Managed care and technology adoption in health care: evidence from magnetic resonance imaging
Introduction
Among the many questions raised by growth in managed care is the impact it will have on the development, adoption, and use of new medical technologies. The US health care system has been characterized for many decades by rapid technological progress, fueled in part by a reimbursement system that generously payed for the development and use of new advanced therapies (Weisbrod, 1991). Now, some fear that growth in managed care is eroding the pillars that supported this system. Managed care has reduced physician and hospital reimbursement in many parts of the US and moved to limit use of expensive tests and procedures by enrollees, often focusing most intently on spending for new high cost technologies at the most advanced institutions. These kinds of changes could reduce the profitability of new innovations, and slow adoption and reduce the overall availability of technologies. This, in turn, could have ripple effects throughout the process of technology development if researchers and developers perceive changes in the markets for new products and scale back their efforts or alter their research and development strategies.
Changes in the availability of new technologies and the rate of technological change could have important implications for the health care system. It is widely believed that the majority of health care cost growth over the past 50 years is due to technological change (Newhouse, 1992, Fuchs, 1996). Rapid technological change also appears to have significantly improved the capacity of medicine to treat disease and thereby substantially improved the well-being of patients (e.g. Cutler et al., 1998). Understanding the impact of managed care on technology change is thus important for assessing its impact on spending and patient welfare, as well as for evaluating and optimally designing policies that would influence the future development of managed care.
This paper investigates the relationship between managed care activity and the adoption of magnetic resonance imaging (MRI) equipment, a good example of a technology that could have been influenced by managed care. MRI is a diagnostic tool for producing high resolution images of body tissues, most frequently the brain and spinal cord. The first prototype MRI machines for human imaging were installed in the United States in 1980 and MRI entered general clinical use in 1982 (Baltaxe and Geokas, 1983, Hillman and Schwartz, 1985). It diffused during the 1980s and 1990s, the period in which managed care came to play a significant role in the US health care system.
MRI has attracted attention, from managed care plans among others, partly because of its high cost. Hospitals or other health care providers that wish to offer MRI typically purchase and install an MRI scanner.1 The machines themselves are costly, typically running more than US$ 1.5 million for a new imager, and there are often substantial facility modifications that must be made to provide coolant for the magnets and shield surrounding equipment from powerful magnetic fields (Bell, 1996, Steinberg and Evens, 1988). The operating costs of MRI can also be significant. Personnel and maintenance costs can easily amount to US$ 200 000 per year for most facilities, and the cost of supplies were estimated to be more than US$ 100 per scan in 1995 (Bell, 1996). Patient charges associated with MRI procedures vary widely depending on things like the complexity of the images required and physician charges for interpretation, but it is not difficult to run up total charges of more than US$ 1000 for many MRI procedures.
MRI can improve the speed and accuracy with which many diagnoses can be made. For some conditions and patients, though, MRI scans can be viewed as helpful but not necessary. It is sometimes possible to substitute other less expensive procedures like computed tomography (CT) or ultrasound for MRI with arguably limited effects on the quality of the diagnosis. Virtually, all insurers cover medically indicated MRI procedures, but health plans concerned about costs have been particularly vigilant about the use of MRI in cases where its benefits are not immediately clear or where other procedures could be substituted.
Section 2 briefly reviews mechanisms by which managed care could have influenced adoption of MRI. I then turn to the empirical work. Using data on hospital adoption of MRI and data on the overall availability of MRI, I examine MRI diffusion and availability in markets with varying levels of HMO market share. I conclude that managed care was associated with slower diffusion of MRI, particularly in hospitals. With expenditures for the purchase of MRI equipment typically running in the millions of dollars, reductions in adoption should have produced substantial savings. But, achieving these savings may also have entailed reductions in the use of services that benefit patients, which would leave questions about the net welfare effects open. After studying the effects of managed care on adoption patterns, I briefly examine the relationship between HMO market share and the number of MRI procedures performed. The results suggest that increases in HMO market share are strongly associated with declines in the utilization of MRI procedures.
The general patterns and determinants of technology adoption in health care, including the case of MRI, have been widely studied.2 The overall impacts of managed care on spending and premiums have also been previously examined.3 However, there is relatively little work that examines the effects of managed care on technology adoption and use in detail. Cutler and Sheiner (1998) investigated the relationship between state-level HMO market share and the availability of a range of services in hospitals, finding evidence that managed care slowed the diffusion of technologies that were diffusing recently. Baker and Brown (1999) report that managed care reduced the number of mammography providers, but increased the volume of procedures performed at the remaining sites. Baker and Phibbs (2000) report that high HMO market share was associated with slower adoption of neonatal intensive care units between 1980 and 1996. The literature is not unanimous, however, Baker and Spetz (1999) report that managed care activity was not associated with changes in an index of hospital technologies, suggesting that managed care may not slow overall adoption, and Hill and Wolfe (1997) reported mixed effects of managed care on diffusion of a range of technologies in Wisconsin during and after rapid growth in managed care activity.4
Section snippets
Managed care activity and technology adoption
“Managed care”, for purposes of discussion here, describes a collection of activities health plans can undertake that are designed to reduce the high levels of utilization and spending that accompanied unfettered fee-for-service medicine, and improve the efficiency of health care delivery. These activities can include a range of things like the use of financial incentives to influence utilization patterns, direct oversight of utilization decisions, selective contracting with preferred
Empirical approach and data
I study the impact of managed care on MRI by comparing MRI diffusion and availability in markets with varying levels of managed care activity. I define markets as health care service areas (HCSAs). HCSAs are groups of counties constructed to approximate markets for health care services based on Medicare patient flow data (Makuc et al., 1991). There are 802 HCSAs covering the entire continental United States.
I use data on MRI diffusion and availability from three complementary sources. I begin
Overall MRI diffusion and availability
Table 1 summarizes adoption of MRI by hospitals in the 1983–1993 AHA survey sample. Over this time period, 1176 hospitals adopted MRI. Kaplan-Meier estimates of the cumulative adoption probability rise from 0 to nearly 25% by 1993. A total of 90 of the original 5344 hospitals are censored before 1993, when all remaining hospitals are censored. The majority of these are censored because they close or merge during the time period, and the large number of hospitals in this category is consistent
HMOs and hospital MRI, 1983–1993
Hazard models provide a natural framework for studying technology adoption by a well defined set of candidate adopters (e.g. Rose and Joskow, 1990, Cutler and McClellan, 1996). Denoting the cumulative probability that hospital i has MRI at time t by Fi(t) and the density function as fi(t), the hazard is defined as the probability that hospital i acquires MRI at time t conditional on not having acquired MRI up to that point: λi(t)=fi(t)/[1−Fi(t)]. I parameterize the hazard using a proportional
HMOs and MRI machines in and out of hospitals, 1993 and 1995
The AHA data provide only part of the picture of MRI availability in the United States since many MRI machines are not in hospitals, and even for hospitals the AHA surveys do not provide information about the number of installed units. The 1993 and 1995 MRI censuses provide data on the number of magnets operated in and outside of hospitals.
I used MRI census data for 707 HCSAs with populations over 25 000 to estimate regressions of the form
HMOs and hospital MRI After 1993
A natural question is the extent to which these effects have persisted into the later 1990s. AHA data from 1994 to 1998 can provide information about more recent trends in hospital MRI adoption. I used this data to compute the number of hospitals that indicated having MRI “owned or provided by the hospital or a subsidiary” per 100 000 population in each area, which should serve as a general measure of MRI availability in the area. I then estimated annual cross-sectional OLS models of the form
MRI utilization
Reductions in adoptions could reduce patient access to MRI equipment.
Conclusions
Data from AHA surveys and from two MRI censuses indicate that increases in HMO activity are associated with slower diffusion of MRI equipment and lower overall MRI availability. This is consistent with the view that changes in incentives brought about by managed care can have important impacts on technology diffusion in health care.
Since MRI is still diffusing, it is probably too early to say for sure that the equilibrium levels of MRI will be lower in high managed care areas, although that
Acknowledgements
I thank David Cutler, Randall Ellis, Alan Garber, William Vogt, anonymous referees, and many seminar participants for helpful comments. Susan Wheeler provided invaluable assistance with data analysis. This project was supported by a grant from the Robert Wood Johnson Foundation’s Health Care Financing and Organization Program.
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