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Institute of Medicine (US) Committee on Technological Innovation in Medicine; Gelijns AC, Halm EA, editors. The Changing Economics of Medical Technology. Washington (DC): National Academies Press (US); 1991. (Medical Innovation at the Crossroads, No. 2.)

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The Changing Economics of Medical Technology.

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2The Diffusion of New Technology: Costs and Benefits to Health Care


The American public has a love-hate relationship with medical technology. Technologies are extolled for saving lives, improving health status, and improving the quality of care. At the same time technology is vilified as one dominant factor responsible for the continuing escalation of medical costs. Highly visible “big-ticket” items, such as organ transplantation, diagnostic imaging systems, and new biotechnology products attract a major share of both praise and blame.

Five facts about new medical technology underlie this paper. First, new technologies do, on average, improve the quality of medical care by improving health outcomes. This is not true of every technology in every clinical use, but it is true on average. Second, many new technologies are ineffective or redundant and do not improve health outcomes. The trouble is that it is not always easy to discriminate between effective and ineffective technologies at the time they are introduced. Third, new technologies do, on balance, add to health care costs. Some technologies may actually reduce costs by replacing more expensive alternatives or preventing expensive health consequences, but the overall effect is to increase costs. Fourth, the incentives and regulations built into the American health care sector lead to inappropriate diffusion of technologies, both underdiffusion of effective and cost-effective technologies, and overdiffusion of ineffective and cost-ineffective technologies. Reimbursement systems, professional reward structures, legal considerations, and patient demands all contribute to the problem. The fifth inescapable fact about new medical technology is that the American public cannot get enough of it. We demand the best and newest from our providers, and they are, in general, happy to oblige.

The problem is that costs continue to rise, and the ability of the public and private sectors to finance health care is being strained. American society is approaching, or may have reached, the point at which it is not possible to provide the best available health care to every American, regardless of cost. The de facto solution has been to restrict access to health care for a growing segment of the population—the uninsured—while preserving the myth of best available care for those fortunate enough to have coverage.

Upward pressures on health care costs will only increase in the 1990s. A growing array of new technologies will claim an increasingly large share of national resources. The birth cohort of 1945 to 1965, the “baby-boomers,” will move into the age range associated with increasing prevalence of chronic disease. Universal health insurance, in some form, may well be adopted. Any of these three forces will force hard choices, challenging the myth of “best available technology for all.” Medical technologies, especially new ones, will have to justify their costs in a climate of competing claims on resources.

This paper addresses four aspects of the relationship between new medical technology and costs. First, we review the evidence regarding the contribution of new technology to the aggregate cost of health care. Second, we review a normative model of optimal diffusion of technologies, based on evaluation of their cost effectiveness—that is, the ability of a technology to improve health outcomes. Third, we examine the influence of economic incentives that affect adoption of new technology in the U.S. health care system and contrast the resulting priorities with those derived from the normative cost-effectiveness model. We examine incentives for hospitals, fee-for-service physicians, and managed care organizations. We cite examples of incentives for underdiffusion of cost-effective technologies and overdiffusion of cost-ineffective ones. Finally, we comment on future policy options for achieving a more cost-effective pattern of technology diffusion.


Researchers generally agree that medical technology has contributed to rising health care costs (1-3). Health insurance removes financial barriers to consumers, thus raising demand for technology and inducing providers to offer a more expensive mix of services. But researchers have struggled to measure how much technology has contributed to increasing costs. Part of the difficulty lies in defining medical technology. The term is commonly defined broadly to include drugs, devices, surgical procedures, and organizational support systems within which medical care is delivered (4). Identifying the changes in cost attributable to these items in any given period is virtually impossible. Even if the more important innovations could be listed, it would be extremely difficult to trace their overall economic impact.

Another caveat is that the economic impact of a technology is often confused with the purchase price of a piece of equipment or a drug, or the fee paid to a surgeon. The total impact of a technology on health care costs is much broader than that and may include offsetting savings as well as induced costs. The direct cost of a capital-embodied technology includes not only the capital cost itself but also the operating costs required to implement it. The operating costs of even the most capital-intensive technologies may be greater than anticipated because of the need for operating and supervisory personnel, training, insurance, supplies, and space. A new drug or device, on the other hand, may be more expensive to purchase but less expensive to administer than its alternatives (5). Furthermore, a new technology may affect the utilization of other health services. These effects constitute the “induced” costs and savings of a technology. A new imaging device may lead to increased utilization of other tests for confirming a diagnostic hypothesis that would not otherwise have arisen, or the new technology may make other diagnostic procedures unnecessary. Treatments that would not have been considered may be induced by a new diagnostic test (6), or treatments may be avoided because the new technology offers an alternative course of action. Technologies and their induced procedures may lead to side effects and complications requiring further tests and treatments, or side effects and complications may be avoided if the new technology leads to a safer clinical strategy than was possible in its absence. Technology that extends life may require more extended periods of care, often at great expense and in institutional settings. Technology that prevents disease may save resources that would otherwise be required for diagnosis and treatment, although few preventive technologies are cost saving on balance (7,8).

Some researchers have tried to estimate the effect of technology on U.S. health care expenditures by first estimating the impact of other, more easily identifiable sources including price inflation and age-specific population growth (9,10). The portion of the increase in health expenditures not accounted for by these explanatory variables is attributed to technology. Such research does not draw distinctions between expanded applications of existing technologies and introduction of new technologies. Other researchers have sought to measure changes in the cost of treating certain illnesses over time (2,12-14). Still others have used case studies to analyze the impact of important technologies such as intensive care units and computed tomography (15,16).

All three approaches suffer from a variety of problems. For our discussion of the economics of new technology, these approaches are problematic because they do not distinguish between the impacts of new and existing technologies. In general, residual approaches do not pinpoint the precise cause of increases. Many studies attribute cost increases to an increase in “intensity per hospital admission,” which could be explained by non-technological factors, such as changes in the severity or nature of disease. In addition, these studies do not easily identify indirect costs of using new technologies, such as the need for more skilled hospital nurses and technicians, nor do they identify induced costs. Although the specific illness and case study approaches do analyze the impacts of particular technologies, it is difficult to generalize from them. Unlike cost-effectiveness research, to which we will return, this body of research does not attempt to relate cost increases to improvements in health outcome.

Empirical evidence from these types of studies suggests that medical technology accounts for about 10 to 40 percent of the increase in health care expenditures over time (1). Fuchs (3) concluded that technology contributed 0.6 percentage points of the 8.0 percent annual rate of increase in health expenditures from 1947 to 1967. Davis (9) found that technology accounted for about 25 percent of the increase in hospital expenses per admission between 1962 and 1968. More recently, Freeland and Schendler (10) reported that 21 percent of the rise in hospital costs between 1971 and 1981 was due to “intensity per admission.” The Health Care Financing Administration (HCFA) estimated that from 1985 to 1986, 35 percent of changes in personal health expenditures were accounted for by “consumption per capita” and the intensity of consumption because of such factors as demographic changes and changes in income level (11). Employing a specific illness approach, Scitovsky and McCall (2) found that, from 1951 to 1971, cost-increasing changes in treatments generally outweighed cost-saving changes. The main cost-increasing factor was the rise in the use of ancillary services, such as laboratory tests and X-rays. Fineberg (12) and others have also noted the high cost of clinical chemistry tests and other little-ticket technologies. Scitovsky (13) found that from 1971 to 1981 increases in the cost of ancillary services slowed, but several new and expensive technologies raised costs substantially. Showstack et al. (14) also found evidence that big-ticket items, such as intensive care unit management of the critically ill, caused large increases in the 1970s.

Researchers have shown that any individual technology makes a relatively small contribution to health expenditures. For example, a 1979 study found that a 50 percent reduction in the annual operating costs of four expensive technologies—computed tomography, electronic fetal monitoring, coronary bypass surgery, and renal dialysis—would yield savings of 1 or 2 percent of the nation's health expenditures (15). One exception is the use of intensive care units, which Russell found to account for about 10 percent of hospital expenditures in 1974 (16).


If new technologies increase health care costs, how much technology is appropriate? To judge whether the degree of diffusion of particular technologies or of technologies in general is appropriate, we need some standard or criterion. One such criterion is based on the proposition that the objective of medical technology is to improve health outcomes. Each clinical use of a technology utilizes some of society's limited health care resources and, ideally, improves health outcomes. The more the society spends on health care, the more health is improved. Moreover, there are diminishing returns to health care: the first billion dollars yields more health improvement than the six hundredth billion dollars. The more we expand the resources applied to health care, the more health can be improved but the higher the incremental cost per additional unit of health improvement.

The criterion for resource allocation that follows from this formulation of society's objectives is cost effectiveness: if a new technology produces health outcomes at a lower cost per unit than existing technologies, it should be adopted; otherwise, it should not. The principle is that clinical practices having low cost per unit of health benefit should have priority over practices having a higher cost per unit (17,18). Cost-effectiveness analysis has been used widely to assist policy formation and is gaining acceptance in the medical community as an appropriate criterion for resource allocation (18,19). Cost-effectiveness analyses of new medical technologies often are useful guides to their potential role in health care; one of the earliest examples was a cost-effectiveness analysis of hemodialysis in end-stage renal disease (20). This study, which projected a relatively low cost per year of life extension, probably influenced the decision by Congress to fund universal coverage under Medicare. A limitation of the study, to which we will return, was that it considered only the most favorable target group—the relatively young and otherwise healthy—and did not anticipate its expansion to older and sicker patients for whom the cost-effectiveness ratio is much higher. A barrier to applying cost-effectiveness analysis to new technologies generally is that decisions about adoption often are required before satisfactory data on effectiveness or even full cost are available.

Pharmaceuticals have probably received the most attention in cost-effectiveness analyses. Analyses of the drug cimetidine for peptic ulcer disease showed it not only to be cost effective but actually to give net savings relative to standard treatment (21,22). A study of the use of third-generation cephalosporins for hospital-acquired pneumonia also showed savings when compared to standard multiple-drug regimens, largely because of reduced costs of drug preparation and administration, monitoring, and side effects (5). Other drugs, although not cost saving, have been shown to have extremely favorable cost-effectiveness ratios in certain clinical uses. Beta-blockers following myocardial infarction, for example, have been shown to have a cost per year of life saved of from $2,400 for patients at high risk of subsequent infarction to, at most, $13,000 in patients at low risk. For other drugs, effects on quality of life are crucial, which has led to the use of quality-adjusted life years 1 as a measure of health outcome (23). Cost-effectiveness evaluations of antihypertensive drugs, for example, involve assessments of their effects on both quality of life and longevity (24). Diagnostic technologies have also been analyzed for their cost effectiveness. Unfortunately, many important imaging technologies, such as magnetic resonance imaging (MRI), have not been subjected to formal cost-effectiveness analyses because of the difficulty of attributing health benefits to the use of individual diagnostic modalities.

These and other examples illustrate a key lesson for cost-effectiveness research. A technology that is highly cost effective in one clinical situation can be extremely cost ineffective in others. Exercise tolerance testing is a cost-effective screening test for patients with chest pain (25) but not for asymptomatic patients (26). Coronary bypass graft surgery is relatively cost effective for patients with left-main coronary artery disease but not for patients with single-vessel disease (27). Cholesterol-lowering drugs probably are not cost effective for primary prevention of coronary heart disease in patients without other risk factors (28) but may well be cost effective, or even cost saving, in patients with established coronary artery disease or multiple risk factors in addition to high serum cholesterol.

The early lessons from the end-stage renal disease story suggest that even a clinically effective and cost-effective life-saving technology will diffuse into domains where it produces little additional health benefit at great additional cost. The Peter Principle says that employees will rise through the ranks until they reach their highest level of incompetence. The analog for diffusion of medical technology is that a technology will expand its use until it has found its way into medical applications that are cost ineffective. This presents a challenge for developers, utilizers, purchasers, and regulators of new technology: to permit adoption of cost-effective new technologies without allowing them to absorb significant resources for cost-ineffective uses.


We return now to the central question: do the economic incentives in the U.S. health care sector promote diffusion of cost-effective technologies? Health care financing in the 1970s and early 1980s—characterized by cost-based hospital reimbursement, fee-for-service physicians, and generous insurance plans—promoted rapid diffusion of new technologies whether they were cost effective or not. Since providers knew they would be reimbursed for their services, there was relatively little concern over whether technologies were cost effective. As long as technologies were perceived to offer marginal benefits over existing practices, there was pressure in the system to adopt them. As policy makers began to address soaring health care costs in the 1970s, medical technology was singled out as an important source of the problem. The title of a major conference in 1977 asked whether technology was the culprit behind rising health care costs (1). Payers began seriously questioning whether the nation's investment in high-technology medicine was worth the cost. Articles appeared advocating the use of cost-effectiveness analysis for guiding resource allocation (17).

Most observers understood, though, that the culprit was not medical technology so much as perverse incentives that insulated patients and providers from the costs of care. By devising systems with more appropriate incentives, policy makers hoped that resources, including those for new technologies, would be allocated more cost effectively. The widespread reforms of health care financing in this decade, including the adoption of the Medicare Prospective Payment System (PPS) and the rapid growth of managed care insurance plans, have created markedly different incentives for providers to adopt and use new technologies. But while these systems establish incentives for providers to be more cost conscious, they do not necessarily ensure adoption of cost-effective technologies. Let us consider the current incentives for three major players in the diffusion of technology: hospitals, managed care insurance plans (including health maintenance organizations), and physicians.


PPS may distort the adoption of cost-effective new technologies in several ways. Because it establishes fixed, predetermined payments per admission, PPS encourages hospitals to focus on short-run costs and reimbursement levels. But from society's point of view, the consequences of a new technology, in terms of its cost and health impact, are relevant for the duration of the patient's life. Under PPS, hospitals have a disincentive to provide new technologies that increase short-term costs, even if they save costs or offer substantial benefits in the longer run. From the hospital's perspective, diagnosis-related group (DRG) payment levels vie with, or even replace, health effectiveness as the measure of benefit associated with a new technology. PPS also creates an incentive for hospitals to shift services to outpatient settings, even if these services could be performed more efficiently on inpatients. Furthermore, the system favors capital-intensive technologies because capital continues to be reimbursed on a cost basis.

There are, of course, some countervailing incentives that tend to favor adoption of new technology in hospitals. Hospitals compete for patients and physicians by offering high-quality services that often depend on advances in technology. Ethical imperatives to give the best care to each patient and malpractice concerns tend to lead to use of technology. Physicians practicing in a hospital may be advocates for clinically effective technology regardless of bottom-line effects, but they may be as insensitive to cost as to revenue. Recent studies have shown that physicians are poorly informed about the cost of the services they order (29). The result is often conflict between administrators who are concerned with cost and revenue and physicians who are concerned with clinical effectiveness and satisfying patient and professional demands. Neither party reflects societal concerns for maximizing health outcome within budget constraints.

Two provisions of PPS—the annual update factor and recalibration of DRGs—mitigate disincentives to use costly new technologies, but they are likely to have little impact. The update factor, which increases the overall level of hospital reimbursement, increases per-patient hospital payments. But it fails to affect incentives at the margin because the additional funds are not necessarily earmarked to pay for the use of new technologies. The impact of the annual readjustment of DRG weights, which is intended to respond to the use of new technologies for specific diagnoses, is limited because of major time lags between the diffusion of new technologies and readjustment of weights. Since hospitals ultimately face the same DRG weight whether or not they use the technology, these updates do little to change the inherent distortions of the system toward underutilization.

There is limited empirical evidence about the diffusion of new technologies under PPS. The Prospective Payment Assessment Commission has reported that recent years have witnessed continued growth in the number of community hospitals offering lithotripsy, open heart surgery, cardiac catheterization, and organ transplants (30), but some evidence suggests that PPS has slowed the adoption of potentially cost-effective technologies. Kane and Manoukian (31), for example, reported that PPS has effectively halted the diffusion of cochlear implants, despite FDA approval and favorable reviews by the Office of Health Technology Assessment and several medical associations. The authors blame the underdiffusion on Medicare's decision to classify cochlear implant patients in a DRG for which reimbursement covers only a fraction of the cost of the device.

Like all fixed-price systems, PPS does not easily incorporate the changes in resource use that occur with new technologies. Some policy makers have advocated creating new or temporary DRGs, or add-on payments for such important new technologies as cochlear implants (32). But reimbursing technologies on a case-by-case, add-on-payment basis reestablishes a cost basis for payment and fails to remove the other distortions from cost-effective resource allocation noted above.

An alternative to prospective rate setting is global budgeting for hospitals, modeled after the Canadian system. Under global budgeting, hospitals or other entities are allocated a fixed budget and given the discretion to allocate it as they see fit. Because they do not associate fixed payments with the use of individual technologies, global budgets remove some of the incentive to focus on reimbursement levels. They also tend to expand the time perspective in which resource allocation decisions are made. As a result, they may create more appropriate incentives for hospitals to allocate scarce resources for new technologies. But global budgets do not remove all distortions. The hospital perspective is still limited to inpatients, for example. And the incentive to be efficient is attenuated because hospitals can receive a pass-through each year for legitimate cost increases, at least in the Canadian system. There is some evidence that new technologies do not diffuse as rapidly in Canada as in the United States, but it is not clear that the rate is more appropriate or that the most cost-effective technologies are adopted. Studies show, for example, that the United States has eight times more MRI units per capita than Canada, a difference unlikely to be accounted for by differences in disease or demographics (33). Whether the Canadian or the American utilization rate is the more cost effective remains to be determined.

HMOs and Managed Care Plans

The perspective of health maintenance organizations (HMOs) is similar to the societal perspective in cost-effectiveness analysis in several important respects. Since HMOs receive a fixed payment per enrollee, they have incentives to consider the longer-term health and economic consequences of decisions about new technologies. In addition, capitated plans provide patient care in both the ambulatory and hospital setting.

However, the HMO and societal perspective differ in several ways. A major difference is that the HMO perspective is distorted by significant enrollee turnover; in other words, an HMO is not the closed system it may appear to be. The high rate of disenrollment in many capitated plans may have important consequences for the cost-effective adoption of new technologies. Technologies that increase short-run costs but save costs in the long run may be cost effective from society's point of view but not the HMO's, for example. An HMO's cost-effectiveness analysis regarding a new technology can be expected to discount costs, and to some extent health consequences, beyond the point of disenrollment. A second difference is that HMOs do not cover all health care services, such as stays in long-term care facilities. Technologies that affect these costs (e.g., which prevent nursing home stays) would not be as highly valued by the HMO. Third, the adoption of new technologies may be influenced by financial incentives, employed by most HMOs, that encourage physicians to restrict utilization (34). Recent evidence suggests that some financial incentives, as well as the type of HMO, influence the number of outpatient visits and the rate of hospitalization (35). As with hospitals, there are countervailing forces: competition for patients and physicians as well as ethical and malpractice concerns.

Because they receive a fixed amount per patient, capitated plans might be expected to adopt and use technologies at a lower rate than their fee-for-service counterparts. Some empirical evidence supports this hypothesis. One study found that Kaiser Permanente's utilization of computed tomography (CT) examinations in the 1970s was substantially lower than that for California or the nation (36). Epstein and colleagues compared the rate at which patients with uncomplicated hypertension were tested by fee-for-service and large prepaid practices. After correcting for age, sex, and severity of illness, they found 50 percent more electrocardiograms and 40 percent more chest radiographs among patients in a fee-for-service system (37). Fee-for-service physicians believed both tests were associated with higher costs and profits, and the largest differences existed for tests where there was the greatest difference in profitability. Gold and colleagues recently found that HMOs are more likely than other plans to have drug utilization review programs, to mandate the use of generics, and to use formularies (38). Again, it remains to be determined which utilization pattern is more cost effective.

Incentives for Fee-for-Service Physicians

The existing reimbursement systems for physicians have important implications for cost-effective adoption of new technologies. Because they are paid for services provided, fee-for-service physicians have incentives to use new technologies beyond the point at which marginal costs equal marginal benefits. Furthermore, current reimbursement levels have an inherent bias toward procedure-based services. Numerous studies have found that reimbursement is disproportionately higher for technology-driven services than for more cognitive services, such as clinical evaluation and management (39). Relative to resource costs, evaluation and management services are compensated at a lower rate than invasive, imaging, and laboratory services. There is also an inpatient bias to the system. Studies have found that services performed on ambulatory patients are compensated at substantially lower rates than if they are performed on inpatients (39).

The creation of a resource-based relative value scale (RBRVS) with an expenditure ceiling for physician services, recently approved by Congress, will affect the adoption of new technologies in several ways (39). The new fee schedule is intended to establish a “level economic playing field” for physicians based on resources used in providing services. Ideally, the effect will be to make medical decision making income neutral for the physician, leaving clinical benefit as the basis for resource allocation. Keeping the RBRVS up to date with current resource costs to the physician, however, may lead to short-term distortions affecting the use of new technologies.


We have presented evidence that new technologies do increase costs on average, but that some technologies in some clinical uses may save more resources than they cost. We have also suggested that cost effectiveness is an appropriate criterion for guiding the adoption of new technologies, although other criteria, such as equity to the disadvantaged, must also be considered. Finally, we have described characteristics of the American system of reimbursement and health care management that do not always lead to the adoption of the most cost-effective mix of new and old technologies.

We conclude by suggesting some directions for the 1990s. First, new technologies must be evaluated as early as possible and should be reevaluated frequently. Both health and economic impact should be part of these evaluations. This country has not yet found a stable funding base for these kinds of evaluations, but this must be done to provide an adequate information base for policy formulation. Second, we must make the incentive structure facing health care insurers, providers, and consumers correspond more closely to societal goals and resource constraints. Physicians already have a commitment to improving health through effective medical care, and organized medicine has recognized and accepted the challenge of living within budgets. A system based more on global, flexible budgets than on piecemeal regulations would not be without problems, but it might bring improvement. In this regard, caution should be exercised in applying the standard HMO model, because HMOs do not bear the full costs or realize the full benefits of the technologies they employ. Therefore, any system of decentralized global budgeting should give managers financial responsibility for both external and induced costs and savings. The role of information and guidelines for cost-effective care would be enhanced in such an environment, and the research base for providing such information in real time should be expanded. Third, the current reimbursement system, especially the PPS under Medicare, tends to freeze the status quo. Cost-effective new technologies are at a competitive disadvantage relative to cost-ineffective existing ones. We need to level the playing field in this country, to encourage innovation, and to encourage, not stifle, the substitution of cost-effective for cost-ineffective clinical practices. Finally, the voice of the American public cannot be ignored. The people want cost containment, but they also want new technology if it can bring them better health. A system that rewards cost-effective health care and invites cost-effective new technology could accomplish both objectives.


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1. The method of quality-adjusted life years assigns weights, ranging from zero to one, to states of health. Thus, 2 years at a quality level of 0.5 would be equivalent to 1.0 quality-adjusted life year.

Copyright © 1991 by the National Academy of Sciences.
Bookshelf ID: NBK234309


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