This study found that certificate-of-need laws have reduced the number of hospital beds by about 10% and have reduced healthcare expenditures by almost 2%.
Published Online: October 08, 2009
Fred J. Hellinger, PhD
Objective: To estimate the effect of certificate-of-need legislation on hospital bed supply and healthcare expenditures.
Study Design: This study uses state data on several variables, including healthcare expenditures, hospital bed supply, and the existence of a certificate-of-need program, from 4 periods (1985, 1990, 1995, and 2000).
Methods: We estimate 2 multivariate regression equations. In the first equation, hospital bed supply is the dependent variable, and certificate of need is included as an independent variable. In the second equation, healthcare expenditures is the dependent variable, and hospital bed supply and certificate of need are included as independent variables.
Results: Certificate-of-need laws have reduced the number of hospital beds by about 10% and have reduced healthcare expenditures by almost 2%. Certificate-of-need programs did not have a direct effect on healthcare expenditures.
Conclusion: Certificate-of-need programs have limited the growth in the supply of hospital beds, and this has led to a slight reduction in the growth of healthcare expenditures.
(Am J Manag Care. 2009;15(10):737-744)
This study uses statewide data from 4 periods (1985, 1990, 1995, and 2000) to estimate the effect of state certificate-of-need laws on the supply of short-term hospital beds and on healthcare expenditures. The study found the following:
- State certificate-of-need laws reduce the supply of hospital beds.
- Certificate-of-need laws reduce aggregate healthcare spending in the state.
- “Strict” certificate-of-need laws have a much greater effect on hospital bed supply and costs.
Certificate-of-need programs attempt to curtail the construction of unnecessary healthcare facilities and to limit the acquisition of costly equipment that provides little benefit by compelling hospitals and other healthcare entities to acquire prior approval from a governmental entity.1-3 Indeed, efforts to control the growth of healthcare facilities and acquisition of expensive equipment have been ongoing for more than 60 years.4
The 1946 federal Hill-Burton program provided funds for new hospital construction contingent on the adoption of a state health plan that detailed the process by which proposed projects would be evaluated.5,6 The Hill-Burton program encouraged local planning to facilitate the recognition and classification of local needs.
State and local Comprehensive Health Planning agencies (so-called A and B agencies) were created by the 1966 amendments to the Public Health Service Act. These agencies were obligated to produce a state plan for healthcare facilities growth, but they were given no statutory power to implement their judgments and were incapable of mandating the submittal of capital budgets. Consequently, their effectiveness was limited. Nevertheless, many Blue Cross plans refused to reimburse for the interest and depreciation expenses associated with unapproved capital projects.
The Medicare program was enacted in 1966 and adopted a cost-based reimbursement method for short-term hospital services. Following the enactment of Medicare, large increases in hospital and healthcare costs created an intense interest among third-party payers, lawmakers, and the public in the size and expense of short-term hospitals.7
In 1967, New York became the first state to enact a certificate-of-need program. Shortly thereafter, Rhode Island, Maryland, and California passed certificate-of-need legislation.8
Section 1122 of the 1972 amendments to the Public Health Service Act incorporated controls on capital expansion by healthcare facilities through the withholding of Medicare and Medicaid funds for the interest and depreciation expenses associated with unapproved projects. States were allowed to designate either their state health planning agency or Hill-Burton agency to determine the need for new capital expenditures. The National Health Planning and Resources Development Act of 1974 required states to enact certificate-of-need laws to receive funds through the Public Health Service Act.9 Only Louisiana failed to implement a certificate-of-need law, but Louisiana operated a section 1122 program during this period and in 1991 passed a certificate-of-need law. In 1986, Congress repealed the federal mandate to implement certificate of need to receive funds under the Public Health Service Act.
The sanctions included in the National Health Planning and Resources Development Act of 1974 were never imposed, although 3 states (Utah, Idaho, and New Mexico) repealed their certificate-of-need law in the early 1980s before the federal mandate was rescinded (Table 1).8,10 Eight more states (Arizona, Minnesota, Kansas, Texas, California, South Dakota, Wyoming, and Colorado) dismantled their certificate-of-need program during the late 1980s, and 2 states (North Dakota and Pennsylvania) dismantled their program in the mid-1990s.
Several studies11-14 of the effect of certificate-of-need laws found that they had little effect on the supply of hospital beds or on the cost of care. However, Salkever and Bice3,15 found that certificate-of-need laws reduced the number of hospital beds but did not decrease a hospital’s investment in other plant assets, and Cromwell16 found that certificate-of-need laws reduced the number of hospital beds but did not affect other measures of hospital investment. These studies are based on data from before 1986, when the federal mandate to operate certificate-of-need programs was overturned.
In contrast, the present study uses data from 1985, 1990, 1995, and 2000 to examine the effect of certificate-of-need legislation. It will be relevant to ascertain whether these findings change when more recent data become available. Indeed, there is concern that many state certificate-of-need programs have become too lenient, suggesting that the effect of state certificate-of-need laws on hospital bed supply has lessened in recent years.17,18
Because all but 1 state (Louisiana) operated some form of certificate-of-need process until the early 1980s, it is difficult to isolate and estimate the effect of this legislation using data from before 1986 unless data from before 1974 are used, as this is when certificate-of-need legislation was mandated for all states. It is possible to estimate the effect of certificate-of-need laws using data after 1983 because 11 states repealed their certificate-of-need laws after 1983 and before 1990 (Table 1). In addition, 2 states (Indiana and Wisconsin) repealed and reinstated their certificate-of-need laws in the early 1990s, and 2 states (Pennsylvania and North Dakota) repealed their programs after 1990. Meanwhile, Louisiana implemented its first certificate-of-need program in 1991.
Another 9 states repealed the sections of their certificate-of-need laws covering short-term hospitals, while maintaining controls on other types of facilities, and 7 of these states did so in the 1980s. Consequently, statewide data from the 1980s and 1990s provide a contrast between states that operated certificate-of-need programs and those that did not operate a certificate-of-need program, as well as between states with a certificate-of-need program that covered hospitals and states without such a program. Moreover, because most states that repealed their certificate-of-need laws did so in the 1980s, data from the 1990s provide a contrast between states that had no certificate-of-need law for several years and states with a certificate-of-need program that had been in place for more than a decade.
An array of independent variables are included in our model to explain the supply of short-term hospital beds per 100,000 civilian residents and the level of healthcare expenditures per capita. Three of these relate to certificate-of-need legislation: (1) a dichotomous variable indicating whether a state had a certificate-of-need law in a given year, (2) a dichotomous variable indicating whether a state had a certificate-of-need law that covered short-term acute care hospitals in a given year, and (3) a dichotomous variable indicating whether a state had a stringent certificate-of-need process as designated by the American Health Planning Association.10
The supply of physicians is included in our model as an independent variable. It is assumed that states with more physicians will have more short-term hospital beds and higher healthcare expenditures, and physician availability is measured by the number of active nonfederal physicians practicing in each state per 100,000 civilian residents. The mean personal per capita income also is included as an independent variable in our model. States with higher personal incomes are assumed to have a greater demand for healthcare services and higher healthcare expenditures, and for this reason we include personal income as an independent variable in our model.
Similarly, it is assumed that states with higher unemployment rates are likely to have decreased demand for health services, fewer hospital beds, and lower healthcare expenditures. For this reason, we include a state’s unemployment rate in our model.
Because it is likely that population density is a proxy for omitted measures of price, we expect to find an inverse relationship between population density and hospital bed supply. It is also possible that there are fewer hospital beds in sparsely populated areas because of the longer distances involved for patients seeking physician care or hospital care, and it is likely that citizens in less densely populated states are more likely to receive healthcare in states that are more densely populated. For these reasons, we include a variable that measures the number of citizens (measured in thousands) per square mile for each state.
A recent publication states: “In general, individuals with lower income, less education, and lower-status occupations and employment have poorer health. Therefore, it would seem that raising educational levels would reduce health-related expenditures for the public sector, as well as for individuals.”19(p1) We include the proportion of the state’s population who graduated from high school, the proportion of residents without health insurance, and the proportion of residents enrolled in a health maintenance organization. We anticipate that each of these variables is inversely related to healthcare expenditures per capita.
We also include a variable measuring the political climate in a state because the political climate may affect the likelihood that a state repeals certificate-of-need legislation and the amount spent on healthcare. We chose the proportion of voters in the state who voted for the Democratic candidate for president in the most recent election to measure the political climate in a state. In addition, we include a variable measuring the number of deaths per 1000 residents to adjust for the health and age of the state’s population.
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