomic risk assessment. In addition, translational research should emphasize the broader benefits of genomic knowledge, including applications of genomic research that provide clinical benefit outside the context of personal genomic risk.
Project description:The increasing availability of personal genomic tests has led to discussions about the validity and utility of such tests and the balance of benefits and harms. A multidisciplinary workshop was convened by the National Institutes of Health and the Centers for Disease Control and Prevention to review the scientific foundation for using personal genomics in risk assessment and disease prevention and to develop recommendations for targeted research. The clinical validity and utility of personal genomics is a moving target with rapidly developing discoveries but little translation research to close the gap between discoveries and health impact. Workshop participants made recommendations in five domains: (1) developing and applying scientific standards for assessing personal genomic tests; (2) developing and applying a multidisciplinary research agenda, including observational studies and clinical trials to fill knowledge gaps in clinical validity and utility; (3) enhancing credible knowledge synthesis and information dissemination to clinicians and consumers; (4) linking scientific findings to evidence-based recommendations for use of personal genomics; and (5) assessing how the concept of personal utility can affect health benefits, costs, and risks by developing appropriate metrics for evaluation. To fulfill the promise of personal genomics, a rigorous multidisciplinary research agenda is needed.
Project description:PURPOSE:The dizzying pace of genomic discoveries is leading to an increasing number of clinical applications. In this report, we provide a method for horizon scanning and 1 year data on translational research beyond bench to bedside to assess the validity, utility, implementation, and outcomes of such applications. METHODS:We compiled cross-sectional results of ongoing horizon scanning of translational genomic research, conducted between 16 May 2012 and 15 May 2013, based on a weekly, systematic query of PubMed. A set of 505 beyond bench to bedside articles were collected and classified, including 312 original research articles; 123 systematic and other reviews; 38 clinical guidelines, policies, and recommendations; and 32 articles describing tools, decision support, and educational materials. RESULTS:Most articles (62%) addressed a specific genomic test or other health application; almost half of these (n = 180) were related to cancer. We estimate that these publications account for 0.5% of reported human genomics and genetics research during the same time. CONCLUSION:These data provide baseline information to track the evolving knowledge base and gaps in genomic medicine. Continuous horizon scanning of the translational genomics literature is crucial for an evidence-based translation of genomics discoveries into improved health care and disease prevention.
Project description:BACKGROUND:Genomic risk information, based on common genomic susceptibility variants associated with risk of complex diseases such as cancer, may be incorporated into personalised prevention and screening strategies. We aimed to engage with members of the public, who are important stakeholders in this process, to further inform program development and other implementation outcomes such as acceptability and appropriateness. METHODS:Semi-structured interviews were undertaken with 30 participants (aged 24-69?years, 50% female) recruited from a pilot trial in which they received personalised genomic risk information for melanoma. We explored participants' views and attitudes towards offering general personal genomic risk information to the broader population. The data were analysed thematically. RESULTS:Two overarching themes relevant to implementation considerations were identified. Firstly, participants' preferences for accepting an offer of genomic risk information were based on family history, disease incidence and the possibility of prevention. Secondly, participants felt that the processes for offering risk information should be based on individual preferences, triaged according to risk and be supported by a health professional trained in genomics. CONCLUSIONS:Participants felt that offering personal genomic risk information to the general population to inform prevention and early detection recommendations is acceptable, particularly for common, complex conditions such as cancer. Understanding participants' preferences for receiving genomic risk information will assist with communication strategies and health workforce planning. We anticipate that these findings will contribute to the development of implementation strategies for incorporating genomic risk information into routine clinical practice.
Project description:PURPOSE:Implementation science offers methods to evaluate the translation of genomic medicine research into practice. The extent to which the National Institutes of Health (NIH) human genomics grant portfolio includes implementation science is unknown. This brief report's objective is to describe recently funded implementation science studies in genomic medicine in the NIH grant portfolio, and identify remaining gaps. METHODS:We identified investigator-initiated NIH research grants on implementation science in genomic medicine (funding initiated 2012-2016). A codebook was adapted from the literature, three authors coded grants, and descriptive statistics were calculated for each code. RESULTS:Forty-two grants fit the inclusion criteria (~1.75% of investigator-initiated genomics grants). The majority of included grants proposed qualitative and/or quantitative methods with cross-sectional study designs, and described clinical settings and primarily white, non-Hispanic study populations. Most grants were in oncology and examined genetic testing for risk assessment. Finally, grants lacked the use of implementation science frameworks, and most examined uptake of genomic medicine and/or assessed patient-centeredness. CONCLUSION:We identified large gaps in implementation science studies in genomic medicine in the funded NIH portfolio over the past 5 years. To move the genomics field forward, investigator-initiated research grants should employ rigorous implementation science methods within diverse settings and populations.
Project description:BACKGROUND:To implement standardized machine-processable clinical sequencing reports in an electronic health record (EHR) system, the International Organization for Standardization Technical Specification (ISO/TS) 20428 international standard was proposed for a structured template. However, there are no standard implementation guidelines for data items from the proposed standard at the clinical site and no guidelines or references for implementing gene sequencing data results for clinical use. This is a significant challenge for implementation and application of these standards at individual sites. OBJECTIVE:This study examines the field utilization of genetic test reports by designing the Health Level 7 (HL7) Fast Healthcare Interoperability Resources (FHIR) for genomic data elements based on the ISO/TS 20428 standard published as the standard for genomic test reports. The goal of this pilot is to facilitate the reporting and viewing of genomic data for clinical applications. FHIR Genomics resources predominantly focus on transmitting or representing sequencing data, which is of less clinical value. METHODS:In this study, we describe the practical implementation of ISO/TS 20428 using HL7 FHIR Genomics implementation guidance to efficiently deliver the required genomic sequencing results to clinicians through an EHR system. RESULTS:We successfully administered a structured genomic sequencing report in a tertiary hospital in Korea based on international standards. In total, 90 FHIR resources were used. Among 41 resources for the required fields, 26 were reused and 15 were extended. For the optional fields, 28 were reused and 21 were extended. CONCLUSIONS:To share and apply genomic sequencing data in both clinical practice and translational research, it is essential to identify the applicability of the standard-based information system in a practical setting. This prototyping work shows that reporting data from clinical genomics sequencing can be effectively implemented into an EHR system using the existing ISO/TS 20428 standard and FHIR resources.
Project description: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.
Project description:Tracking scientific research publications on the evaluation, utility and implementation of genomic applications is critical for the translation of basic research to impact clinical and population health. In this work, we utilize state-of-the-art machine learning approaches to identify translational research in genomics beyond bench to bedside from the biomedical literature. We apply the convolutional neural networks (CNNs) and support vector machines (SVMs) to the bench/bedside article classification on the weekly manual annotation data of the Public Health Genomics Knowledge Base database. Both classifiers employ salient features to determine the probability of curation-eligible publications, which can effectively reduce the workload of manual triage and curation process. We applied the CNNs and SVMs to an independent test set (n = 400), and the models achieved the F-measure of 0.80 and 0.74, respectively. We further tested the CNNs, which perform better results, on the routine annotation pipeline for 2 weeks and significantly reduced the effort and retrieved more appropriate research articles. Our approaches provide direct insight into the automated curation of genomic translational research beyond bench to bedside. The machine learning classifiers are found to be helpful for annotators to enhance the efficiency of manual curation.
Project description:We describe the development and implementation of a randomized controlled trial to investigate the impact of genomic counseling on a cohort of patients with heart failure (HF) or hypertension (HTN), managed at a large academic medical center, the Ohio State University Wexner Medical Center (OSUWMC). Our study is built upon the existing Coriell Personalized Medicine Collaborative (CPMC®). OSUWMC patient participants with chronic disease (CD) receive eight actionable complex disease and one pharmacogenomic test report through the CPMC® web portal. Participants are randomized to either the in-person post-test genomic counseling-active arm, versus web-based only return of results-control arm. Study-specific surveys measure: (1) change in risk perception; (2) knowledge retention; (3) perceived personal control; (4) health behavior change; and, for the active arm (5), overall satisfaction with genomic counseling. This ongoing partnership has spurred creation of both infrastructure and procedures necessary for the implementation of genomics and genomic counseling in clinical care and clinical research. This included creation of a comprehensive informed consent document and processes for prospective return of actionable results for multiple complex diseases and pharmacogenomics (PGx) through a web portal, and integration of genomic data files and clinical decision support into an EPIC-based electronic medical record. We present this partnership, the infrastructure, genomic counseling approach, and the challenges that arose in the design and conduct of this ongoing trial to inform subsequent collaborative efforts and best genomic counseling practices.
Project description: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.
Project description:Despite significant progress in genomics research over the past decade, we remain years away from the integration of genomics into routine clinical care. As an initial step toward the implementation of genomic-based medicine, we explored primary care patients' ideas about genomic testing for common complex diseases to help develop future patient education materials and interventions to communicate genomic risk information. We conducted a mixed-methods study with participants from a large primary care clinic. Within four focus groups, we used a semi-structured discussion guide and administered brief pre- and post- discussion quantitative surveys to assess participants' interest, attitudes, and preferences related to testing and receipt of test results. Prior to the discussion, moderators presented a plain-language explanation of DNA and genetics, defined "SNP", and highlighted what is known and unknown about the risks associated with testing for SNPs related to colorectal cancer risk. We used the NVIVO 8 software package to analyze the transcripts from the focus group discussions. The majority of participants (75 %) were "very" or "somewhat interested" in receiving information from a colon cancer SNP test, even after learning about and discussing the small and still clinically uncertain change in risk conferred by SNPs. Reported interest in testing was related to degree of risk conferred, personal risk factors, family history, possible implications for managing health /disease prevention and curiosity about genetic results. Most people (85 %) preferred that genetic information be delivered in person by a healthcare or genetics professional rather than through print materials or a computer. These findings suggest that patients may look to genetic counselors, physicians or other healthcare professionals as gatekeepers of predictive genomic risk information.