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Health Tracking |
TRENDS
Trends In Contract Management: The Hidden Evolution In Hospital Organization
| Abstract |
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Contract management is an arrangement whereby the day-to-day operation of the hospital is contracted to an outside organization. In the past two decades there has been dramatic growth in the number of hospitals opting for contract management, yet surprisingly little attention has been paid to this phenomenon. Using national data, we report trends and demonstrate that adoption of contracts results in decreases in service offerings more often than increases. Since contract-managed hospitals tend to be located in rural areas, this raises concerns regarding access to care. On the other hand, contract management may allow distressed hospitals to survive.
Profound changes in the way U.S. hospitals are being managed have transpired during the past two decades. While researchers and policymakers have considered issues such as the growth of managed care and consolidation of the hospital industry, little attention has been paid to management incentives and their impact on the delivery of services and access to care. In particular, there is a paucity of research and discussion of contract management, a dramatic and pervasive development in the manner in which incentives are provided.
Under contract management, a hospital’s board of trustees retains an outside organization to manage the facility. The contractor provides an administrator, usually along with an entire management team, to oversee day-to-day operations. Contract managers provide hospitals with expertise that may not be available locally. Also, by essentially contracting out the entire management function, boards of nonprofit hospitals may be able to introduce profit-maximizing incentives into their organizations.1 Thus, contract management provides an alternative to selling an independent hospital to a chain, closure, or conversion to for-profit status.2
Previous research has found that adoption of contract management improves hospitals’ financial performance and may improve allocative efficiency, especially in smaller hospitals and in hospitals located away from major metropolitan areas.3 Although anecdotal evidence is in the public domain, there appears to be little understanding of what contract managers actually do and at what social costs they may attain these efficiencies.
This paper examines the characteristics of contract-managed hospitals and explores the "black box" of specific activities that might be changed as a result of the adoption of contract management. An important issue in recent years is the extent to which hospitals compete on quality and whether this results in unnecessary duplication of hospital services. Over-provision of services could be a contributing factor to rising hospital costs.4 While this manner of competitive behavior may have the potential of attracting patients, hospitals also might reduce service offerings to control costs.
| Trends And Characteristics |
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 Top Trends And Characteristics Comparative Analysis Of ServicesDiscussionEditor's NotesNOTES |
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The lack of discussion of contract management is surprising, given its pervasiveness. Between 1980 and 2000 the share of community hospitals under contract management increased 1.5-fold (Exhibit 1
). The increase was particularly dramatic during the 1980s. Growth slowed in the mid-1990s, paralleling trends in hospital consolidation in general.5
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The trade press and industry sources reflect a dynamic industry, with contract-management firms of various sizes promoting services to hospital boards. Quorum Health Group has been the dominant player, with approximately 170 hospitals under full contract nationally, followed by Brim HealthCare, with thirty-six rural hospitals in fourteen states, and Alliant Management Services, which manages about twenty hospitals in the Midwest.6 Many smaller firms manage ten hospitals or fewer in any given year and operate regionally or locally only. In some cases, the larger contract managers may also own several hospitals outright. Conversely, large multi-hospital systems may offer contract management to a few hospitals they do not own. According to the American Hospital Association (AHA), of about 190 hospitals in 2000 affiliated with HCA, six were strictly contract-managed rather than wholly owned.7
To examine the characteristics of contract-managed compared with traditionally managed hospitals, we used data from the AHA Annual Survey database for 1991 and 2000. Exhibit 2 displays several common hospital descriptors for the universe of acute care, nonfederal hospitals for 1991 and 2000, the starting and ending years of the database, with breakdowns for facilities that were and were not contract-managed. The mean values of these variables indicate that contract-managed hospitals are smaller facilities serving a lower case complexity. The mean number of beds in contract-managed hospitals is roughly half that in other hospitals. The number of admissions was approximately 40 percent that of traditionally managed hospitals in 1991 and fell to one-third in 2000. The concentration of facilities with fifty beds or fewer among contract-managed hospitals grew from 36 percent in 1991 to 42 percent in 2000. Occupancy rates are lower in contract-managed hospitals, and the average length-of-stay is higher; it remained relatively steady compared with other hospitals during the 1990s. Contract-managed hospitals are also distinctive in being primarily rural based. Finally, contract-managed hospitals differ in the pattern of ownership. Many public hospitals have entered into contract management as a strategy for coping with tough fiscal constraints. Nearly half of contract-managed facilities were government-owned in 2000, more than twice the rate of the comparison group; this differential rose over the study period.
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| Comparative Analysis Of Services |
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| TopTrends And CharacteristicsComparative Analysis Of ServicesDiscussionEditor's NotesNOTES |
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Methods. The AHA survey also contains extensive information on the individual service offerings of U.S. hospitals. For the universe of acute care, nonfederal hospitals, preliminary analysis identified fifty-one unique services for which there were significant differences in service offerings either across time or between hospitals using and not using contract management. Binary variables described whether or not a hospital offered a particular service and also identified contract-managed hospitals. To refine the analyses and to facilitate the drawing of some broad inferences, we grouped these fifty-one hospital services into fourteen service dimensions.8
Next we identified all hospitals that adopted contract management during the study period. Among these, we chose for analysis the 207 hospitals that adopted between 1993 and 1998—those for which we had data falling two years before and two years after adoption (allowing the contract-adopting hospitals a period of adjustment). This provided pre- and post-adoption samples of contract-managed hospitals with data spanning the years 1991–2000. For comparison, we took a stratified random sample of non-contract-managed hospitals (without replacement) numbering three times the number of adopters, or 621 hospitals. We stratified the random sample along two dimensions. First, because contract-managed hospitals are more likely to be rural, government-owned, and small, we calculated propensity scores that described the probability of an individual hospital’s being contract-managed.9 Second, we matched the controls to the contract adoption group by longitudinal distribution. The final data set contains 1,656 observations and comprises two sets of matched pairs of hospitals. The contract-management pairs represent actual pre- and post-adoption years, and the comparison groups signify simulated pre- and post-intervention years. This type of research design is commonly referred to in economics as the difference-in-differences (DD) method.10
Analysis. We used the probit model for estimation of the probability that a particular service is offered.11 Service functioned as the dependent variable in each equation (estimated individually for each service). Binary variables were included in the DD model representing time (0 =pre period; 1 =post period) and contract management (0 =comparison group; 1 =contract management–adopting group). The time variable controlled for the ways in which time influenced all hospitals in the analysis, independently of contract-management status. The contract-management variable captured overall differences between adopting and nonadopting hospitals. The interaction of these two variables was also entered into the model as a way of capturing the difference in the change in service offerings (the DD effect) between the group of hospitals that adopted contract-management arrangements and the comparison group. Simply put, it yields the net effect associated with contract adoption, after taking out the trend effect.
Results.
The probit regression results indicated that overall, the hospitals expanded their service mixes over time (Exhibit 3). This change holds for all hospitals in our data regardless of contract-management status. Two broad trends emerged. First, services related to health promotion and disease prevention were on the rise, for example, women’s health centers, child wellness, sports medicine, social work, fitness centers, and nutrition programs. Second, some high-cost specializations were observed to be declining, including transplant, HIV, and reproductive health services. This may likely reflect increasing concentration of these services in large hospitals rather than a decline in the overall intensity of these activities. Other areas of growth include cardiology, home health, and hospice services.
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The list of services that are more likely to be offered by nonadopters includes most diagnostic and specialty psychiatric offerings as well as home health services, but no services from the emergency, pediatric, or long-term care dimensions (Exhibit 4
). Skilled nursing care was more likely to be offered in contract-managed hospitals. Overall, it appears that contract-managed hospitals compare fairly well with traditionally managed hospitals in breadth of service offerings according to the types of patients served. Yet they do not offer the depth of service in terms of specialization and level of technology.
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Finally, we ask if there is a net difference between the two groups of hospitals, because of contract adoption. Exhibit 5
addresses this question using the DD approach. It displays services for which there was a significant effect on the interaction between time and contract management. We found that only six services differ in this way. Of these, four services were more likely to decline for contract adopters relative to the comparison group, and two were more likely to grow. There also does not appear to be any particular pattern with regard to service dimension.
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Exhibit 5
also lists the DD of probabilities of offering the service (measuring the net effect in service attributable to contract adoption) expressed as a percentage of hospitals in the sample offering the service. The magnitudes are notable, ranging from 13.8 percent for neonatal intermediate care to 54.1 percent for magnetic resonance imaging (MRI). | Discussion |
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| TopTrends And CharacteristicsComparative Analysis Of ServicesDiscussionEditor's NotesNOTES |
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Observing trends in the 1990s overall, our analysis shows that hospitals tended to increase services more often than they tended to decrease services. Increased service offerings were more common in certain low-end categories but occurred rarely in high-tech services. There appears to be no such systematic pattern for services that decreased over time. Contract-managed hospitals were less likely to offer a wide variety of services, and the adoption of contracts was more likely to result in reduction than addition of services. We focus mainly on the effects of contract management on service provision; research is also needed to examine its impact on the staffing crisis in rural areas.
Interim policy implications. Hospitals that opt for contract-management arrangements, we have found, tend to be small and located most often in rural areas. Given the itinerant nature of contract managers, this suggests that rural communities are experiencing difficulties in retaining managers locally. The difficulty of retaining medical professionals in rural areas has been the subject of great concern among policymakers. At the federal level, special bonus payments are available to physicians located in Health Professional Shortage Areas (HPSAs).12 A variety of similar state-level programs exist; also, states may tap into the Medicare Rural Hospital Flexibility Program to apply for special grants to improve services and staffing. Nonetheless, the need to retain skilled managers in rural and under-served areas may have been completely overlooked. To remedy this, policymakers may need to develop new sets of policies with incentives for hospital administrators to locate in such areas, much like the policies already available for physicians.
Direction for future research. Although the research here is preliminary, our results suggest that policymakers must pay greater attention to the important and overlooked phenomenon of contract management in hospital care. One area of concern is the potential adverse impact on access to care, as contract managers tend to eliminate services in potentially underserved rural communities. At the same time, contract managers may instead reduce services that are duplicated in the community, thereby contributing to efficiency. This could also improve quality, as research increasingly shows a link between volume of care and health outcomes. Future research is needed to determine the impact on the community by comparing contract-managed hospitals with neighboring hospitals. We suspect that the higher payments to rural hospitals enacted as part of the Medicare Prescription Drug, Improvement, and Modernization Act (MMA) of 2003 will reduce the incentive for rural hospitals to affiliate with both systems and contract management firms. On this, the jury is still out.13
| Editor's Notes |
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| TopTrends And CharacteristicsComparative Analysis Of ServicesDiscussionEditor's NotesNOTES |
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Kathleen Carey (Kathleen.Carey{at}med.va.gov) is an assistant professor of health services at the Boston University School of Public Health and an economist at the U.S. Department of Veterans Affairs Management Science Group in Bedford, Massachusetts. Avi Dor is the John R. Mannix Blue Cross and Blue Shield Professor of Health Care Economics, Weatherhead School of Management, Case Western Reserve University, in Cleveland, Ohio, and a research associate with the National Bureau of Economic Research.
The views expressed here are those of the authors and do not necessarily represent those of the Department of Veterans Affairs.
| NOTES |
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| TopTrends And CharacteristicsComparative Analysis Of ServicesDiscussionEditor's NotesNOTES |
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- See W.R. Scott et al., Institutional Change and Healthcare Organizations (Chicago: University of Chicago Press, 2000). Contract management should be distinguished from departmental contracting, whereby certain activities (for example, information systems) or departments (for example, emergency department) are outsourced. An example of a hospital that openly reports its relationship with a contract management firm is Wabash General Hospital in Mt. Carmel, Illinois. More information is available on the hospital’s Web site, www.wabashgeneral.com/geninfo.htm (12 August 2004).
- D.M. Cutler and J.R. Horwitz, "Converting Hospitals from Not-for-Profit to For-Profit Status: Why and What Effects," in The Changing Hospital Industry: Comparing Not-for-Profit and For-Profit Institutions, ed. D.M. Cutler (Chicago: University of Chicago Press, 2000).
- A. Dor, "Are Contract-Managed Hospitals More Efficient?" Pub. no. 94–0004 (Rockville, Md.: Agency for Healthcare Research and Quality, 1994); A. Dor, S. Duffy, and H. Wong, "Expense Preference Behavior and Contract Management: Evidence from U.S. Hospitals," Southern Economic Journal 64, no. 2 (1997): 542–554; and [CrossRef]K. Carey and A. Dor, "Does Managerial ‘Outsourcing’ Reduce Expense Preference Behavior? A Comparison of Adopters and Non-Adopters of Contract Management in U.S. Hospitals," NBER Working Paper no. 9157 (Cambridge, Mass.: National Bureau of Economic Research, 2002).
- Some early work supported the hypothesis of the "medical arms race" (MAR) in which increased hospital competition led to cost-increasing acquisitions of specialized clinical services as well as other means of nonprice competition. See J.S. Robinson and H.S. Luft, "The Impact of Hospital Market Structure on Patient Volume, Average Length of Stay, and the Cost of Care," Journal of Health Economics 4, no. 4 (1985): 333–356. More recent studies fail to uphold the MAR hypotheses. [CrossRef][ISI][Medline]See, for example, D. Dranove, M. Shanley, and C. Simon, "Is Hospital Competition Wasteful?" RAND Journal of Economics 23, no. 2 (1992): 247–262; [CrossRef][ISI][Medline]G. Melnick et al., "The Effects of Market Structure and Bargaining Position on Hospital Prices," Journal of Health Economics 11, no. 3 (1992): 217–233; and [CrossRef][ISI][Medline]T.L. Gift, R. Arnould, and L. DeBrock, "Is Healthy Competition Healthy? New Evidence of the Impact of Hospital Competition," Inquiry 39, no. 1 (2002): 45–55.[ISI][Medline]
- V. Gallaro and P. Reilly, "Where Have All the Good Deals Gone?" Modern Healthcare (26 January 2004): 34.
- See www.brimhealthcare.com or www.sih.net, which describes Alliant on the Southern Illinois Healthcare site. A related press account reports the decision of a Florida hospital, Jupiter Medical Center, to delay its sale to a for-profit chain while being managed by Brim. P. Galewitz, "Will More Hospitals Be Forced to Sell? For Some Independence Too Costly," Palm Beach Post, 25 July 2001.
- In 2001 Quorum was acquired by Triad hospitals, but it remains an independent subsidiary (as it had been temporarily under HCA in the 1980s). By 2002 it managed 223 health care facilities and owned an additional 22 hospitals outright. Irving Levin Associates, Health Care Acquisition Report, 2002 (New Canaan, Conn.: Irving Levin Associates, 2002).
- See G.J. Bazzoli et al., "A Taxonomy of Health Networks and Systems: Bringing Order Out of Chaos," Health Services Research 33, no. 6 (1999): 1683–1717.[ISI][Medline]
- Propensity score methods are used to reduce bias in observational studies when the experimental unit of interest lacks the benefit of randomization. See R.H. Dehijia and S. Wahba, "Propensity Score-Matching Methods for Nonexperimental Causal Studies," Review of Economics and Statistics 84, no. 1 (2002): 151–161; and [CrossRef][ISI]P.R. Rosenbaum and D.B. Rubin, "Constructing a Control Group using Multivariate Matched Sampling Methods That Incorporate the Propensity Score," American Statistician 39, no. 1 (1985): 33–38. The propensity score, defined here as the conditional probability of adopting contract management, is obtained from a logistic regression. By summarizing information into a scalar, stratification on the propensity score can match the distribution across many covariates. Logistic regression covariates follow the procedure in our earlier work on contract-managed hospitals. See Carey and Dor, "Does Managerial ‘Outsourcing’ Reduce Expense Preference Behavior?"[CrossRef]
- D. Card and A.B. Kreuger, "Minimum Wages and Employment: A Case Study of the Fast-Food Industry in New Jersey and Pennsylvania," American Economic Review 84, no. 4 (1994): 772–793; [ISI]B.C Madrian, "Employment-Based Health Insurance and Job Mobility: Is There Evidence of Job-Lock?" Quarterly Review of Economics 109, no. 1 (1994): 27–54; and B.D. Meyer, "Natural and Quasi-Experiments in Economics," Journal of Business and Economic Statistics 13, no. 2 (1995): 151–161.
- A statistical concern in applying the DD estimator is the matched-pair nature of the observations. The structure of the data is longitudinal, with precisely two observations for each of the 828 unique hospitals, so that the pre and post observations on individual hospitals are correlated. There are two overall approaches to addressing such correlation in modeling binary outcomes in longitudinal studies: subject-specific (random effects) and population-averaged techniques. The former generally are appropriate when the within-subject effects, or hospital effects here, are of interest. As our objective is to make inferences about group differences, we use the generalized estimating equations (GEE) method as is common to estimate population-averaged effects. See F.B. Hu et al., "Comparison of Population-Averaged and Subject-Specific Approaches for Analyzing Repeated Binary Outcomes," American Journal Of Epidemiology 147, no. 7 (1998): 694–703;
[Abstract/Free Full Text] P.J. Diggle et al., Analysis of Longitudinal Data, 2d ed. (Oxford: Oxford University Press, 2002); and K.-Y. Liang and S.L. Zeger, "Longitudinal Data Analysis using Generalized Linear Models," Biometrika 73, no. 1 (1986): 13–22.[Abstract/Free Full Text] - L.R. Shugarman and D.O. Farley, "Shortcomings in Medicare Bonus Payments for Physicians in Underserved Areas," Health Affairs, 22, no. 4 (2003): 173–187.
[Abstract/Free Full Text] - S. Heffler et al., "Health Spending Projections through 2013," Health Affairs, 11 February 2004, content.healthaffairs.org/cgi/content/abstract/hlthaff.w4.79 (12 August 2004).
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