The sequencing of the human genome and the identification of links between specific genetic variants and diseases have led to tremendous excitement over the potential of genomics to direct patient treatment toward more effective or less harmful interventions. Still, the use of whole genome sequencing challenges the traditional model of medical care where a test is ordered only when there is a clear indication for its use and a path for downstream clinical action is known. This has created a tension between experts who contend that using this information is premature and those who believe that having such information will empower health care providers and patients to make proactive decisions regarding lifestyle and treatment options. In addition, some stakeholders are concerned that genomic technologies will add costs to the health care system without providing commensurate benefits, and others think that health care costs could be reduced by identifying unnecessary or ineffective treatments.
Economic models are frequently used to anticipate the costs and benefits of new health care technologies, policies, and regulations. Economic studies also have been used to examine much more specific issues, such as comparing the outcomes and cost-effectiveness of two different drug treatments for the same condition. These kinds of analyses offer more than just
1 The planning committee’s role was limited to planning the workshop, and the workshop summary has been prepared by the workshop rapporteurs as a factual summary of what occurred at the workshop. Statements, recommendations, and opinions expressed are those of individual presenters and participants and are not necessarily endorsed or verified by the Institute of Medicine, and they should not be construed as reflecting any group consensus.
predictions of future health care costs. They provide information that is valuable when implementing and using new technologies. Unfortunately, however, these economic assessments are often limited by a lack of data on which to base the examination. This particularly affects health economics, which includes many factors for which current methods are inadequate for assessing, such as personal utility, social utility, and patient preference.
To understand better the health economic issues that may arise in the course of integrating genomic data into health care, the Roundtable on Translating Genomic-Based Research for Health hosted a workshop in Washington, DC, on July 17-18, 2012, that brought together economists, regulators, payers, biomedical researchers, patients, providers, and other stakeholders to discuss the many factors that may influence this implementation. The workshop was one of a series that the roundtable has held on this topic, but it was the first focused specifically on economic issues.
To have a focused discussion on the potential downstream health economic issues that arise from various models of using whole genome sequencing in clinical settings, participants were asked to make three assumptions: (1) whole genome sequencing costs are an acceptable and fixed expense, though interpretation costs may not be; (2) data storage costs are assumed to be acceptable and fixed as well; however, electronically stored data may not be transportable across health care systems over an individual’s lifespan; and (3) such tests are available in the context of a health care encounter.
The workshop began with two broad overviews of the economics of genomic applications in medicine, the first from the perspective of a clinician (Chapter 2), and the second from the perspective of an economist (Chapter 3). The remainder of the workshop’s first day was organized around three different encounters that one individual female patient had with the health care system over the course of a 15-year period and three life events. In the first (Chapter 4), she visits an obstetrician for preconception testing:
In 2012, a 35-year-old Ashkenazi Jewish female smoker in good health is seen for a preconception visit. Under the current standard care model, targeted carrier status testing is offered. In terms of high effect sized variations that would be detected by traditional genetic testing, she is found to be a carrier for Tay-Sachs. In addition, if testing were extended in this scenario beyond what might be considered to be current standard of care, she would be found to harbor a prothrombin gene mutation, as well as variations in CYP2C9 and VKORC, indicating that she is likely to be highly sensitive to warfarin anticoagulation. She is also homozygous for ApoE4, but does not have familial hypercholesterolemia. She can be expected to have lower risk
variants and variants of unknown significance in accordance with expected population frequencies for the conditions under consideration.
In the second (Chapter 5), she develops a spontaneous deep vein thrombosis:
The individual is seen at 40 years of age with progressive left lower extremity swelling and pain. Evaluation reveals an unprovoked deep vein thrombosis in her left lower extremity. She will be treated as an outpatient with low-molecular-weight heparin and warfarin. Targeted testing includes CYP2C9 and VKORC gene analysis.
In the last (Chapter 6), she develops a lung cancer:
The individual is seen at age 50 with cough, dyspnea, and chest discomfort. Evaluation reveals a lung mass; bronchoscopy and biopsy reveal a non-small-cell lung cancer. Her tumor is found to have variations that allow the use of targeted therapy, and with treatment the patient goes into remission.
The three case scenarios were developed and presented to speakers to provide a guiding framework for discussions about the downstream and ancillary effects of providing genomic information in the clinical setting. The scenarios represent potential points where genetic information may currently provide value in clinical decision making and allow for a discussion of the potential sources of benefits and costs associated with three models of genomic data delivery:
- Targeted mutation detection using individual or panels of tests (current standard of care). This will include detection of variants of unknown significance.
- Whole genome sequencing with provision of data relevant only to the current clinical situation and a handful of high effect sized “actionable variants.” This will include detection of variants of unknown significance.
- Whole genome sequencing with provision of data relevant to the clinical situation as well as other potentially significant secondary findings using the current best available data for interpretation. This will include lower effect sized variants, as well as variants of unknown significance.
Two separate panels reacted to each of these three scenarios. The first panel consisted of a clinician, a futurist, and a patient, who talked about how having genomic information could affect the choices, attitudes, and needs of stakeholders throughout the health care system. The second panel
consisted of three economists who discussed the major economic issues surrounding the three scenarios.
On the second day of the workshop, the panelists from the first day reflected in a condensed form on their conclusions from the day before. Workshop participants also commented on the implications of issues raised during the workshop. These reflections and comments constitute the final chapter of this workshop summary.
In his concluding remarks at the workshop, W. Gregory Feero, who at the time was a special adviser to the director of the National Human Genome Research Institute, offered his perspective on the major themes that emerged from the day and a half of discussion. Feero’s summary of these themes is presented here as an introduction to the wide range of topics that arose in considering the economic consequences of genomic technologies. These ideas should not be seen as the conclusions of the workshop as a whole, but they do provide an overview of the topics summarized in the remainder of this volume.
The diversity of issues that comprise the economics of whole genome sequencing requires a spectrum of expertise and perspectives, Feero said. Some of these issues are solely economic, but others involve technology development; research needs; ethical, legal, and social issues and education; and health services. Each of these issues poses obstacles to the integration of genomics into clinical care and each needs to be well understood if the potential benefits of genomics are to be maximized.
The economics of genomic sequencing vary by application and by setting, Feero said. A major question is therefore how to frame and analyze the economic issues. Values and costs can be measured in different ways, and these methods influence decisions about the use of technologies. In particular, improved methods are needed for assessing value, personal utility, and patient preferences.
A related complication is that public health, clinical care, and academic medicine have different economic assessment models. These models have to be aligned in a way that makes a difference to patients, said Feero. Also, particular models will be more or less useful in the currently evolving health care environment.
The infrastructure needs to be developed to measure outcomes related to economic factors along with standard health outcomes, not just for genomics but across the health care system. For example, better and quicker
approaches are needed for performing economic evaluations of genetic and genomic tests and the consequences of assaying particular genetic variants. Evaluating tests and variants one by one will be too daunting, said Feero. Sorting tests and variants into categories that can be assessed is one possible way of achieving this objective.
Economic analyses should be integrated into ongoing whole genome sequencing clinical studies, Feero said. It is being considered in some demonstration projects, but it could be part of all clinical studies. The economic incentives for test and evidence development under the current system of reimbursement versus a value-based pricing approach that incorporates the intellectual cost of interpretation need to be further explored.
If health care resources are flat or declining, and a potentially innovative technology is available, what or who will be replaced to allow for funding of genomic interventions? People will need to come to grips, said Feero, “with the fact that we should not be paying for very expensive, not particularly efficacious things in lieu of some things in genomics that actually are efficacious and not that expensive.”
Sequencing will continue to get faster, cheaper, and more accurate, said Feero. At the same time, cheaper and faster technologies are needed for molecular characterization of samples beyond DNA.
Integrating genomic information into health information technologies and other infrastructures is constrained with current information technology systems. In academia, for example, many information technology departments have long lists of problems to solve and a finite budget, noted Feero, and these problems will compete against the incorporation of genomic results into databases.
Better methods are needed to determine which genetic variants should be acted upon in a clinical encounter. Behavioral research could determine if and how genomic information modifies the behavior of patients and health care providers, which is particularly important because this behavior will be a major driver of costs, said Feero. Also new methods are needed to increase participation in clinical trials, including participation of underrepresented subpopulations.
Epidemiological research is needed to evaluate risk assessments across platforms for various conditions, noted Feero. Epidemiologists also need to determine the relative contributions of environmental factors to health outcomes.
In general, resources need to be shifted toward translational research, said Feero, and this research needs to illuminate the economics of adapting new technologies.
Ethical, Legal, and Social Issues and Education
In the area of ethical, legal, and social issues, outcomes data on informed consent is a major need, cited Feero. What kind of informed consent is appropriate in the relationship between provider and patient?
In the area of education, Feero asked, can more efficient methods for patient and provider education be developed? Also, genomic scientists and clinicians need education about economic analyses applied to genomic tests.
Health systems will need new methods and a stronger infrastructure, including informatics, to track and analyze the downstream consequences of providing sequence data, said Feero. For example, do codes exist that will follow what happens when genomic information is made available?
When should genomic sequencing be done during the lifespan of an individual, Feero asked. Possibilities range from having the complete sequence available at birth to conducting targeted sequencing at the time of diagnosis. If genomic results that are already available are more likely to be used than results that need to be obtained after the patient presents themselves, this raises the question of thresholds for the use and generation of evidence.
Knowledge gained from new technologies may not be applicable to all populations because not all populations are represented in research, noted Feero, which could heighten disparities in health care. Efforts should be invested in determining how new technologies could exacerbate or ameliorate existing disparities. However, it is important to remember that this issue is not specific to genomics.
Finally, asked Feero, in a world of stable or declining resources, do accountable care organizations provide a model for producing more efficient health care using genomic technologies?
The Need for a Systems Perspective
All these issues need to be considered from a systems perspective, said Feero. Most researchers, including economists, consider problems within a particular context and develop a carefully designed question, which produces an internally consistent and robust answer for that question. But any such problem is just part of a much larger overall picture. Particularly
in health care, economic analyses encompass issues that range far beyond costs and benefits to complex issues of regulation, ethics, and equity, as the above themes demonstrate. Many different sources of information will need to be brought together efficiently to enable informed decision making and to determine how to move forward with integrating genomic medicine in a way that maximizes patient benefit while at the same time making the most economic sense.