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PERSPECTIVEGetting To ‘Smart’ Health Care
As the United States struggles with improving the return on its sizable health care investment and consumers become increasingly involved in health care decisions, interest in comparative effectiveness will rise because of its relevance to value, personalized health care, quality, and cost containment. Advances in biomedicine and health information technology present exciting opportunities for providing timely, relevant information about the comparative effectiveness of health care services. Successful growth will require a transparent, participatory approach and new partnerships between the public and private sectors to achieve the goal of producing valid evidence for decision making.
AMERICANS ARE fortunate to live at a time when investments in biomedical research have resulted in a plethora of new diagnostic and therapeutic options. An expanded array of choices for treating hypertension, heart failure, HIV, and other chronic illnesses and unprecedented innovations in diagnosis and prediction bring us closer to a vision of personalized health care than ever. These new opportunities represent only the beginning—and they challenge all parties to determine which innovations represent added value, which offer minimal enhancements to current choices, and which fail to reach their potential. The need to develop better evidence about the benefits, risks, and costs of alternative choices is imperative. Thus, Gail Wilensky’s paper on the structure, financing, and function of a center that supports better decision making in health care is timely and important.1 In briefly reviewing how other developed countries are approaching this challenge, her paper makes clear that comparative effectiveness research is a global enterprise, independent of differences in how health care is organized and financed. The urgency of this need is underscored by our understanding that new information often takes years to inform practice. A "smart" health care system requires effective tools to organize and disseminate relevant information to multiple audiences in addition to the underlying evidence. Although research investments are deemed a public good, the timely application of the products of research will depend on effective partnerships between the research enterprise and health care delivery, and between the public and private sectors. Growing investments in health information technology (IT) offer the capacity to disseminate reliable information to the point of decision making and to provide important feedback to the biomedical enterprise itself. In short, comparative effectiveness research is a key component of, but tightly linked with, health care delivery itself in the Information Age.
The concept of comparative effectiveness is not new—indeed, the creation of the Agency for Healthcare Research and Quality (AHRQ) was inspired by policymakers who grasped the power of information to improve health care. The salience of comparative effectiveness was recognized in Section 1013 of the Medicare Prescription Drug, Improvement, and Modernization Act (MMA) of 2003, which authorized AHRQ to conduct and support syntheses and research on topics of highest priority to the Medicare, Medicaid, and State Children’s Health Insurance Program (SCHIP) populations. As we have implemented the Effective Health Care program in response to this mandate, important themes have emerged. Priority setting. Numerous entities including the Institute of Medicine (IOM) have struggled with the challenge of setting priorities for technology assessment, for transforming health care. Commonly, priorities are set using a combination of factors such as burden of illness, impact on a population, cost, and potential for impact. The authors of Section 1013 recognized that traditional priority setting relied disproportionately on the views of expert panels and researchers. They envisioned a new, more balanced approach—one that better meets the needs of those who manage, are served by, and have a stake in these programs. To accomplish this goal, the statute directs the secretary of health and human services, rather than AHRQ, to establish priorities, informed by a transparent priority-setting process that includes all stakeholders. Framing the research questions. Research that compares similar types of interventions is helpful for specific purposes. However, clinicians and patients increasingly confront decisions for which multiple different treatments are relevant. For example, should a fifty-five-year-old woman with a scan showing greatly decreased bone density take drugs, increase Vitamin D and calcium intake, focus on weight-bearing exercise, or watchfully wait? Drugs are effective, but there is limited information on long-term effects; some women will develop kidney stones after increased calcium; current evidence does not allow precise formulation of an effective exercise prescription; and many women will never experience a fracture. Clearly, our work must provide evidence that informs the choices confronting clinicians and patients and, where possible, should closely align with the sequence of decisions they face. As Section 1013 directs, we also need to revisit our findings frequently to incorporate new evidence, such as a genetic test that identifies people at increased risk of untoward outcomes. Balancing benefits and harms. By definition, informed decisions require information on both comparative benefits and harms. Few interventions are risk free, and for many chronic conditions the therapeutic goal is management of symptoms and disease state rather than cure. Often times, the decision comes with some assumption of harm—by both patient and clinician—but with the understanding that the benefits are worth that risk. Since few clinical studies follow patients over years of treatment, clinicians and patients must use the best available information to identify the option or options that best match the individual’s values and preferences. Variation attributable solely to informed decision making should be celebrated in a smart system, and it offers future opportunities to evaluate the outcomes of different decisions. Research as a means, not an end. The continued and future growth of diagnostic and treatment options is dazzling but clearly overwhelms the current research enterprise. Hence, priority setting to identify the most urgent questions in need of answers, and discussions of which methods are best suited to the question at hand, will continue to challenge the brightest in the field. However, research on comparative effectiveness is a means, not an end. The ultimate goal is timely, relevant information for decision making. The traditional products of academic research have been peer-reviewed articles, whose findings diffuse into practice slowly if at all. Moreover, many articles written for a scientific audience might not be easily put into perspective by clinicians, consumers, and others. We have a great deal to learn about developing and disseminating valid information in a variety of formats to diverse audiences—from Internet reports to interactive decision tools to clinical decision support. To that end, AHRQ created the John M. Eisenberg Center for Communications and Decision Sciences Center to produce and improve products that assure the understanding and use of comparative effectiveness research findings. Over time, this work will enable AHRQ to apply the state of the art in decision science to how we carry out our role as a clearinghouse for communicating and using the findings of comparative effectiveness research. Comparative effectiveness research and health services research. Assuring the prompt and effective use of comparative effectiveness research cannot be done in isolation of research that clarifies which features of health care organizations and which public policies impede or accelerate the use of new information to improve care. Where comparative effectiveness research focuses on the question of what works and for whom, health services research provides a framework for understanding how systems can both contribute to and use information on benefits and harms of alternative treatments. Perhaps more important, health services research clarifies which combinations of policies, tactics, and organizational characteristics are most likely to accelerate delivery of interventions to people most likely to benefit and to offer some protections so that people who are likely to experience harms are sufficiently informed. Trust as a process, not a structure. Wilensky quite rightly identifies the point that comparative effectiveness research can be a risky business. Studies that identify winners and losers might first be reported in the business section and have substantial financial impacts. More subtly, manufacturers might perceive that inferences not directly supported by science are made in the interest of effective communication—a risk that must be balanced by the knowledge that clinicians and patients often need to make decisions now and might not be able to wait for a better study. The risks posed by continued unabated increases in health spending, however, make it inevitable that comparative assessments will be conducted. Emulating work conducted in other countries, AHRQ’s Effective Health Care program has established transparency in all aspects of the process. Manufacturers are notified when a study is begun, are invited to submit relevant studies and data, and have the opportunity—along with any other interested party—to comment on the framing of the specific research questions as well as draft reports. In addition, it is clear that the program’s success is dependent on effective collaboration with scientists from industry as well as academe. It is too soon to develop firm conclusions regarding the effectiveness of the process mandated by Section 1013. But there appears to be a growing recognition that to the extent that the trend toward comparative effectiveness research is inevitable, industry’s concerns are more likely to be heard and addressed by the type of transparent process we are required to follow than by private-sector reviews for which the methodologies are considered proprietary information.
For the past fifteen years, researchers have become increasingly innovative in using administrative data to glean insights about variations in clinical care and to develop testable hypotheses for clinical trials. The inherent limitations of administrative data, however, have overshadowed methodological and statistical advances in conducting observational studies. Anticipated growth in investments in health IT across the health care sector now offer an unprecedented opportunity for redefining the possibilities of observational studies, accelerating and targeting the uptake of relevant information, and providing feedback to the biomedical enterprise itself. Investments in health IT by large delivery systems are driven today by the urgency of improving the quality, efficiency, and safety of care. As part of AHRQ’s Effective Health Care program, we now have the capacity to conduct accelerated practical studies about the outcomes, comparative clinical effectiveness, safety, and appropriateness of health care items and services to address questions for which expensive clinical trials are not appropriate. The network comprises thirteen research-based health organizations with access to electronic health information databases and the capacity to conduct rapid-turnaround research. The potential for electronic health records, with appropriate privacy protections, to support research is also increasingly apparent. This potential could be greatly augmented by establishing health systems consortia to collaborate on selected research topics. Such an approach would be most effective by the development of common, consistent definitions for selected data elements so that each data repository would remain independent but capable of contributing to studies requiring very large sample sizes that no single system could address in isolation (for example, the impact of breakthrough treatments affecting a small patient population). This approach could also support the creation of research registries derived from clinical information systems rather than established as a stand-alone enterprise and could assist in the development of much-needed longitudinal information on a variety of treatments. These developments will not eliminate the need for prospective clinical trials but will certainly inform which are most critical and how they can be conducted efficiently. Health IT also supports the use of clinical decision support to deliver information relevant to a person to the point of decision making. Most commonly envisioned as a pop-up reminder on a screen, clinical decision support should include information communicated directly to patients and caregivers at home—by phone, computer, or other means. Last, identifying the impacts of innovative treatments based on advances in molecular biology and genetics can also be improved by interoperable health IT systems that permit longitudinal assessment of benefits and unanticipated harms. Some of these treatments will likely be applied to patients who do not completely match eligibility criteria—as it is probable that some patients who would be expected to benefit do not. In both instances, the capacity to provide information back to biomedical researchers can only aid in the development and refinement of future advances.
The U.S. health care system is poised to take advantage of advances in science and information and communications technology in ways that have previously only been imaginable. Recent policies to promote the adoption of interoperable health IT, continued expansion of diagnostic and treatment options, increased consumer interest in health and health care decisions, and broad interest in improving value reinforce the need for valid, reliable, and accessible information on the comparative benefits and potential harms of treatment options. This vision is achievable and dependent on effective collaboration between the public and private sectors. A transparent, participatory approach to collaboration is essential; broad engagement of stakeholders can mitigate the expected controversies of the findings of comparative effectiveness research. As health care delivery becomes an intrinsic part of a networked world, a focus on comparative effectiveness is clearly as much about quality, safety, and personalized health care as it is about cost containment. The best structure and home for comparative effectiveness research should flow from identifying the most effective strategies for initiating and managing new partnerships that are critical to its success.
Carolyn Clancy (carolyn.clancy{at}ahrq.hhs.gov) is director of the Agency for Healthcare Research and Quality in Rockville, Maryland.
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