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Approaches to Assessing Value— Illustrative Examples

INTRODUCTION

The rising healthcare costs in the United States in the face of global economic turmoil underscore the necessity for a health system that identifies and eliminates low-value services, minimizes inappropriate use of medical services, and responds to the explosion of costly new technologies, thus positioning value as a key cornerstone to improving the quality of care delivered in this country (Clancy, 2008; Leavitt, 2008; Paulus et al., 2008). In workshop discussions, participants repeatedly suggested that creating a system that encourages and incentivizes the delivery of high-value services relies first on creating a common approach to defining and assessing value in health care.

Emerging from the presentations and dialogue at the workshop session on approaches to assessing value was the importance of perceptions and perspectives—the meaning of value changes as the stakeholders change. L. Gregory Pawlson discusses methods of estimating the value of physicians on both individual and group levels and the importance of measuring quality, resource use, and cost. He discusses the strides made in value measurement of providers and outlines the steps necessary to expand on prior work in a manner that will allow accurate, informative, and comparative assessments of efficiency and value in health care.

Since surgical care accounts for more than 40 percent of overall spending for inpatient care (National Center for Health Statistics, 2006), developing approaches to assess and estimate the value of individual surgical and interventional procedures is paramount. Justin B. Dimick highlights two



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3 Approaches to Assessing Value— Illustrative Examples INTRODUCTION The rising healthcare costs in the United States in the face of global economic turmoil underscore the necessity for a health system that identifies and eliminates low-value services, minimizes inappropriate use of medical services, and responds to the explosion of costly new technologies, thus positioning value as a key cornerstone to improving the quality of care delivered in this country (Clancy, 2008; Leavitt, 2008; Paulus et al., 2008). In workshop discussions, participants repeatedly suggested that creating a system that encourages and incentivizes the delivery of high-value services relies first on creating a common approach to defining and assessing value in health care. Emerging from the presentations and dialogue at the workshop session on approaches to assessing value was the importance of perceptions and perspectives—the meaning of value changes as the stakeholders change. L. Gregory Pawlson discusses methods of estimating the value of physi- cians on both individual and group levels and the importance of measuring quality, resource use, and cost. He discusses the strides made in value mea- surement of providers and outlines the steps necessary to expand on prior work in a manner that will allow accurate, informative, and comparative assessments of efficiency and value in health care. Since surgical care accounts for more than 40 percent of overall spend- ing for inpatient care (National Center for Health Statistics, 2006), develop- ing approaches to assess and estimate the value of individual surgical and interventional procedures is paramount. Justin B. Dimick highlights two 9

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0 VALUE IN HEALTH CARE domains of surgical value: the value of surgical interventions and the value of individual providers, including both surgeons and hospitals. He discusses methods of measuring costs and outcomes in both of these domains and additionally surveys public policy options for improving value in surgery. Howard P. Forman explores the challenges to determining the cost- effectiveness of diagnostic imaging and argues that better, more widely available, cost-effectiveness information could be an important compo- nent of stemming the growth of unnecessary imaging. David O. Meltzer focuses on the medical cost-effectiveness of preventive services and wellness approaches, concluding that prevention can be, but is not invariably, a short- or long-term cost-effective approach to improving health. Newell E. McElwee examines the issue of determining the value of pharmaceuticals, specifically discussing decision points along the pharmaceutical life cycle. He also emphasizes that the value of pharmaceuticals varies depending on the specific decision considered and the preferences of the stakeholder making that decision. Presenters also focus on assessing the value of diagnostic tools and devices. Ronald E. Aubert proposes a framework for evaluating the poten- tial value of pharmacogenetic diagnostics, providing a case study of how applying pharmacogenetic data to the dosing of warfarin, a blood thinner, could reduce adverse events and yield cost savings to the healthcare sys- tem. Parashar B. Patel concludes the chapter by discussing the impact of evidence requirements for medical devices on innovation and assessment of value from a device manufacturer’s perspective and the need for cross- stakeholder collaborative efforts in order to preserve incentives for innova- tion and discovery. MEASURING VALUE OF AMBULATORY CARE SERVICES L. Gregory Pawlson, M.D., M.P.H., National Committee for Quality Assurance Measurement of value in health care is an increasingly important goal, given assessments that indicate less benefit from and higher cost for services provided in the United States versus countries of comparable wealth, as well as multiple studies pointing out apparent waste and less than desir- able quality of care (Fisher et al., 2003; McGlynn et al., 2003). However, defining value, let alone measuring it, is very challenging in health care, where neither benefits provided nor resources used to create the benefits are straightforward. Although there have been a considerable number of research studies using various econometric approaches to cost and benefit determination in health care, there is as yet no standard practice for mea- suring value or even an agreed-upon definition of value.

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 ILLUSTRATIVE EXAMPLES Regardless of the challenge, accurate, valid, and reliable formulations of both the benefit and the cost portions of the value equation are abso- lutely critical to any hope of creating a “value-based” or value-driven healthcare system. Limitations of Current Approaches The most widely available and relatively easily accessible data sources for determination of quality and cost are so-called claims data (data on services—visits, procedures, laboratory services, and medications dis- pensed) provided by clinicians or others and submitted for payment to insurers. Claims data are intended to document the minimal data required for payment (most often under fee for service) and in many instances do not accurately reflect the actual services provided, the diagnoses to which the services were actually linked, or in some instances, which clinician actually provided the services. Moreover, major gaps in the completeness of claims data can seriously affect their utility in either quality or resource use-cost determinations (Pawlson et al., 2007). Careful audit procedures that look at such areas as sampling framework, completeness of data extraction, and other oversight are critical to using claims data for resource use-cost pur- poses. To provide valid and reliable information for most quality measures, intensive effort is required to abstract information from existing paper medical records. While the increasing use of electronic medical records (EMRs) may ameliorate this issue to some degree, many current EMRs lack adequate documentation and search capabilities that are crucial for their potential use in quality measurement. This gap is largely due to the fact that many EMRs were designed to mirror billing systems or paper records, not to facilitate systemic data collection on clinical care. Surveys, although a critical source of information on some aspects of patient experience of care, are of necessity based on patient recall and interpretation of events and, because of this, provide limited information in some instances. Even where reliable and valid measures exist, limitations of the data are also reflected in the narrow breadth of available quality measurements. Until recently, except for a short-lived effort by the Centers for Medicare and Medicaid Services (CMS; the Health Care Financing Administration at the time) to generate national standardized comparison data from hospitals on coronary artery bypass graft surgeries, there are very few widely avail- able standardized comparison data at any level (physician, group, hospital, or health plan) beyond regional or national comparisons. The Healthcare Effectiveness Data and Information Set (HEDIS) is one example of a widely available standardized set of comparison data, but it is available only at the health plan level. Moreover, since the development of HEDIS was driven primarily by consumers and purchasers concerned about the potential nega-

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2 VALUE IN HEALTH CARE tive impact of health plans and capitation on quality through underuse of services (e.g., not providing screening for breast cancer), HEDIS measures, until recently, were focused almost exclusively on problems of underuse at the plan level. There has been substantial recent effort by CMS and others to extend publicly available quality measurement to other levels of the system. In some instances these efforts have been accompanied by calls (and, in some cases, funding) for the development of a broader range of clinical structure, process, and outcome measures of quality and measures related to overuse, misuse, resource use-cost, and patient experiences of care. However, we are still far behind where we need to be to assess value broadly in the healthcare system. Moreover, creating measures in areas such as overuse, appropriate use, misuse, and resource use-cost is proving to be very challenging. Con- sider that Brook and colleagues demonstrated in the 1980s that much care cannot be categorized definitively as appropriate or inappropriate and little correlation exists between rates of inappropriate care and service utiliza- tion in a given region (Chassin et al., 1987; Park et al., 1986). David Eddy has noted that structural issues related to the nature of clinical medicine, such as relative rarity of key outcomes, remote times between interventions and outcomes, the heterogeneity of practice populations of different physi- cians, and inherent uncertainty in disease outcomes, pose major barriers to measurement, especially at more granular levels of the system such as hospitals or physician office practices (Eddy, 1998). While risk adjustment offers some hope of adjusting for some of the differences created by these factors, there is broad consensus that current risk adjustment approaches are far from ideal or adequate. Finally, research looking at the relationship between relative quality achieved and relative resources used has shown that the relationship is complex. Fisher and colleagues found that despite the use of 60 percent more care for hospitalizations, specialist care, and major tests in the last six months of life of Medicare patients in high-cost regions of the United States, the quality of care in high-cost regions appears actually to be lower (Fisher et al., 2003). Our own research has suggested small but significant negative correlations between higher quality and lower resource use for inpatient hospitalizations and positive correlations between higher quality and higher resource use for medications at the health plan level (O’Connor et al., 2008). Measuring Value at What Level of Care? The National Academy of Engineering and Institute of Medicine (2005) report Building a Better Delivery System: A New Engineering/Health Care Partnership described multiple levels of the healthcare system, ranging from the patient to the environment (defined as entities such as insurers

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 ILLUSTRATIVE EXAMPLES or regulators that do not deliver health care directly but influence the care delivered). In ambulatory care, quality could be examined at the indi- vidual physician, group, integrated delivery system, regional, or national level. Measurement at the individual physician level is appealing from the standpoint of accountability and “actionability.” Moreover, if information generated from a given physician’s patient chart is used, there is no problem with relating a given action to a specific patient and physician. However, both quality and costs are often “generated” at a higher level of the system. For example, many, if not most, patients with multiple chronic conditions interact with a substantial number of clinicians over the course of a single year. These multiple interactions represent a web of health care that can- not be captured by examining individual physician-patient interactions in a group of patients. Attribution of clinical measurement and cost to a single clinician is also problematic because much of the variance in costs or quality does not appear to reside at the level of the individual physician (O’Connor et al., 2008). This, coupled with the inherently wide variation in resource use-cost, especially where inpatient or surgical-procedure use is involved, the aforementioned heterogeneity of patients among practices, and the relatively small numbers of patients with a given condition in an individual physician practice, places severe limits on measurement, espe- cially for public reporting or accountability at the individual physician or even the small-group level. The National Committee for Quality Assurance (NCQA), as promulgated in its Physician-Hospital Quality reporting stan- dards, has indicated, based on a number of studies within and external to NCQA, that for quality measures, at least 30 patients are needed to obtain a reasonably low probability of misclassification, but adherence to the more stringent criterion of a 90 percent confidence interval or a reliability coefficient of 0.7 is highly desirable (Scholle et al., 2008). For resource use-cost measures, given widely variable confidence intervals depending on the specific resource use category and disease, there is no defined minimal sample size; thus, only a calculated confidence interval (CI) of 0.9 or greater or a reliability coefficient of 0.7 would be acceptable. Indeed, to achieve a calculated CI of 0.9 appears to require a sample size of more than 100 patients for even the most reliable resource use measures, and in most instances the number required exceeds 500. Thus, while physician-level measurement may provide important feedback for individual practitioners, data derived from small sample sizes cannot reliably be generalized to the practice of medical care at the broader system level. To overcome these problems with sample size requirements and mis- classification, both quality and resource use related to accountability should most often be measured at some level higher than the individual physician, such as the group or integrated delivery system (contractual or virtual) level. By examining clinical care patterns and use from the organizational

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 VALUE IN HEALTH CARE level of physician practice groups, much richer information about the rela- tionships between quality and care emerge, especially for patients with mul- tiple chronic conditions. System-level measurements also promote a sense of shared accountability for healthcare costs and outcomes. Within a system, data on individual physician performance, although not sufficiently robust for public reporting, can serve as the basis for feedback and discussion of performance. While there are relatively few functionally integrated health delivery systems that can facilitate these system-level assessments of value, research is critically needed to explore how to create or assign individual clinicians to virtually determined delivery systems (on the basis of hospital use, referrals to other physicians, etc.). Moving to Measurable Clinical Efficiency The concept of “measurable clinical efficiency” addresses using a set of quality measures as a proxy for benefit and a set of resource use measures as a proxy for the cost function (Table 3-1). As illustrated in Table 3-1, such value assessments would include mea- surements of misuse, overuse, and underuse in evaluating the quality func- tion and use of various types of resources for the resource use-cost function. Resource use in this respect can be measured using disease- or condition- specific claims, defined episodes delineated by “clean claims periods,” and sorting costs exclusively into those episode groups or by looking at total costs for all services for a defined group of patients for a defined period of time. Either actual (defined by claims paid or allowable charges) or stan- dardized prices can be used since both have their advantages and disadvan- tages. All of these approaches imply looking at both quality and cost over TABLE 3-1 Measurable Clinical Efficiency—Measures of Quality and Their Associated Outcomes Measures of Underuse: Appropriate Overuse: Misuse: provision of quality of needed use: provision provision of potentially harmful care services not of needed unnecessary services provided services services Cost-waste Avoidable Excess Cost of Cost of misuse outcomes consequences cost-use for overuse appropriate care Clinical Clinical outcomes and patient experience outcomes Total cost-use Aggregate cost-relative resource use

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 ILLUSTRATIVE EXAMPLES time and different entities, rather than in a single place at a single time as with most current quality measurement. Measurable clinical efficiency can be reported for improvement or accountability purposes by combining composites of quality with resource use-cost measures in the same population of patients. The composites can be displayed in various combinations (ratios, scatter plots, relative “star” ratings, etc.). As noted before, the choice of what level of the healthcare system (e.g., individual clinicians, sites, groups, integrated delivery systems, health plans) to attribute measures of quality and resource use needs to be balanced with important trade-offs. Finally, further research to explore the relationships between quality and cost and what elements of the system have an impact on these measures is critical, as is continuing to set reason- able rules and standards for fairness and accuracy of measurement. Conclusion Limited transparency and problems with reliability of measurement hinder resource use-cost and quality measurements, and current tools pro- vide only an initial starting point for combining these areas to determine value. Further research and development to develop reliable and valid measures of appropriateness of care and additional measures of overuse and misuse of clinical care as well as resource use measurement, is critical. Consideration must also be given to the development of measures of clini- cal outcomes at group, network, and plan levels. “Composite” measures incorporating clinical performance and intermediate outcomes in quality and resource use measures at multiple system levels need to be developed to allow comparative assessment of efficiency and value. As electronic medical records evolve and their capacity expands, attention should be paid to the types of data needed to assess the aspects of care related to value. Only with concerted and sustained attention to these interim steps can actual value to health care can be measured and used to improve quality and reduce waste in our healthcare system. ASSESSING THE VALUE OF SURGICAL CARE Justin B. Dimick, M.D., M.P.H., and John D. Birkmeyer, M.D., University of Michigan Surgery accounts for a large proportion of healthcare services in the United States. The number of patients undergoing inpatient surgery doubled from 2000 through 2006 (from 23 million to 46 million) (National Center for Health Statistics, 2006). Surgical care also comprises a major compo- nent of healthcare expenditures, exceeding 40 percent of overall spend-

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 VALUE IN HEALTH CARE ing for inpatient care (National Center for Health Statistics, 2006). With healthcare costs skyrocketing, any effort to curtail their growth will have to include surgical care. Payers and purchasers also increasingly recognize that costs must be controlled without sacrificing quality. Consequently, their focus has shifted to optimizing value, rather than considering quality or costs in isolation. When assessing the value of surgical care, there are two perspectives to consider. The first perspective—the value of surgical interventions— considers the value of surgery, relative to other approaches, for treating specific conditions. Often referred to as “technology assessment,” this per- spective uses the tools of evidence-based medicine to evaluate the effective- ness and cost-effectiveness of new interventions. Identifying and eliminating surgical services of no value (waste) or low value will reduce healthcare spending without impacting quality. Motivated by the widespread variations in outcomes and costs across providers, the second perspective assesses the value of specific surgical providers relative to others. Value assessment in this context, provider profiling, is particularly timely and is the focus of several public reporting and value-based purchasing efforts. Value can be optimized by directing patients to the highest-value hospitals and surgeons—those that provide high-quality, efficient health care. Assessing the value of surgical care is challenging. This paper surveys existing tools—what we have—and tools on the immediate horizon—what we need—for value assessment in surgery. Within each perspective, we consider the evaluation of two key domains: outcomes and cost. We close by considering policy approaches for using the tools discussed to improve value in the context of surgical care. Assessing the Value of New Surgical Inventions The last decade has seen explosive growth in new medical technology. While this trend is pervasive in medicine, it is disproportionately focused in procedural specialties, especially surgery. There are new surgical procedures for conditions that were previously not treated. For example, bariatric surgery for morbid obesity has increased tenfold over the past decade and is now the second most common abdominal operation in the United States (Santry et al., 2005). There are also new, less invasive procedures that replace existing surgical procedures. For example, endovascular repair of aortic aneurysms has largely replaced the conventional, open surgical pro- cedure (Schermerhorn et al., 2008). New technology is an important driver of healthcare cost growth (Baker et al., 2003; Fuchs, 1999). There is general consensus among economists, policy makers, and healthcare purchasers that the introduction of new

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 ILLUSTRATIVE EXAMPLES surgical procedures, pharmaceuticals, and diagnostic imaging increases healthcare spending. However, there is extensive debate regarding the value of this new technology—whether the benefits are worth the costs (Cutler and McClellan, 2001). Understanding the value of new surgical interven- tions requires an evaluation of both outcomes and costs. Evaluating Outcomes Comparing the effectiveness of new surgical interventions is tradition- ally the domain of evidence-based medicine. Principles of evidence-based medicine are central to the assessment of the value of novel therapies, including pharmaceuticals, medical devices, and surgical procedures. The goal of this assessment is to understand the comparative effectiveness and cost-effectiveness of new interventions. Because these tools are no different for surgery than for other new technologies or interventions and are con- sidered elsewhere in this report, we consider them only briefly here. Comparative effectiveness is evaluated by critical examination of ran- domized clinical trials and observational studies. The goal of these studies is to quantify the net benefit, in terms of healthcare outcomes, of the new surgical intervention compared to the next best alternative. Randomized trials, which minimize baseline differences in comparison groups, are widely considered the gold standard for evaluating new interventions. However, observational studies are important for two reasons. First, observational trials are sometimes the only option. In many situations, randomized trials are not feasible due to expense or a lack of clinical equipoise. Second, observational studies, particularly if they are population based, provide an estimate of the effectiveness of an intervention in the “real world.” In con- trast, randomized trials provide evidence of efficacy in a narrow, carefully selected subpopulation. Carotid endarterectomy, a procedure to prevent stroke, is one example in which observational studies made a contribution beyond the randomized trials. For this procedure, randomized clinical trials and population-based studies yielded very different estimates of surgical risk. Using the national Medicare population, Wennberg and colleagues demonstrated that out- comes after carotid endarterectomy were much better in hospitals that par- ticipated in the randomized trials compared to other, lower-volume facilities (Wennberg et al., 1998). Because surgical decisions are made by weighing the risks versus the benefits of the procedure, these population-based esti- mates of surgical outcomes are necessary to guide decision making and to understand the value of a surgical intervention in the real world. Although the basic tools for evaluating comparative effectiveness exist, several challenges must be overcome. First, we need to address the paucity of evidence evaluating new interventions (Phillips, 2008). In the United

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 VALUE IN HEALTH CARE States, we have an undeveloped infrastructure for evaluating evidence. For primary evidence of benefit, we often rely on trials initiated by investiga- tors or industry. For synthesis studies, such as meta-analysis, we rely on networks of volunteers, such as the Cochrane Collaborative. A national infrastructure for setting priorities and funding studies is a necessary first step in filling the evidence void. The second challenge we need to address is the rapid uptake of unproven surgery. New surgical techniques often become widespread prior to good evidence of their benefit. This premature diffusion may be due to the lack of regulatory oversight of surgical tech- niques and devices. There is currently no gatekeeper, analogous to the Food and Drug Administration (FDA), to prevent new surgical technologies from being adopted prior to good evidence of their benefit. Strengthening the link between evidence and insurance coverage would also help slow the premature adoption of new technology. Currently, we rely on individual payers to evaluate and make coverage decisions on most interventions. The Medicare Evidence Development & Coverage Advisory Committee (MEDCAC) was recently created to advise the Centers for Medicare and Medicaid Services on national coverage decisions (Holloway et al., 1999). While this effort is no doubt a good start and provides a framework on which to build, it currently evaluates a small fraction of new interventions. Evaluating Costs The costs of new interventions must also be considered. In assessing new technologies, the costs of an intervention must be considered in the context of its clinical benefit. While some new interventions are actually cost-saving, most result in an incremental increase in healthcare costs. Cost-effectiveness is a formal method for integrating evidence of benefit with information on costs. The cost-effectiveness of new interventions is evaluated as the incremental benefit divided by the incremental cost, rela- tive to the next-best alternative. Most often, cost-effectiveness is evaluated using decision analytic techniques, and reported as the cost (in dollars) per quality-adjusted life-year (QALY). The best evidence regarding effec- tiveness, as described in the section above, is used in the numerator. The incremental cost (the denominator) is often the most challenging estimate to obtain. Good estimates of intervention costs must be performed from the societal perspective; these often include the costs of the intervention itself, other healthcare costs, and indirect costs to society (e.g., time lost from work). Although the tools of cost-effectiveness are also well developed, there are still important challenges to overcome. First, we must address the inconsistent application of cost-effectiveness methods. For example,

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9 ILLUSTRATIVE EXAMPLES a recent review of studies focusing on the cost-effectiveness of carotid endarterectomy found tremendous differences across studies. Divergent conclusions of cost-effectiveness were reported from studies that addressed the same questions and used similar inputs (Holloway et al., 1999). For an asymptomatic patient, the cost-effectiveness varied from 1.8 months at a cost of $52,700 per QALY to 3 months at a cost of $8,004 per QALY. Until this problem is addressed, critics will continually point to the inconsistent results of cost-effectiveness studies. Although we have the necessary tools to evaluate effectiveness and cost- effectiveness, we clearly need a central organization for applying them in a uniform manner. There are obvious precedents. For example, the National Institute for Health and Clinical Excellence (NICE) was established as a part of the British National Health Service in 1999 (Pearson and Rawlins, 2005). NICE was created to set standards for the adoption of new health- care technologies and explicitly take into account both clinical effectiveness and cost-effectiveness. Some advocate the creation of a similar organization in the United States. With the creation of such an organization, we would make the necessary first step toward improving the value of surgery by identifying and potentially reducing the use of surgical services with small (or expensive) marginal benefits. Assessing the Value of Hospitals and Surgeons The second perspective to consider is the value of surgical providers— surgeons and hospitals. Motivated by the widespread variations in use, quality, and costs across surgical providers, this perspective is particularly timely and is the focus of several public reporting and value-based purchas- ing efforts. Profiling Outcomes Empirical data from numerous sources reveal widespread variations in morbidity and mortality after surgery. Recent data from the 123 hospi- tals participating in the National Surgical Quality Improvement Program show that morbidity rates after colon surgery range from 3 to 23 percent, even after adjusting for differences in patient’s baseline risk (Figure 3-1). Knowledge of these variations has led to an unprecedented number of efforts aimed at measuring surgical quality. Unfortunately, these efforts are hindered by a lack of good measures. The measures we currently have—individual quality indicators—are severely limited (Birkmeyer et al., 2004). Hospital morbidity and mortality rates are often too “noisy” due to the small number of cases performed at individual hospitals (Dimick et al., 2004). Hospital volume, widely used in

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00 VALUE IN HEALTH CARE ingly tied to participation in such studies, and this appears to be a promis- ing concept in certain instances if research can be efficiently and adequately designed to answer critical questions regarding clinical value. As pressure has grown for rational prioritization in health care as a means to control spending, economic evaluations have greatly increased for high-cost device technologies. While there is broad understanding that interventions should be worth their costs to society, methods for assessing economic value remain immature and we caution against simplistic use of blunt instruments such as cost-effectiveness in reimbursement and funding decisions. Methods to assess the clinical and economic value of device interven- tions must take into consideration the nature of innovation in the medical device arena. For example, newly developed procedures may not be ripe for a fair assessment since the procedural technique may still be undergoing refinement. Similarly, there may be only a small cadre of skilled and expe- rienced physicians performing the intervention. On the other hand, waiting until the technology matures may result in faster dissemination than desired by policy makers, particularly among populations that may not receive the greatest clinical benefits. We recognize that policy makers must assess and refine methods to determine the value of all types of treatment modalities, including device interventions. The goal is to provide comparative information to clini- cians, payers, and patients. However, ultimately, medical innovators need a predictable and reasonable framework in order to support development and commercialization of new medical devices in a society that still values technology advancement. While the bar continues to be raised in terms of clinical and economic evidence, we caution that the desire for additional evidence from clinical trials will always outpace our ability to perform them (Gelijns et al., 2005). Without proper application by policy makers to tailor requirements for different devices, there will be longer development time lines, reduced innovation, and fewer treatment options for patients. REFERENCES Advanced Medical Technology Association. 2008. The 0 (k) process: The key to effective device regulation. P. 25. AHRQ (Agency for Healthcare Research and Quality). 2006. Inpatient quality indicators com- posite measure. Draft technical report. http://qualityindicators.ahrq.gov/news/AHRQ_ IQI_Composite_Draft.pdf (accessed June 27, 2007). Appleby, J. 2008. The case of CT angiography: How Americans view and embrace new tech- nology. Health Aff (Millwood) 27(6):1515-1521. Bairstow, P., A. Dodgson, J. Linto, and M. Khangure. 2002. Comparison of cost and outcome of endovascular and neurosurgical procedures in the treatment of ruptured intracranial aneurysms. Australas Radiol 46(3):249-251.

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02 VALUE IN HEALTH CARE ———. 2008a. NCD for percutaneous transluminal angioplasty (PTA). Medicare coverage manual. 100-3. Department of Health and Human Services. Washington, DC: U.S. Government Printing Office. ———. 2008b. Posting of potential NCD topics: Proposed topic list for first quarterly release. Department of Health and Human Services. Chassin, M. R., J. Kosecoff, R. E. Park, C. M. Winslow, K. L. Kahn, N. J. Merrick, J. Keesey, A. Fink, D. H. Solomon, and R. H. Brook. 1987. Does inappropriate use explain geo- graphic variations in the use of health care services? A study of three procedures. JAMA 258(18):2533-2537. Cheng, A. K., and J. K. Niparko. 1999. Cost-utility of the cochlear implant in adults: A meta- analysis. Arch Otolaryngol Head Neck Surg 125(11):1214-1218. Cheng, A. K., H. R. Rubin, N. R. Powe, N. K. Mellon, H. W. Francis, and J. K. Niparko. 2000a. Cost-utility analysis of the cochlear implant in children. JAMA 284(7):850-856. Cheng, C. H., G. D. Sanders, M. A. Hlatky, P. Heidenreich, K. M. McDonald, B. K. Lee, M. S. Larson, and D. K. Owens. 2000b. Cost-effectiveness of radiofrequency ablation for supraventricular tachycardia. Ann Intern Med 133(11):864-876. Chernew, M. E., A. B. Rosen, and A. M. Fendrick. 2007. Value-based insurance design. Health Aff (Millwood) 26(2):w195-w203. Clancy, C. 2008 (September 27). Value-based purchasing, transparency and transformation. Keynote address for the Third Annual Health Information Technology Summit. Wash- ington, DC. Clyde, A. T., L. Bockstedt, J. A. Farkas, and C. Jackson. 2008. Experience with Medicare’s new technology add-on payment program. Health Aff (Millwood) 27(6):1632-1641. Cohen, J. T., P. J. Neumann, and M. C. Weinstein. 2008. Does preventive care save money? Health economics and the presidential candidates. N Engl J Med 358(7):661-663. Cutler, D. M. 2004. Your money or your life: Strong medicine for America’s health care system. xiv:158. Cutler, D. M., and M. McClellan. 2001. Is technological change in medicine worth it? Health Aff (Millwood) 20(5):11-29. Dartmouth University. 2008. Research agenda and findings. http://www.dartmouthatlas.org/ agenda.shtm (accessed January 11, 2009). ———. 2009. The Dartmouth atlas of healthcare. http://www.dartmouthatlas.org/ (accessed January 9, 2009). Deloitte Center for Health Solutions. 2008. The medical home: A solution to chronic care man- agement? http://www.deloitte.com/dtt/article/0%2C1002%2Csid%253d80772%2526cid %253d186574%2C00.html?wt.mc_id=indianapca (accessed January 11, 2009). Derdeyn, C. P., J. D. Barr, A. Berenstein, J. J. Connors, J. E. Dion, G. R. Duckwiler, R. T. Higashida, C. M. Strother, T. A. Tomsick, and P. Turski. 2003. The International Sub- arachnoid Aneurysm Trial (ISAT): A position statement from the executive committee of the American Society of Interventional and Therapeutic Neuroradiology and the Ameri- can Society of Neuroradiology. Am J Neuroradiol 24(7):1404-1408. Detre, K., R. Holubkov, S. Kelsey, M. Cowley, K. Kent, D. Williams, R. Myler, D. Faxon, D. Holmes, Jr., M. Bourassa, et al. 1988. Percutaneous transluminal coronary angioplasty in 1985-1986 and 1977-1981. The National Heart, Lung, and Blood Institute Registry. N Engl J Med 318(5):265-270. Deyo, R., and D. L. Patrick. 2005. Hope or hype: The obsession with medical advances and the high cost of false promises. New York: American Management Association. Dimick, J. B., H. G. Welch, and J. D. Birkmeyer. 2004. Surgical mortality as an indicator of hospital quality: The problem with small sample size. JAMA 292(7):847-851.

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