In this paper, we review the evolution of the field of public health genomics in the United States in the past two decades. Public health genomics focuses on effective and responsible translation of genomic science into population health benefits. We discuss the relationship of the field to the core public health functions and essential services, review its evidentiary foundation, and provide examples of current US public health priorities and applications. We cite examples of publications to illustrate how Genetics in Medicine reflected the evolution of the field. We also reflect on how public-health genomics is contributing to the emergence of "precision public health" with near-term opportunities offered by the US Precision Medicine (AllofUs) Initiative.GENETICS in MEDICINE advance online publication, 14 December 2017; doi:10.1038/gim.2017.211.

Purpose We examined 12-year trends in BRCA testing rates and costs in the context of clinical guidelines, national policies, and other factors. Methods We estimated trends in BRCA testing rates and costs from 2003 to 2014 for women aged 18-64 years using private claims data and publicly reported revenues from the primary BRCA testing provider. Results The percentage of women with zero out-of-pocket payments for BRCA testing increased during 2013-2014, after 7 years of general decline, coinciding with a clarification of Affordable Care Act coverage of BRCA genetic testing. Beginning in 2007, family history accounted for an increasing proportion of women with BRCA tests compared with personal history, coinciding with BRCA testing guidelines for primary care settings and direct-to-consumer advertising campaigns. During 2013-2014, BRCA testing rates based on claims grew at a faster rate than revenues, following 3 years of similar growth, consistent with increased marketplace competition. In 2013, BRCA testing rates based on claims increased 57%, compared with 11% average annual increases over the preceding 3 years, coinciding with celebrity publicity. Conclusion The observed trends in BRCA testing rates and costs are consistent with possible effects of several factors, including the Affordable Care Act, clinical guidelines and celebrity publicity. GENETICS in MEDICINE advance online publication, 21 September 2017; doi:10.1038/gim.2017.118.

PROBLEM/CONDITION: Genetic testing for breast cancer 1 (BRCA1) and breast cancer 2 (BRCA2) gene mutations can identify women at increased risk for breast and ovarian cancer. These testing results can be used to select preventive interventions and guide treatment. Differences between nonmetropolitan and metropolitan populations in rates of BRCA testing and receipt of preventive interventions after testing have not previously been examined. PERIOD COVERED: 2009-2014. DESCRIPTION OF SYSTEM: Medical claims data from Truven Health Analytics MarketScan Commercial Claims and Encounters databases were used to estimate rates of BRCA testing and receipt of preventive interventions after BRCA testing among women aged 18-64 years with employer-sponsored health insurance in metropolitan and nonmetropolitan areas of the United States, both nationally and regionally. RESULTS: From 2009 to 2014, BRCA testing rates per 100,000 women aged 18-64 years with employer-sponsored health insurance increased 2.3 times (102.7 to 237.8) in metropolitan areas and 3.0 times (64.8 to 191.3) in nonmetropolitan areas. The relative difference in BRCA testing rates between metropolitan and nonmetropolitan areas decreased from 37% in 2009 (102.7 versus 64.8) to 20% in 2014 (237.8 versus 191.3). The relative difference in BRCA testing rates between metropolitan and nonmetropolitan areas decreased more over time in younger women than in older women and decreased in all regions except the West. Receipt of preventive services 90 days after BRCA testing in metropolitan versus nonmetropolitan areas throughout the period varied by service: the percentage of women who received a mastectomy was similar, the percentage of women who received magnetic resonance imaging of the breast was lower in nonmetropolitan areas (as low as 5.8% in 2014 to as high as 8.2% in 2011) than metropolitan areas (as low as 7.3% in 2014 to as high as 10.3% in 2011), and the percentage of women who received mammography was lower in nonmetropolitan areas in earlier years but was similar in later years. INTERPRETATION: Possible explanations for the 47% decrease in the relative difference in BRCA testing rates over the study period include increased access to genetic services in nonmetropolitan areas and increased demand nationally as a result of publicity. The relative differences in metropolitan and nonmetropolitan BRCA testing rates were smaller among women at younger ages compared with older ages. PUBLIC HEALTH ACTION: Improved data sources and surveillance tools are needed to gather comprehensive data on BRCA testing in the United States, monitor adherence to evidence-based guidelines for BRCA testing, and assess receipt of preventive interventions for women with BRCA mutations. Programs can build on the recent decrease in geographic disparities in receipt of BRCA testing while simultaneously educating the public and health care providers about U.S. Preventive Services Task Force recommendations and other clinical guidelines for BRCA testing and counseling.

Should diagnoses, and corresponding changes in disease management, be sufficient demonstration of clinical utility, even in the absence of evidence for improved clinical outcomes? This question is posed to the health-care payer community in a recent American College of Medical Genetics and Genomics (ACMG) position statement on the clinical utility of genetic and genomic services.1 Affirmative arguments could be drawn from examples of individually rare, highly penetrant, single-gene disorders. We fully support the ACMG’s call for inclusion of individual, familial, and societal levels of impact in the evaluation of testing. Nevertheless, broadening the definition of clinical utility for all cases may be less helpful in the evaluation of genetic tests than promoting more context-dependent and transparent decision-making, with less rigidity and dogmatic adherence to artificial logic models.

PURPOSE: We developed, implemented, and evaluated a multicomponent cancer genetics toolkit designed to improve recognition and appropriate referral of individuals at risk for hereditary cancer syndromes. METHODS: We evaluated toolkit implementation in the women's clinics at a large Veterans Administration medical center using mixed methods, including pre-post semistructured interviews, clinician surveys, and chart reviews, and during implementation, monthly tracking of genetic consultation requests and use of a reminder in the electronic health record. We randomly sampled 10% of progress notes 6 months before (n = 139) and 18 months during implementation (n = 677). RESULTS: The toolkit increased cancer family history documentation by almost 10% (26.6% pre- and 36.3% postimplementation). The reminder was a key component of the toolkit; when used, it was associated with a twofold increase in cancer family history documentation (odds ratio = 2.09; 95% confidence interval: 1.39-3.15), and the history was more complete. Patients whose clinicians completed the reminder were twice as likely to be referred for genetic consultation (4.1-9.6%, P < 0.0001). CONCLUSION: A multicomponent approach to the systematic collection and use of family history by primary-care clinicians increased access to genetic services.

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.

As evidence accumulates on the use of genomic tests and other health-related applications of genomic technologies, decision makers may increasingly seek support in identifying which applications have sufficiently robust evidence to suggest they might be considered for action. As an interim working process to provide such support, we developed a horizon-scanning method that assigns genomic applications to tiers defined by availability of synthesized evidence. We illustrate an application of the method to pharmacogenomics tests.

For decades, newborn screening was the only public health program in the US focused on reducing morbidity, mortality and disability in people affected by genetic conditions. The landscape has changed, however, as evidence-based recommendations are now available for several other genomic applications that can save lives now in the US. Many more such applications are expected to emerge in the next decade. An action plan, based on evidence, provides the impetus for a new paradigm for public health practice in genomics across the lifespan using established multilevel processes as a guide. These include policy interventions, education, clinical interventions, and surveillance. Applying what we know today in hereditary breast/ovarian cancer, Lynch syndrome and familial hypercholesterolemia has the potential to affect thousands of people in the US population every year. Enhanced partnerships between genetic and nongenetic providers of clinical medicine and public health are needed to overcome the challenges for implementing genomic medicine applications both now and in the future.

A decade after the sequencing of the human genome, the National Human Genome Research Institute announced a strategic plan for genomic medicine. It calls for evaluating the structure and biology of genomes, understanding the biology of disease, advancing the science of medicine, and improving the effectiveness of health care. Fulfilling the promise of genomics urgently requires a population perspective to complement the bench-to-bedside model of translation. A population approach should assess the contribution of genomics to health in the context of social and environmental determinants of disease; evaluate genomic applications that may improve health care; design strategies for integrating genomics into practice; address ethical, legal, and social issues; and measure the population health impact of new technologies. (Am J Public Health. Published online ahead of print November 17, 2011: e5-e8. doi:10.2105/AJPH.2011.300299).

OBJECTIVE: To test the association of family history of diabetes with the adoption of diabetes risk-reducing behaviors and whether this association is strengthened by physician advice or commonly known factors associated with diabetes risk. RESEARCH DESIGN AND METHODS: We used cross-sectional data from the 2005-2008 National Health and Nutrition Examination Survey (NHANES) to examine the effects of family history of diabetes on the adoption of selected risk-reducing behaviors in 8,598 adults (aged ≥20 years) without diabetes. We used multiple logistic regression to model three risk reduction behaviors (controlling or losing weight, increasing physical activity, and reducing the amount of dietary fat or calories) with family history of diabetes. RESULTS: Overall, 36.2% of U.S. adults without diabetes had a family history of diabetes. Among them, ~39.8% reported receiving advice from a physician during the past year regarding any of the three selected behaviors compared with 29.2% of participants with no family history (P < 0.01). In univariate analysis, adults with a family history of diabetes were more likely to perform these risk-reducing behaviors compared with adults without a family history. Physician advice was strongly associated with each of the behavioral changes (P < 0.01), and this did not differ by family history of diabetes. CONCLUSIONS: Familial risk for diabetes and physician advice both independently influence the adoption of diabetes risk-reducing behaviors. However, fewer than half of participants with familial risk reported receiving physician advice for adopting these behaviors.

In a recent commentary in Clinical Pharmacology and Therapeutics, Altman1 declares that the implementation of pharmacogenomics (PGx) “requires that we separate it from other elements of genomic medicine.” He argues that PGx tests “need only reach reasonable expectations of noninferiority (compared with current prescribing practices) to merit use.” In his view, the implementation of PGx is less challenging than the use of genomics for estimating disease risk and prognosis, because genetic tests for drug response phenotypes offer better explanatory power and less risk for discrimination or misinterpretation. He also believes that cost-benefit analyses for PGx are not necessary because “genotyping is asymptotically approaching no cost” and positive test results are unlikely to lead to “spiraling follow-up test costs.” | We, too, are enthusiastic about the prospects for PGx, but we see no reason why its successful integration into practice should require an exception from the principles of evidence-based medicine. The factors cited above do not distinguish pharmacogenomic tests from other genetic or nongenetic tests used to direct interventions in practice. “Genetic exceptionalism”—the concept that genetic information is unique and requires special protection—was first invoked in relation to health policy issues such as privacy and insurance discrimination. After years of debate, many researchers and practitioners have concluded that genetic information should not be treated differently from other personalized medical information.2 Recently, Evans et al.3 introduced the term “reverse genetic exceptionalism” to describe the premature embrace of genetics in healthcare and disease prevention. The idea that genetic information is different and therefore merits a pass when it comes to evidentiary standards (for example, because it has personal utility4) has been a hotly discussed topic, especially with respect to personal genomic tests sold directly to consumers.5

In spite of accelerating human genome discoveries in a wide variety of diseases of public health significance, the promise of personalized health care and disease prevention based on genomics has lagged behind. In a time of limited resources, public health agencies must continue to focus on implementing programs that can improve health and prevent disease now. Nevertheless, public health has an important and assertive leadership role in addressing the promise and pitfalls of human genomics for population health. Such efforts are needed not only to implement what is known in genomics to improve health but also to reduce potential harm and create the infrastructure needed to derive health benefits in the future.