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Knowing what Works in Health Care: A Roadmap for the Nation 2 An Imperative for Change Abstract: This chapter documents the imperative for immediate action to change how the nation marshals clinical evidence and applies it to endorse the most effective clinical interventions. The chapter describes five interconnecting, persistent health policy challenges that are inextricably associated with the need to know what works in health care: (1) unsustainable rates of increase in costs, (2) unwarranted geographic variation in the use of services, (3) unreliable quality, (4) consumer-directed health care, and (5) the need to make informed decisions about the health services that should be covered by health insurance. The chapter provides a brief description and assessment of the efforts that are being made to address the need for information on clinical effectiveness as well as the primary challenges facing the current system. This sets the stage for the committee’s recommendations for addressing the challenge in the subsequent chapters. To a great extent, the resolution of some of the nation’s most pressing health policy concerns hinges on the capacity to identify highly effective clinical services. Unsustainable rates of growth in health spending result from the delivery of effective as well as ineffective care. The high costs associated with the provision of both appropriate and inappropriate care lead to higher insurance premiums. Unwarranted variation in clinical practice reflects deviations from accepted standards of care, as well as uncertainty and disagreement regarding what those standards should be. This contributes to the health care quality chasm in which patients cannot always be assured that they will receive the best, most effective care. The common thread in each of these policy areas is the need to differentiate between effective and ineffective care.
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Knowing what Works in Health Care: A Roadmap for the Nation In recent years, the capacity of the United States to evaluate clinical effectiveness has improved substantially. A number of public and private organizations synthesize and assess the evidence on clinical effectiveness, and many others focus on applying in real world settings the knowledge that those organizations generate. However, significant gaps in the ability to develop, synthesize, and apply the evidence on clinical effectiveness remain; and the nation faces major challenges as an array of new—and often very expensive—technologies and treatments rapidly enter the health care marketplace. As a result, the nation needs to continue to improve its capacity to assess clinical effectiveness and ensure that health care decision making is grounded in the evidence about what works. BACKGROUND Over the past 50 years medical knowledge has grown dramatically as breakthroughs have occurred in numerous areas of medical science, including genomics, stem cell biology, biomedical engineering, molecular biology, and immunology (Sung et al., 2003). Investments in biomedical research, both public and private, have increased steadily over time, resulting in a rapid pace of innovation in health care (Neumann and Sandberg, 1998; Zinner, 2001). Many more preventive, diagnostic, and treatment alternatives are available to patients than were available in past years; and even more are in development, including products that have resulted from research in pharmacogenomics, biotechnology, and nanotechnology (Joint Economic Committee, 2007; Walsh, 2005). Investments in research directed at understanding the human genome and the functions of genes will provide more opportunities to deliver personalized medicine, which will tailor diagnoses and therapies to an individual’s own genotype (Meadows, 2005). At the same time, the 77 million members of the nation’s baby boom generation are nearing retirement age, and soon the health system will be confronted with patients from this large and increasingly complex cohort of individuals with multiple comorbidities, including physical and cognitive impairments (AHRQ, 2001). This will place increased demands on the health system and will add to cost pressures. For patients and providers, as well as for society as a whole, ascertaining the effectiveness of the available preventive, diagnostic, and treatment options is becoming increasingly urgent. The expense of emerging technologies and the projected increases in consumer demand virtually ensure that cost control will be a central focus for policy makers, health plans, and others in the coming years (Clancy, 2003). Moreover, variation in treatment patterns means that, in many cases, patients will continue to receive care that deviates from standards of high quality. In the context of rapidly ris-
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Knowing what Works in Health Care: A Roadmap for the Nation ing costs, society’s ability to distinguish between health interventions that work and those that do not work, and for whom they work, is becoming more and more important. Medical Advances In recent years, many new diagnostics, devices, drugs, biologics, and procedures have been added to the medical armamentarium. In addition, innovations first established in other fields have been applied to medicine through technology transfer, including lasers, ultrasound, and magnetic resonance spectroscopy (Gelijns and Rosenberg, 1994). Over the course of the coming decade, the pace of innovation in medical care is likely to accelerate even more. Although the time from discovery to clinical availability remains long, many medical innovations are moving closer to the release stage. In recent years, the number of patents that have been issued for biomedical devices and biopharmaceuticals has increased significantly. From 1991 to 2003, the number of new patents issued for medical devices doubled from 4,500 to more than 9,000. From 1992 to 2001, the total number of biotechnology patents granted per year tripled, from less than 2,600 to nearly 7,800 (IOM, 2007a). Information Overload Along with the increase in the numbers of medical treatments and interventions that are available, the volume of literature describing investigations of these interventions has also expanded. From 1978 to 2001, 8.1 million journal articles were published in MEDLINE.1 From 1978 to 1985, the average annual number of articles indexed by MEDLINE was 272,344. By the 1994 to 2001 time period, the average annual volume of indexed articles had increased by 46 percent to 442,756. Much of the growth in the literature was in articles on randomized trials and other types of clinical research that could be used to guide evidence-based practice (Druss and Marcus, 2005). The evidence base for clinical effectiveness has thus become so vast that it is essentially unmanageable for individual providers (IOM, 2001). Yet, at the same time, the primary literature provides limited guidance on a broad range of urgent clinical questions, such as comparative effectiveness and long-term patient outcomes (Tunis et al., 2003). The massive quantity of evidence places significant demands on anyone 1 MEDLINE is a database of the National Library of Medicine, National Institutes of Health.
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Knowing what Works in Health Care: A Roadmap for the Nation seeking to stay abreast of current standards of care. For physicians, information on the available care options can be overwhelming, even when just a single class of interventions, such as pharmaceuticals, is considered. For example, for antihypertensive medications, a search of the PubMed database of the National Center for Biotechnology Information of the National Library of Medicine, the National Institutes of Health (NIH) (http://pubmed.gov), by use of the terms “antihypertensive agents AND therapeutic use” identified 312 English-language review articles that the PubMed database had indexed between October 1, 2006, and September 12, 2007. As a result of this increase in the quantity of relevant information, synthesized information such as systematic reviews, clinical guidelines, and resources (e.g., The Cochrane Library), have become essential tools for the users of the evidence (Druss and Marcus, 2005). However, the number of these products has also grown substantially. For example, as of September 2007, the Agency for Healthcare Research and Quality’s (AHRQ’s) National Guideline Clearinghouse (2007b) listed 54 clinical practice guidelines under the heading “antihypertensives.” In this situation, end users need a mechanism to determine which summaries are the most relevant, valid, and reliable. For physicians—and patients—who are motivated enough to read through and assess all of the relevant individual clinical studies on their own, keeping current is an arduous, if not impossible, task. Given the variable quality of the research and its limited generalizability, these providers and patients are faced not only with reconciling vastly different research findings but also with scrutinizing each study’s methodology in detail to ensure that the study has been well designed, that the analyses have been well performed, and that the results apply to their particular clinical circumstance (Abramson, 2004). This expectation is unrealistic, especially given that today’s medical residents frequently lack the knowledge in biostatistics necessary to interpret the findings of published clinical research (Windish et al., 2007). These findings illustrate the need for a system that can make sense of all of the data that currently exist, as well as the new knowledge that is now being generated. PERSISTENT HEALTH POLICY CHALLENGES Clinical effectiveness is a central issue in health care. Improving the capacity to conduct clinical effectiveness assessments has the potential to improve health care in a range of vital areas, from cost to quality and access. These opportunities make it imperative that the United States makes improvements in its capacity to make impartial, accurate effectiveness assessments. This capability may also provide the financial leeway needed to allow the adoption of innovative breakthrough technologies.
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Knowing what Works in Health Care: A Roadmap for the Nation Unsustainable Rates of Increase in Costs A significant proportion of health care costs is directed to care that has not been shown to be effective and that may actually be harmful. For example, Wennberg and colleagues (2006) concluded that decreased utilization of acute care hospitals and physician visits by Medicare beneficiaries could actually lead to better clinical outcomes and also prolong the solvency of the program. The authors found that 30 percent of Medicare spending on chronically ill individuals was unnecessary. Other studies have also estimated that the potential savings from reducing excessive spending on services of little or no value in the Medicare program may be as high as 30 percent of all expenditures (Wennberg et al., 2002a). Historically, health care cost-containment efforts in the United States have had little to no success (Altman and Levitt, 2002). The levels of spending on health care rose from 5.7 percent of the gross domestic product (GDP) in 1965 to 16 percent of the GDP in 2004 (Lubitz, 2005). By 2015, spending is projected to reach 20 percent of the GDP, or an estimated $4 trillion, up from $1.9 trillion in 2004 (Borger et al., 2006; Cutler, 2005). The U.S. Government Accountability Office (2007) concludes that rising health care costs pose a fiscal challenge not just to the federal budget but also to states, American businesses, and society as a whole. The federal Medicare program spent $374 billion in 2006 and accounted for 13 percent of all federal spending (Kaiser Family Foundation, 2007). Spending on Medicare is projected to reach $564 billion in 2012 and in the subsequent years will continue to consume an increasingly large portion of federal revenues. Along with projected increases in spending on Social Security, Medicaid, and interest on the federal debt, these expenditures will begin to crowd out spending in many other areas of the budget. As a result, fiscal pressures will necessitate a series of difficult budget decisions in coming years (Walker, 2007). Figure 2-1 provides Congressional Budget Office estimates of Medicare and Medicaid spending as a percentage of the GDP through 2050. In this context, improving the U.S. capacity to evaluate the effectiveness of medical treatment options appears to be vital. Unwarranted Geographic Variation in the Use of Health Services Evidence suggests that there is a substantial potential to improve the quality of health care by addressing the inappropriate variation in the use of health services (IOM, 2001). Analysis of the widespread geographic differences in health spending and the use of services does not support the hypothesis that greater spending results in increased life expectancy or better health outcomes overall in the regions with higher levels of spending (Fisher et al., 2003a; Fuchs, 2004; Wennberg et al., 2002b).
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Knowing what Works in Health Care: A Roadmap for the Nation FIGURE 2-1 Total federal spending for Medicare and Medicaid under assumptions about the health care cost growth differential. SOURCE: Congressional Budget Office (2007). Health care differs substantially across the country, from one small region to another and from one city to the next (Feenberg and Skinner, 2000; Fisher et al., 2003a). These variations occur across a wide range of health interventions, including the use of delivery by cesarean section (Baicker et al., 2006); cardiac procedures after acute myocardial infarction (Guadagnoli et al., 1995); treatment of degenerative diseases of the hip, knee, and spine (Weinstein et al., 2004); and the treatment of individuals who are chronically ill (Wennberg et al., 2004). There are also significant disparities in the quality and the quantity of the health services received by minority groups in the United States (IOM, 2003). Among Medicare beneficiaries, regional differences in spending reflect a greater frequency of physician visits, the more frequent use of specialist consultations, more frequent tests and minor procedures, and the greater use of the hospital and intensive care unit in certain regions (Fisher et al., 2003b). In addition, larger expenditures are associated with dramatic differences in end-of-life care seen in various parts of the country (Skinner and Wennberg, 2003). Overall, the difference in lifetime Medicare spending between a typical 65-year-old in Miami, Florida, and one in Minneapolis, Minnesota, has been estimated to be more than $50,000 (Wennberg et al., 2002b). Figure 2-2 illustrates these spending differentials in 2003.
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Knowing what Works in Health Care: A Roadmap for the Nation FIGURE 2-2 Medicare spending per capita in the United States, by hospital referral region, 2003. NOTE: The numbers in parentheses indicate the number of regions in each group. Reprinted, with permission, from The Dartmouth Atlas Project, 2003. Copyright 2007 by The Trustees of Dartmouth College. SOURCE: The Dartmouth Atlas Project (2003). Greater expenditures do not necessarily result in better health outcomes, however (Fuchs, 2004). Fisher and colleagues (2003b) found no evidence that the patterns of practice observed in higher-spending regions led to improved survival, a slower decline in functional status, or a greater satisfaction with care. A higher rate of utilization of medical tests and procedures can, in some cases, have negative consequences for patients, as in the case of false-positive screening test results (Mitka, 2004). Consequently, differentiating between effective and ineffective health utilization is an important policy objective. Variation in physician practice patterns has been a persistent concern because it points to the overuse and underuse of specific health services (Schwartz, 1984; Wennberg, 2004). These designations suggest that there are benchmarks that define optimal use; however, these are often not well defined. Investigators have asserted that, for some preference sensitive services, informed patient preference should be used to establish the bench-
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Knowing what Works in Health Care: A Roadmap for the Nation marks for appropriate use (Wennberg, 1988; Wennberg and Wennberg, 2003), yet this presupposes that patients (and providers) have access to reliable, relevant, and trustworthy information about treatment outcomes. This is often not the case. As a result, many policy makers have called for the establishment of a national organization that would be able to meet the need for clinical effectiveness information (America’s Health Insurance Plans, 2007; BCBSA, 2007a; Medicare Payment Advisory Commission, 2007; Shortell et al., 2007; Wilensky, 2006). The Quality Chasm The Institute of Medicine (IOM) report Crossing the Quality Chasm (2001) identified six aims for patient care: safety, effectiveness, patient centeredness, timeliness, efficiency, and equity. To promote effective care, the report indicated that scientific knowledge should be employed to ensure that all patients who might benefit from a certain intervention receive the services, whereas those who are not likely to benefit should not (i.e., avoiding underuse and overuse). The report recognized that the evidence base needed to support effective care is limited for many health and health care topics, but it concluded that health care providers and organizations should do more to determine the most appropriate therapies on the basis of the strength of the evidence and then adhere to those preferred therapies. Strategies that encourage quality improvement, such as pay-for-performance incentives, are also based on the ability to recognize excellent performance, promote best practices, and reduce errors (Berwick et al., 2003). The IOM report Rewarding Provider Performance (2007b) highlights performance measures as key building blocks in this effort. However, these measures must be based on benchmarks of appropriate clinical performance, and these are often not available. Thus, a lack of reliable information about clinical effectiveness limits the ability to guide care and to evaluate it. Consumer-Directed Health Care Many policy makers believe in empowering consumers and patients to be prudent managers of their own health and health care (Buntin et al., 2006; Congressional Budget Office, 2006). Proponents of consumer-directed health plans argue that consumers who are equipped with good information on the cost and quality of health services will have the power to reduce the cost and improve the quality of care. Yet, information on the effectiveness, risks, and benefits of alternative treatments is rarely adequate (U.S. Government Accountability Office, 2006).
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Knowing what Works in Health Care: A Roadmap for the Nation Coverage Decisions Private and public health plans are struggling with an almost daily challenge of learning how their covered populations might benefit—or be harmed—by newly available health services. In making coverage decisions, it is rare for plans to have access to all of the information that they need, and it is often unclear what should guide their decision making in cases in which the scientific knowledge is inconclusive or lacking. Determining what level of evidence and what degree of certainty is sufficient to move forward with a decision to cover or not cover a new treatment involves a judgment about the risks of acting too soon (promoting the use of a treatment that is later determined to be ineffective or harmful) and acting too late (delaying the use of a treatment that is truly beneficial) (Atkins et al., 2005b). The value of costly, emerging technologies is widely debated. Cutler and McClellan (2001) argue that although technological changes have accounted for the bulk of the increases in medical expenditures over time, these medical advances have proved to be worth far more than their costs. In contrast, Redberg (2007) argues that many treatments undergo rapid adoption despite relatively limited evidence, resulting in high levels of spending for unproven procedures. The current controversy over the use of drug-eluting stents for the treatment of vascular disease is a case in point. In deciding what to include as part of their covered package of benefits, health plans and purchasers must decide about the value of specific interventions for particular groups of patients. Health services and technologies are deemed medically necessary, and therefore appropriate for inclusion in the benefit package, or experimental and investigational, and therefore not eligible for coverage. However, the term “medical necessity” is ill defined, unexamined, and idiosyncratically applied (Bergthold, 1995). Historically, insurers relied on the expert opinions of physicians in deciding what services and technologies to include as part of their benefit packages. Over time, however, plans have placed a stronger emphasis on high-quality scientific studies (Garber, 2001; Tunis and Pearson, 2006). CURRENT LANDSCAPE Providers, patients, health plans, and others need information about clinical effectiveness to ensure that the decisions that they make are solidly grounded in the evidence about what works. Toward that end, Congress has substantially increased funding for the NIH in recent years. Between 1998 and 2003 the NIH budget doubled, and by fiscal year 2007 it had reached $28.6 billion (Loscalzo, 2006). Private spending on research has also increased significantly (Iglehart, 2001). For example, investments in research and development on new medicines by the biotechnology and phar-
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Knowing what Works in Health Care: A Roadmap for the Nation maceutical research member companies of the Pharmaceutical Research and Manufacturers of America (PhRMA) (2006) reached $39.4 billion in 2005, up from $2 billion in 1980. In recent years there have also been increasing investments in the synthesis of the available clinical evidence in the United States, for example, with the establishment of AHRQ’s Evidence-based Practice Centers (EPCs), as well as private-sector activities (Atkins et al., 2005a; Garber, 2001). Appropriations for health services research made to all federal agencies—AHRQ, the NIH, the Veteran’s Health Administration, the U.S. Department of Defense, the Centers for Medicare & Medicaid Services (CMS), the U.S. Food and Drug Administration (FDA), and the Centers for Disease Control and Prevention—has now reached approximately $1.5 billion annually. However, research on clinical effectiveness receives only a small part of that investment (IOM, 2007a). In general, vastly more funding is available for primary medical research than for the synthesis of the available evidence. Key Players A number of public- and private-sector organizations are involved in the collection, analysis, and dissemination of clinical effectiveness information. In addition to the NIH and the private-sector groups that fund primary research, many other organizations are involved in assessing that information and synthesizing it in ways that inform decision making. Some of the many organizations that conduct these activities are described below. U.S. Food and Drug Administration In deciding whether particular drugs or devices should be allowed to enter the market, the FDA plays a central role in assessing clinical efficacy data. The FDA consists of eight offices. One of these, the Center for Drug Evaluation and Research (CDER), evaluates the safety and efficacy of all new drugs before they are sold on the market and monitors the safety of drugs after they have been approved. Other offices within the FDA include the Center for Biologics Evaluation and Research and the Center for Devices and Radiological Health. In deciding on drug approvals, the CDER relies on advisory committees to obtain outside opinions and advice. Advisory committees review the evidence and provide input on new drugs; major new indications for previously approved drugs; and requirements for new drugs, such as boxed warnings on drug labels. The CDER takes advisory committee recommendations under consideration, but they are not binding (CDER, 2007). The CDER follows many of the same procedures when it evaluates its portfolio
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Knowing what Works in Health Care: A Roadmap for the Nation of new products, which include vaccines and blood- and tissue-derived products. The process for obtaining FDA approval for devices is entirely different from the process for obtaining approval for drugs, and the standards for proving safety and efficacy are also different. All medical devices must be manufactured under a quality assurance program, be suitable for the intended use, be adequately packaged and properly labeled, and have establishment registration and device listing forms on file with the FDA. The manufacturers of only some classes of devices, however, must provide clinical data showing safety and efficacy. AHRQ’s Effective Health Care Program Under Section 1013 of the Medicare Prescription Drug, Improvement, and Modernization Act, Congress directed AHRQ to conduct and support research focused on patient outcomes; comparative clinical effectiveness; and the appropriateness of specific pharmaceuticals, devices, and health services. This AHRQ project, known as the Effective Health Care Program, incorporates three approaches as part of its work on comparative effectiveness: (1) knowledge synthesis through the EPCs (see below); (2) the generation of new knowledge through a network of research-based health care organizations with access to electronic health information databases and the capacity to conduct rapid-turnaround research; and (3) the translation of the research work into patient-oriented materials, conducted through the John M. Eisenberg Clinical Decisions and Communications Science Center (AHRQ, 2007b). Congress has appropriated $15 million annually for this effort. Syntheses of the Available Evidence Public and private organizations, such as AHRQ’s EPCs, the Blue Cross and Blue Shield Association (BCBSA) Technology Evaluation Center (TEC), the Cochrane Collaboration, the ECRI Institute, and Hayes, Inc., conduct syntheses of the available evidence (Table 2-1). These organizations provide systematic reviews, meta-analyses, and technology assessments that synthesize the available literature and describe what is known about the effectiveness of specific clinical interventions. Individuals and organizations use the syntheses of the available evidence that these organizations produce in a number of ways. Public and private health plans use the information to inform their coverage decisions, professional and patient care organizations use the information to create practice guidelines, organizations that track provider performance rely on it to establish benchmarks of appropriate care, and the information is also
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Knowing what Works in Health Care: A Roadmap for the Nation TABLE 2-3 Examples of Organizations That Establish Clinical Guidelines and Recommendations Organization Description ACC/AHA The ACC has partnered with the AHA to develop guidelines for evidence-based cardiovascular care since 1980. Writing groups are specifically charged with performing a formal literature review, weighing the strength of evidence for or against a particular treatment or procedure, and including estimates of expected health outcomes when data exist. ACP In 1981, the ACP launched the Clinical Efficacy Assessment Project to evaluate advances in medicine and develop clinical practice guidelines based on the best evidence available. Current guidelines are based on evidence reports commissioned by AHRQ and produced by EPCs. ADA The ADA has established the Evidence Analysis Library, which consists of relevant nutritional research and evidence-based guidelines. AHRQ and USPSTF The U.S. Public Health Service convened USPSTF in 1984, and since 1998 it has been sponsored by AHRQ. The USPSTF consists of a panel of private-sector experts, and its recommendations are regarded as the “gold standard” for clinical preventive services. American Diabetes Association The American Diabetes Association funds research, publishes scientific findings, and conducts programs nationwide. Clinical practice guidelines and recommendations are developed from literature reviews by clinicians and are reviewed by the Executive Committee. ASCO ASCO convenes expert panels to develop clinical practice guidelines for methods of cancer treatment and care. The manual for generating these guidelines is updated regularly to reflect significant changes. NHLBI The NHLBI organizes voluntary expert panels to develop clinical practice guidelines related to heart, blood vessel, lung, and blood diseases in children and adults. NOTE: ACC = American College of Cardiology; ACP = American College of Physicians; ADA = American Dietetic Association; AHA = American Heart Association; ASCO = American Society of Clinical Oncology; NHLBI = National Heart, Lung, and Blood Institute. SOURCES: ACC (2007); ACP (2007); ADA (2007); AHRQ (2007a); American Diabetes Association (2007); ASCO (2007); Eagle and Guyton (2004); NHLBI (2007). impartial assessments of the scientific evidence to reach conclusions about the effectiveness of a broad range of clinical preventive services, including screening, counseling, and preventive medications. Its recommendations are intended for use in the primary care setting. Under contract to AHRQ, an EPC conducts systematic reviews of the
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Knowing what Works in Health Care: A Roadmap for the Nation evidence on specific topics in clinical prevention that serve as the scientific basis for USPSTF recommendations. The USPSTF reviews the EPC report, estimates the magnitude of benefits and harms for each preventive service, reaches consensus about the net benefit for each preventive service, and issues a recommendation. Performance Measurement Organizations A number of organizations track and evaluate provider performance by measuring their actual clinical practices against the recommended practices (Table 2-4). To conduct this work, performance measurement groups first establish standards of care against which the performance of providers can be assessed. These are based on the available evidence and the guidelines issued by professional groups. In many cases, however, adequate guidelines are not available or are not evidence based, and this has been a significant barrier to the development of performance measures. Significant Challenges Although the U.S. system for the development, synthesis, and application of clinical evidence has expanded and improved over the past several decades, it continues to face significant challenges. Among these are the persistent gaps in the information available to decision makers, as well as the confusing manner in which the information is presented (e.g., different organizations use different coding schemes to represent similar concepts). Moreover, the quality of the information is often suspect because of a lack of transparency regarding the methods used to generate the information as well as conflict of interest concerns. In addition, inefficiencies in the current system that result from duplications of effort mean that fewer resources are available to fill the remaining information gaps. These concerns are detailed below. Unmet Information Needs Physicians now have access to a vast amount of relevant clinical information, but often this information is difficult to navigate and it may not address their specific concerns (Tunis, 2005). New tools, such as the Up-to-Date database and the American College of Physicians’ Physicians’ Information and Education Resource are bringing more information directly to physicians’ offices, but uncertainties about the quality and the applicability of the evidence remain. The available information may not be suitable to the clinician’s needs for a number of reasons. For example, although the provider may want to
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Knowing what Works in Health Care: A Roadmap for the Nation TABLE 2-4 Examples of Organizations That Measure Performance Organization Description AQA Alliance In 2004, the American Academy of Family Physicians, the American College of Physicians, and America’s Health Insurance Plans joined with AHRQ to create the AQA Alliance (originally the Ambulatory Care Quality Alliance). The AQA Alliance has developed a collaborative process in which physicians, consumers, purchasers, health insurance plans, and others develop strategies for measuring performance at the physician or group level; collecting data; and reporting the information to consumers, physicians, and other stakeholders. The Joint Commission (formerly JCAHO) A nonprofit organization established in 1951, the Joint Commission evaluates 15,000 health organizations in the United States and provides accreditation to those meeting its quality standards. The Joint Commission sets standards to ensure the quality and the safety of the care provided. Performance measures supplement the standards-based survey process by providing specific performance targets, allowing ongoing performance monitoring, and working toward continuous improvement. NCQA A nonprofit organization founded in 1990, the NCQA accredits health organizations to provide consumers and employers with an indicator of quality. The NCQA develops quality standards and performance measures, building consensus among large employers, policy makers, physicians, patients, and health plans to decide what aspects of quality to measure, how to measure it, and how to promote improvement. The NCQA tracks quality through the Health Plan Employer Data and Information Set and publishes annual reports on its findings. NQF A nonprofit membership organization founded in 1999, the NQF was established as a public-private partnership to promote a common approach to measuring and reporting health care quality. The NQF includes participation from consumers, public and private purchasers, employers, professionals, provider organizations, health plans, accrediting bodies, and others. Its goals are to promote collaborative efforts, develop a national quality measurement and reporting strategy, standardize health care performance measures, promote consumer understanding of quality information, and promote an enhanced system capacity for evaluation. NOTE: JCAHO = Joint Commission on Accreditation of Healthcare Organizations; NCQA = National Committee for Quality Assurance; NQF = National Quality Forum. SOURCES: AQA Alliance (2006); The Joint Commission (2007); NCQA (2007); NQF (2007). know how a particular intervention is likely to affect patients with multiple comorbidities, such patients are frequently excluded from research studies and are often not covered by clinical guidelines (Boyd et al., 2005). In addition, relatively little is known about interventions for rare diseases
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Knowing what Works in Health Care: A Roadmap for the Nation (European Organisation for Rare Diseases, 2005). Moreover, even though the evidence that is presented in systematic reviews may be comprehensive, it does not necessarily come in a form that is meaningful to doctors. For example, review documents typically summarize treatment effects in terms of relative risk, which does not take into account the prevalence of the disease. They also may not account for the presence of comorbidities. Physicians may prefer to make treatment decisions according to the absolute risks and benefits of treatment (presented as the number of events per 100 patients treated or the number of patients who need to be treated to prevent a single event) (Jackson and Feder, 1998). Consumers also have unmet information needs. Direct-to-consumer advertising encourages greater spending on prescription drugs, which may potentially avert the underuse of medication but which may also promote medication overuse (Donohue et al., 2007). Consumers need to know when claims are valid and apply to them and when the claims are exaggerated or irrelevant to their needs. Physicians must be prepared to respond to consumer requests for information on heavily marketed prescription drugs and other clinical services, and they are also the target of aggressive sales efforts by pharmaceutical representatives (Angell, 2004). Inconsistent Coding The organizations that provide systematic reviews and clinical guidelines use different grading systems to characterize the quality of evidence and the strength of recommendations. These codes fall primarily into four categories: letters only (e.g., A, B, and C), Roman numerals only (e.g., I, II, and III), mixed letters and numerals (e.g., Ia, Ib, and IIa), and terms (e.g., strong and weak or consistent and inconsistent) (Schünemann et al., 2003). The discrepancies among grading systems cause difficulties for end users, who must decipher and remember what each of the various designations means. AHRQ identified more than 100 scales, checklists, and other instruments used to rate the quality of individual studies and the strength of bodies of evidence (AHRQ, 2002). Transparency Although by definition systematic reviews are supposed to use scientific methods to synthesize the available evidence, the organizations that produce these syntheses do not always make the processes and deliberations that they used public and transparent. Few organizations depend on an externally reviewed protocol to conduct their reviews. Consequently, the steps taken to address some of the difficult—often very subjective—elements of the synthesis process, such as the basis for including or excluding particular
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Knowing what Works in Health Care: A Roadmap for the Nation articles from reviews, are not apparent. Moher and colleagues (2007) assessed 300 systematic reviews and found that only 56 percent reported their full literature search strategy. The same concerns apply to all evidence reviews, whether they are conducted by the various professional and advocacy groups or by government organizations. Whereas some groups closely adhere to evidence-based principles in supporting their clinical recommendations, many do not (Shaneyfelt et al., 1999). As a result, transparency is a key concern. One large study found that 87 percent of the clinical practice guidelines did not say whether a systematic search for published studies had been conducted (Grilli et al., 2000). Under those circumstances, users will have difficulty assuring themselves that the evidence is truly comprehensive or whether a subjective selection process has transpired. The lack of availability of transparent methods sections in evidence reviews reduces the ability of these users to make conscientious comparisons of guidelines addressing the same topic. Financial Interests A number of questions regarding the objectivity of organizations that develop practice guidelines have been raised. Professional societies, for example, may be subject to pressures from parts of their constituencies and individuals who have a substantial economic or professional stake in the intervention being considered, and these pressures have the potential to bias the guideline development process (Schwartz, 1984). Moreover, guideline development groups may receive funding from organizations affected by the findings, leading to concerns about the objectivity of their conclusions (Saul, 2006). Panels supported by public-sector organizations, such as the FDA and the NIH, have also been criticized for including panelists with financial ties to the manufacturers whose products are affected by the decisions. For example, among the nine NIH panelists who produced guidelines recommending lower cholesterol targets in 2004, six had each received research grants, speaking honoraria, or consulting fees from at least three—and in some cases all five—of the statin manufacturers, which stood to profit from the decision. Only one panel member had no financial ties of some type to statin manufacturers (Kassirer, 2004). Recently, these concerns have led to the development of more restrictive conflict of interest measures at the FDA and the NIH (NIH, 2004; Vedantam, 2007). Policy makers also become involved in decision making that is affected by private financial interests. One example is erythropoietin, an injectable drug used for the treatment of anemia in dialysis patients. In 2005, erythropoietin cost the Medicare program $1.75 billion—more than any other
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Knowing what Works in Health Care: A Roadmap for the Nation medication. The treatment of anemia focuses in part upon maintaining the level of hematocrit, a measure of red blood cell mass, within a target range. In 1989, the FDA established a recommended target hematocrit level of 30 to 33 percent. Under lobbying pressure from manufacturers, Congress encouraged CMS to broaden its payment policy, and in 2006 CMS allowed the target range to extend to 39 percent and above. This increase had a substantial impact on treatment utilization and cost. However, several studies showed that dialysis patients assigned to higher hematocrit target levels did not have better rates of survival, rates of hospitalization, or cardiac outcomes and in fact could be prone to adverse cardiovascular events, including myocardial infarction, vascular access thrombosis, increased use of antihypertensive medications, and cerebrovascular events (Cotter et al., 2006). In a report released in 2007, the FDA indicated that it had found no evidence indicating that the anemia medicines improved quality of life or extended survival in cancer or dialysis patients. In fact, several studies suggested that the drugs can shorten patients’ lives when they are used at high doses (Berenson and Pollack, 2007). A CMS coverage decision in 2007 stated that the evidence was sufficient to conclude that treatment with an erythropoiesis-stimulating agent is not reasonable and necessary for beneficiaries with certain clinical conditions, such as anemia associated with the treatment of leukemia (CMS, 2007a). Unnecessary Duplications of Effort In general, current efforts to assess clinical effectiveness are poorly coordinated, and there are significant duplications of effort (Hibble et al., 1998; Silagy et al., 2001; Timmermans and Mauck, 2005). Multiple stakeholders expend considerable resources essentially repeating work that has been done elsewhere or adding to that work. Frequently, the professional societies and payers that use evidence assessments as a basis for their decision making conduct their own supplementary evidence assessments if an existing synthesis is poorly done, not transparent, or out of date. Many organizations may believe that they must review bodies of evidence—and often the same bodies of evidence—as part of their professional obligation. The list of organizations that add their voice is long and diverse: professional societies, individual physicians, health plans and purchasers, patients and consumer advocacy groups, producers of consumer decision aids, trade associations, manufacturers, public and private systematic reviewers, health services researchers, universities, think tanks, consultancy groups, Medicare contractors, federal regulators, NIH panels, state and federal policy makers, state and federal courts, and even the media. Not surprisingly, this often results in a cacophony of voices that in the
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