Health care in the age of genetic medicine

Goal-Directed Health Care: Redefining Health and Health Care in the Era of Value-Based Care

Health care reform efforts have increasingly emphasized payment models that reward value (quality/cost). It seems appropriate, therefore, to examine what we value in health care, and that will require that we examine our definition of health. In spite of admonitions from the World Health Organization and others, our current health care system operates under the assumption that health represents the absence of health problems. While that perspective has led to incredible advances in medical science, it now may be adversely affecting value. Problem-oriented care is clearly one of the drivers of rising costs and it could be adversely affecting the quality of care, depending upon how quality is defined. 

If we redefined health in terms of patient-centered goals, health care could be focused more directly on meaningful outcomes, reducing the number of irrelevant tests and treatments. Greater emphasis would be placed on prevention, meaningful activities, advance directives and personal growth and development. The role of patients within clinician-patient relationships would be elevated, strengthening therapeutic relationships. Reframing health in terms of health-related goals and directing the health care system to help people achieve them, could both improve quality and reduce costs. In the process, it could also make health care less mechanical and more humane.

Ethical, legal, and social implications of incorporating genomic information into electronic health records

The inclusion of genomic data in the electronic health record raises important ethical, legal, and social issues. In this article, we highlight these challenges and discuss potential solutions. We provide a brief background on the current state of electronic health records in the context of genomic medicine, discuss the importance of equitable access to genome-enabled electronic health records, and consider the potential use of electronic health records for improving genomic literacy in patients and providers. We highlight the importance of privacy, access, and security, and of determining which genomic information is included in the electronic health record. Finally, we discuss the challenges of reporting incidental findings, storing and reinterpreting genomic data, and nondocumentation and duty to warn family members at potential genetic risk.

Pairomics, the omics way to mate choice

The core aspects of the biology and evolution of sexual reproduction are reviewed with a focus on the diploid, sexually reproducing, outbreeding, polymorphic, unspecialized, altricial and cultural human species. Human mate choice and pair bonding are viewed as central to individuals' lives and to the evolution of the species, and genetic assistance in reproduction is viewed as a universal human right. Pairomics is defined as an emerging branch of the omics science devoted to the study of mate choice at the genomic level and its consequences for present and future generations. In pairomics, comprehensive genetic information of individual genomes is stored in a database. Computational tools are employed to analyze the mating schemes and rules that govern mating among the members of the database. Mating models and algorithms simulate the outcomes of mating any given genome with each of a number of genomes represented in the database. The analyses and simulations may help to understand mating schemes and their outcomes, and also contribute a new cue to the multicued schemes of mate choice. The scientific, medical, evolutionary, ethical, legal and social implications of pairomics are far reaching. The use of genetic information as a search tool in mate choice may influence our health, lifestyle, behavior and culture. As knowledge on genomics, population genetics and gene-environment interactions, as well as the size of genomic databases expand, so does the ability of pairomics to investigate and predict the consequences of mate choice for the present and future generations.

The future workforce in cancer prevention: advancing discovery, research, and technology

As part of a 2-day conference on October 15 and 16, 2009, a nine-member task force composed of scientists, clinicians, educators, administrators, and students from across the USA was formed to discuss research, discovery, and technology obstacles to progress in cancer prevention and control, specifically those related to the cancer prevention workforce. This article summarizes the task force's findings on the current state of the cancer prevention workforce in this area and its needs for the future. The task force identified two types of barriers impeding the current cancer prevention workforce in research, discovery, and technology from reaching its fullest potential: (1) limited cross-disciplinary research opportunities with underutilization of some disciplines is hampering discovery and research in cancer prevention, and (2) new research avenues are not being investigated because technology development and implementation are lagging. Examples of impediments and desired outcomes are provided in each of these areas. Recommended solutions to these problems are based on the goals of enhancing the current cancer prevention workforce and accelerating the pace of discovery and clinical translation.

Personalized cancer genetics training for personalized medicine: improving community-based healthcare through a genetically literate workforce

PURPOSE

To assess the impact of a multimodal interdisciplinary course on genetic cancer risk assessment and research collaboration for community-based clinicians. Clinicians are increasingly requested to conduct genetic cancer risk assessment, but many are inadequately prepared to provide these services.

METHODS

A prospective analysis of 131 participants (48 physicians, 41 advanced-practice nurses, and 42 genetic counselors) from community settings across the United States. The course was delivered in three phases: distance didactic learning, face-to-face training, and 12 months of web-based professional development activities to support integration of skills into practice. Cancer genetics knowledge, skills, professional self-efficacy, and practice changes were measured at baseline, immediate, and 14 months postcourse.

RESULTS

Knowledge, skills, and self-efficacy scores were significantly different between practice disciplines; however, postscores increased significantly overall and for each discipline (P < 0.001). Fourteen-month practice outcomes reflect significant increases in provision of genetic cancer risk assessment services (P = 0.018), dissemination of cancer prevention information (P = 0.005) and high-risk screening recommendations (P = 0.004) to patients, patient enrollment in research (P = 0.013), and educational outreach about genetic cancer risk assessment (P = 0.003).

CONCLUSIONS

Results support the efficacy of the multimodal course as a tool to develop a genetically literate workforce. Sustained alumni participation in web-based professional development activities has evolved into a distance-mediated community of practice in clinical cancer genetics, modeling the lifelong learning goals envisioned by leading continuing medical education stakeholders.

Public health in the genomic era: will Public Health Genomics contribute to major changes in the prevention of common diseases?

The completion of the Human Genome Project triggered a whole new field of genomic research which is likely to lead to new opportunities for the promotion of population health. As a result, the distinction between genetic and environmental diseases has faded. Presently, genomics and knowledge deriving from systems biology, epigenomics, integrative genomics or genome-environmental interactions give a better insight on the pathophysiology of common diseases. However, it is barely used in the prevention and management of diseases. Together with the boost in the amount of genetic association studies, this demands for appropriate public health actions. The field of Public Health Genomics analyses how genome-based knowledge and technologies can responsibly and effectively be integrated into health services and public policy for the benefit of population health. Environmental exposures interact with the genome to produce health information which may help explain inter-individual differences in health, or disease risk. However today, prospects for concrete applications remain distant. In addition, this information has not been translated into health practice yet. Therefore, evidence-based recommendations are few. The lack of population-based research hampers the evaluation of the impact of genomic applications. Public Health Genomics also evaluates the benefits and risks on a larger scale, including normative, legal, economic and social issues. These new developments are likely to affect all domains of public health and require rethinking the role of genomics in every condition of public health interest. This article aims at providing an introduction to the field of and the ideas behind Public Health Genomics.

Using Alzheimer's disease as a model for genetic risk disclosure: implications for personal genomics

Susceptibility testing for common, complex adult-onset diseases is projected to become more commonplace as the rapid pace of genomic discoveries continues, and evidence regarding the potential benefits and harms of such testing is needed to inform medical practice and health policy. Apolipoprotein E (APOE) testing for risk of Alzheimer's disease (AD) provides a paradigm in which to examine the process and impact of disclosing genetic susceptibility for a prevalent, severe and incurable neurological condition. This review summarizes findings from a series of multi-site randomized clinical trials examining psychological and behavioral responses to various methods of genetic risk assessment for AD using APOE disclosure. We discuss challenges involved in disease risk estimation and communication and the extent to which participants comprehend and perceive utility in their genetic risk information. Findings on the psychological impact of test results are presented (e.g. distress), along with data on participants' health behavior and insurance purchasing responses (e.g. long-term care). Finally, we report comparisons of the safety and efficacy of intensive genetic counseling approaches to briefer models that emphasize streamlined processes and educational materials. The implications of these findings for the emerging field of personal genomics are discussed, with directions identified for future research.

Genetics, genomics, and cancer risk assessment: State of the Art and Future Directions in the Era of Personalized Medicine

Scientific and technologic advances are revolutionizing our approach to genetic cancer risk assessment, cancer screening and prevention, and targeted therapy, fulfilling the promise of personalized medicine. In this monograph, we review the evolution of scientific discovery in cancer genetics and genomics, and describe current approaches, benefits, and barriers to the translation of this information to the practice of preventive medicine. Summaries of known hereditary cancer syndromes and highly penetrant genes are provided and contrasted with recently discovered genomic variants associated with modest increases in cancer risk. We describe the scope of knowledge, tools, and expertise required for the translation of complex genetic and genomic test information into clinical practice. The challenges of genomic counseling include the need for genetics and genomics professional education and multidisciplinary team training, the need for evidence-based information regarding the clinical utility of testing for genomic variants, the potential dangers posed by premature marketing of first-generation genomic profiles, and the need for new clinical models to improve access to and responsible communication of complex disease risk information. We conclude that given the experiences and lessons learned in the genetics era, the multidisciplinary model of genetic cancer risk assessment and management will serve as a solid foundation to support the integration of personalized genomic information into the practice of cancer medicine.

Pharmacogenomics instruction in US and Canadian medical schools: implications for personalized medicine

Aims: To determine the extent of pharmacogenomics instruction at US and Canadian medical schools, characterize perceptions of curricular coverage, identify curricular resources and compare responses with similar studies conducted in US pharmacy schools and British medical schools. Materials & methods: A survey was sent to the pharmacology department chairs of US and Canadian medical schools accredited by the Liaison Committee on Medical Education or the American Osteopathic Association’s Commission on Osteopathic College Accreditation. Data were collected from July 2009 to February 2010. Results: A total of 56% of eligible medical schools responded (90 out of 160). Of these schools, 82% (74 out of 90) incorporated pharmacogenomics into their curriculum. However, only 28% (21 out of 74) had more than 4 h of the required didactic pharmacogenomic coursework, and only 29% (22 out of 75) were planning to increase the number of pharmacogenomic coursework hours in the next 3 years. Pharmacogenomics coursework was most often contained within a required pharmacology course (66%; 49 out of 74) taught in the second professional year (72%; 53 out of 74). A total of 57% (44 out of 77) considered pharmacogenomics instruction at their own school as ‘poor’ or ‘not at all adequate’ while 76% (54 out of 71) considered it ‘poor’ or ‘not at all adequate’ at most medical schools. Conclusion: Most US and Canadian medical schools have begun to incorporate pharmacogenomics material into their curriculum; however, the extent of instruction is less than that of US pharmacy schools. To adequately prepare physicians to practice in the era of personalized medicine, medical schools should be encouraged to incorporate greater pharmacogenomic material in their curriculum.

Extending comprehensive cancer center expertise in clinical cancer genetics and genomics to diverse communities: the power of partnership

Rapidly evolving genetic and genomic technologies for genetic cancer risk assessment (GCRA) are revolutionizing the approach to targeted therapy and cancer screening and prevention, heralding the era of personalized medicine. Although many academic medical centers provide GCRA services, most people receive their medical care in the community setting. However, few community clinicians have the knowledge or time needed to adequately select, apply, and interpret genetic/genomic tests. This article describes alternative approaches to the delivery of GCRA services, profiling the City of Hope Cancer Screening & Prevention Program Network (CSPPN) academic and community-based health center partnership as a model for the delivery of the highest-quality evidence-based GCRA services while promoting research participation in the community setting. Growth of the CSPPN was enabled by information technology, with videoconferencing for telemedicine and Web conferencing for remote participation in interdisciplinary genetics tumor boards. Grant support facilitated the establishment of an underserved minority outreach clinic in the regional County hospital. Innovative clinician education, technology, and collaboration are powerful tools to extend GCRA expertise from a National Cancer Institute-designated Comprehensive Cancer Center, enabling diffusion of evidenced-base genetic/genomic information and best practice into the community setting.

Discriminatory accuracy from single-nucleotide polymorphisms in models to predict breast cancer risk

One purpose for seeking common alleles that are associated with disease is to use them to improve models for projecting individualized disease risk. Two genome-wide association studies and a study of candidate genes recently identified seven common single-nucleotide polymorphisms (SNPs) that were associated with breast cancer risk in independent samples. These seven SNPs were located in FGFR2, TNRC9 (now known as TOX3), MAP3K1, LSP1, CASP8, chromosomal region 8q, and chromosomal region 2q35. I used estimates of relative risks and allele frequencies from these studies to estimate how much these SNPs could improve discriminatory accuracy measured as the area under the receiver operating characteristic curve (AUC). A model with these seven SNPs (AUC = 0.574) and a hypothetical model with 14 such SNPs (AUC = 0.604) have less discriminatory accuracy than a model, the National Cancer Institute's Breast Cancer Risk Assessment Tool (BCRAT), that is based on ages at menarche and at first live birth, family history of breast cancer, and history of breast biopsy examinations (AUC = 0.607). Adding the seven SNPs to BCRAT improved discriminatory accuracy to an AUC of 0.632, which was, however, less than the improvement from adding mammographic density. Thus, these seven common alleles provide less discriminatory accuracy than BCRAT but have the potential to improve the discriminatory accuracy of BCRAT modestly. Experience to date and quantitative arguments indicate that a huge increase in the numbers of case patients with breast cancer and control subjects would be required in genome-wide association studies to find enough SNPs to achieve high discriminatory accuracy.