Hospitals are generally considered to be the locus of rural health care systems. Not only are important health services based at hospitals, but many of a community's health care personnel are either directly employed by or supported by the local hospital. Further, hospitals are often considered vital to local economies as they bring outside dollars into the communities via third-party payors, provide jobs, stimulate local purchasing, and help attract industry and retirees (Doeksen et al. 1997
). As such, the closure of a hospital can have detrimental effects on a rural community. The rapid succession of hospital closures throughout the 1980s and 1990s helped stimulate legislation, such as creation of Critical Access Hospitals (hospitals that accept certain restrictions and are reimbursed 101 percent of cost from Medicare), designed to ensure the financial viability of small rural hospitals.
The number of small rural hospitals that have chosen to convert to CAH status has risen beyond expectations; as on August 2004, 959 small rural hospitals (over 40 percent of all rural hospitals) have opted out of Prospective Payment System by converting (Flex Monitoring Team 2005
). In some policy circles, concern has been expressed about the effect on the Prospective Payment System of so many hospitals taking advantage of the protection of cost-based reimbursement (MEDPAC 2003
). In light of these concerns, this is an opportune time to more accurately assess the economic importance of small rural hospitals to their communities, and to estimate the potential impact of their closure, should favorable reimbursement policies be changed.
The effect of hospital closures on the health of community members has been relatively well documented and is not the focus of this study. For example, Reif, Des Harnais, and Bernard (1999)
study six communities experiencing a hospital closure and conclude that hospital closures decrease access to health care, whereas Rosenbach and Dayhoff (1995)
find that per-capita Medicare expenditures grew at a slower rate in communities experiencing a closure. Fleming et al. (1995)
find that residents of communities with a hospital closure experienced a mean increase in travel time to care of about 30 minutes. Rather, we are concerned with the relationship between a hospital closure and the local economic conditions before and after the closure. In general, hospital closure is perceived to have negative economic effects on a rural community (Hart, Pirani, and Rosenblatt 1991a
), although few studies have directly measured the effect. A number of studies have attempted to estimate the role of hospitals in their local economies as evidence of the direct and indirect impact a closure would have, by either comparing the closure communities' economies to those of control groups, or through input/output (I/O) analysis.
In one of the earliest studies, Christianson and Faulkner modeled the contribution of rural hospitals to local economies and found an estimated $686,405 to $1,083,282 (US$ in 1978) in community income was generated directly and indirectly by hospital expenditures; income multiplier estimates were less than 2 for 90 percent of the communities (Christianson and Faulkner 1981
). McDermott et al. (1991)
used hospital survey data to estimate the economic impact of a hospital on its host community and found that the combined induced and direct effects, on average, were $54,739 per hospital bed (1991). Studies using I/O analysis, which uses observed data on business and consumer purchase patterns to estimate the direct and indirect/induced effects of a change in one sector of the economy on others, have found similar results. For example, Doeksen, Gerald, and Altobelli (1990)
simulated the effect of a hospital closure in rural Oklahoma and estimated that over a 5-year period approximately 78 jobs, $1.7 million in income, $452,100 in retail sales, and $9,100 in sales tax revenue would be lost because of the closure. Similar conclusions were reached using data from three Texas communities (Doeksen, Loewen, and Strawn 1990
). Cordes et al. (1999)
extended the literature by examining the role of the hospital in the economy and differentiating hospitals by bed size. They found that the estimated economic multipliers increased in magnitude with hospital bed size, but did not specifically estimate the effect of closure using I/O analysis.
While each of these studies suggests that a hospital closure would have negative economic consequences for rural communities, other research has indicated little to no effect on the rural community because of hospital closure. Pearson and Tajalli (2003)
found that hospital closure does not appear to cause short- or long-term harm to the economies of their rural host communities. Their findings were based on a pretest/posttest model of data for 24 Texas rural communities where a hospital closed and a group of control communities. Five economic indicators were examined for trends and none were found to have had a statistically significant change following closure of the hospital. Similarly, Probst et al. (1999)
compared economic indicators in closure communities to a control group of nonclosure communities and failed to find a statistically significant difference in income trends in the closure counties relative to the comparison counties. Stensland et al. (2002)
examined the effect of 42 hospital closures in rural Appalachian communities and concluded that the closure had no effect on short-term or long-term economic growth of those areas.
Predominantly, the literature on the economic effects of hospital closures has relied on I/O analysis. Whereas I/O analysis has been useful in furthering the methodology of measuring hospital closure effects to include spending induced by the hospital business, the technique is limited in many ways. First, it is not designed to calculate “amenity” effects of a hospital closure—the absence of a local hospital may discourage retirees and businesses from moving into the community. Secondly, because of a lack of data on these small rural markets, I/O analysis for rural areas often relies on national purchasing trends, rather than local purchasing patterns, to calculate economic multipliers. Third, I/O treats the study region (often a county) as an isolated economy and tends to ignore market area considerations, which may lead to over- or under-estimation of the effects. Finally, I/O analysis does not offer measures of precision in the estimates. The concept of standard errors (SEs) is critical in ascertaining the degree of confidence one has in the results, and I/O has no such ability.
In this paper, we estimate the effect of hospital closure on the local economy using multivariate regression methods that do not require the use of a control group consisting of communities not experiencing a hospital closure. We posit that the closure of a hospital negatively affects the economic health of a community, and we extend the hospital closure literature in two new dimensions. First, we differentiate between the impact of a hospital closure in a community where another hospital remains open and closure in a community with no other proximal access to hospital services. This distinction is important because many of the ways that a closure can affect local economies, such as the amenity effect, can be mitigated by the presence of a near-by alternative hospital. Second, our analysis considers whether the economic conditions in communities where a hospital has closed can be attributed to the closure, or whether poor economic conditions preceded (and perhaps contributed to) the closure. Our methodology allows this assessment without the necessity of identifying appropriate controls, a difficult task as there may be intrinsic differences between financially struggling communities where hospitals ultimately close and those where they remain open.