Competition and community mental health agencies.

Journal of Health Politics, Policy and Law

Competition and Community Mental Health Agencies Robin E. Clark Dartmouth College Robert A. Dorwart Harvard University

Abstract Community mental health agencies (CMHAs) provide most of the institutional outpatient treatment in the United States. A great deal of this care is given to clients at prices below the actual cost of the service. As the number of mental health providers increases, the question of how competition shapes the performance of CMHAs becomes more important. We use a two-stage least-squares model to examine how competition from other outpatient facilities, psychiatrists, and health maintenance organizations (HMOs), coupled with demographic, economic, and organizational factors affects subsidized care in CMHAs. Our analysis shows that competition from psychiatrists and HMOs reduces the number of subsidized visits that CMHAs provide and that agencies in urban areas and those initiated with federal funds provide more subsidized care. By restricting access to outpatient treatment, competition may have adverse long-term consequences for potential clients and for state mental health authorities.

Community-based mental health agencies (CMHAs) play an increasingly important role in treating mental illness. Freestanding mental health clinics and multiservice mental health organizations provide two-thirds of all institutional outpatient care in the United States (NIMH 1990). Since 1963, when President Kennedy signed into law the federal Community Mental Health Centers Act, the number and the importance of communityTom McGuire, William Crown, Jim Callahan, Jr., Mark Schlesinger, and an anonymous reviewer provided helpful comments on earlier versions of this work, but the authors accept full responsibility for any errors. The research on which this paper is based was supported by a NIMH training grant to Brandeis University, by NIMH grant #ROl-MH40316 to the Kennedy School of Government at Harvard University, and by the National Council of Community Mental Health Centers. Journal of Health Politics, Policy and Law, Vol. 17, No. 3, Fall 1992. Copyright 0 1992 by Duke University.

Published by Duke University Press


518 Journal of Health Politics, Policy and Law

based agencies has increased significantly. Despite a declining federal role in funding community mental health centers, by 1989 there were approximately 2,200 community-based mental health agencies in the United States. Continued emphasis on hospital census reduction assures that the number of agencies will keep growing for the foreseeable future. Federal regulations required grantees to offer a range of mental health services to all citizens without regard for their ability to pay. Typically these agencies determined their clients’ charges on a sliding fee scale based on the clients’ self-reported income. Though no longer funded directly by the federal government, most CMHAs (including many of those that never received federal funds) have continued to provide treatment to low- and middle-income clients at subsidized rates. In many areas, CMHAs are the only source of outpatient treatment for people who are uninsured and unable to pay for the full cost of their treatment. Federally initiated CMHAs were charged with treating indigent patients for two major reasons. First, there was a belief that insurance coverage for mental health care was inadequate, even for those who had private insurance. Second, policymakers viewed access to treatment as an economic issue as well as a concern about equity; early outpatient treatment may prevent a costly hospitalization, and spare clients and their families needless suffering. Because states remain the provider of last resort for people with serious mental disorders, untreated illness eventually becomes a costly problem for state government. Recently, however, there have been growing concerns that, over the past decade, competition for scarce funds may have caused agencies to reduce sharply the amount of care they give to clients who are unable to pay full cost (Kane 1989; Levine et al. 1989). These concerns reflect observations that competition among psychiatric hospitals appears to have grown over this period (Dorwart and Schlesinger 1988) and that cutbacks in government and corporate spending for mental health care coupled with competition from other providers have squeezed the budgets of CMHAs (Jerrell and Larsen 1985). To date, however, there is little information on the extent to which these changes have affected outpatient mental health care providers, nor is it clear what these effects would be. Some observers fear that competition will result in greater inequities between haves and have-nots. They speculate that competition may reduce the amount of subsidized care available, increase out-of-pocket costs to consumers, or promote “cream skimming” of healthy individuals (Thurow 1985; Aiken and Blendon 1986; Menzel 1987). Although it may set the stage for these outcomes, competition per se does not lead inevi-



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tably to any of them. If, for example, providers have incentives to give a reasonable amount of subsidized care and to treat clients with severe illness, competition may not produce inequities (Fisher et al. 1991). Similarly, a strong mission to maintain broad access, which was a cornerstone of the community mental health movement, may deter providers from refusing to treat people who cannot cover the costs of their own care. Knowledge of how competition affects the general performance of CMHAs is also critical because states increasingly rely on CMHAs to play the lead role in maintaining clients with severe illness in their own communities. Many states view contracting with private agencies as an attractive way to provide this care and, possibly, to eliminate the “twotier” system in which insured clients buy treatment from private providers and indigent clients get treatment at public facilities. But if competition undermines the financial health of CMHAs, they may be unable to fulfill their duties adequately, thus resulting in lower-quality service and reduced access for all potential clients. Still, the answer to the question of how competition affects CMHAs is not obvious. Since CMHAs are largely nonprofit and public entities they may react differently from for-profit providers who seek to maximize profit. Also, in the context of a dramatic shift from hospital- to community-based treatment, demand for outpatient treatment may have kept pace with supply, thus reducing the importance of competition. h b lished research gives us few clues about how much competitive pressure is exerted on CMHAs or about how they respond to competition. Competition and Mental Health Care Providers

The concept of economic competition includes both structural and behavioral components. The structural aspect includes such factors as economic demand, the number of firms in a given market, and their respective market shares. The behavioral component of competition consists of the strategic behavior of firms, usually in response to structural competition. For example, in response to a declining market share, a firm may increase its advertising, cut costs, or engage in practices designed either to counter the effects of a smaller market share or to recapture its position in the market. Some of the strategic behaviors ascribed to competition arise from a firm’s desire to maximize profits and thus may not apply to a market composed mainly of nonprofit and public providers. However, it is the belief that health care providers will change their behavior in response




to competition that underlies arguments both for and against increased competition. Studies of competition among health care providers usually infer behavioral competition from measures of structural competition, but numbers of providers and indices of market concentration are determined by factors like the demand for treatment and, in the case of CMHAs, the number of other providers who might serve as substitutes. Using measures such as the number of providers or concentration of market power to represent competition makes it difficult to know which outcomes result from competition and which are related to background factors that influence the number of providers in a given market. White and Chirikos (1988) argue that researchers should draw inferences about the conduct of firms from structural indicators “only if . . . background supply and demand determinants are held constant” (p. 257). We will examine one method of holding background factors constant in our discussion of the demand for treatment. Market Structure

Structural competition is typically measured by assessing the dispersion of market power. As the number of providers increases, the likelihood that a single provider or small group of providers can dominate the market decreases. The market structure for outpatient mental health care includes several types of providers: CMHAs, hospitals, managed care organizations, and private practitioners. Thus, the number of private practitioners or other types of providers in a CMHA’s market area could affect its operations. From 1980 to 1986 the number of new outpatient cases per 100,000 population remained relatively stable, but the number of CMHAs increased by more than 20 percent. During the same period the number of hospitals offering outpatient psychiatric treatment grew by 43 percent (NIMH 1990). Many states require insurers to give a defined level of coverage for outpatient mental health treatment. These mandated benefits, in concert with vendorship laws, spurred significant growth in the number of private practitioners during the 1970s and 1980s. Vendorship laws, which require insurers to reimburse directly psychologists, social workers, or providers from certain other disciplines, encouraged more therapists to enter private practice (Shatkin et al. 1986). In the decade ending in 1985, the number of licensed psychologists more than doubled (NIMH 1990). And, between 1970 and 1990, the number



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of psychiatrists per capita in the United States nearly doubled (Dorwart et al. forthcoming). Mental health providers may compete for insured clients, for government contracts, or for contracts with private purchasers, e.g., for services like employee assistance programs (EAPs). But not all providers compete with equal intensity on all fronts. For example, private practitioners and managed care companies like health maintenance organizations (HMOs) and preferred provider organizations (PPOs) may tend to focus primarily on insured clients and secondarily on contracts with private entities. Since bidding requirements for government mental health contracts often favor nonprofit specialty care providers, private practitioners and managed care organizations are somewhat less likely to compete for government contracts. NIMH data (1990) show that CMHAs depend on government funding for over 80 percent of their revenues; therefore, competition for government contracts may be most important for them, followed by competition for insured clients and private contracts. Intense competition for government funds and for insured clients could seriously impair an agency’s ability to provide subsidized care. Demand

The competitiveness of markets is determined by the demand for as well as the supply of treatment. Two markets with an equal capacity for providing services may have very different levels of demand and thus varying levels of competitiveness. Studies of individuals’ demand for mental health treatment show that a number of factors may influence their decision to seek treatment and the amount of treatment they use. Income, age, ethnicity, marital status, education, employment, insurance coverage, and the region of the country in which a person lives may each influence demand for treatment (McGuire 1981; Horgan 1986; Wells et al. 1986). Policy researchers should be cautious, however, when using these variables to predict demand for CMHA services. The studies did not differentiate among service providers, and demand for CMHA services could be different from that for treatment from other types of providers. Moreover, when measured in the aggregate, some variables associated with individual demand may be interpreted quite differently. For example, at the individual level, demand increases as income rises (McGuire 1981;Wells et al. 1986);but area-based studies of the need for mental health treatment have found that greater need for treatment is associated with lower per capita income levels (Holzer et al. 1988). Unem-




ployed individuals are more likely to need psychiatric treatment (Dooley and Catalan0 1988; Dooley et al. 1988), but high unemployment rates may signal decreases in the number of people with health insurance as well as reduced government spending for mental health (Seawright et al. 1989). Other factors, such as population density and state policies, may also contribute to the demand for treatment. Epidemiologicalstudies show that cities have higher prevalences of mental illness (Blazer et al. 1985) and, therefore, are likely to have higher per capita demand than rural areas. Mandated insurance coverage for mental health treatment (Frisman et al. 1985) and spending for community mental health are also likely to increase the effective demand for CMHA services, that is, the number of people actually seeking treatment. While all of these factors may help determine the demand for outpatient treatment, most are also likely to influence the number of providers offering care. If there are no significant barriers to entry, markets with high levels of demand will attract more providers than areas of lower demand. In a study of hospitals, White and Chirikos (1988) found that a measure of competition appeared to increase costs, but when they took the effects of demand on the concentration of hospital market shares into account, using a simultaneous equations model, competition did not affect costs significantly. They concluded that higher costs were a function of greater demand rather than changes in hospital behavior resulting from competition. Thus, analyzing how economic demand for treatment affects the supply of providers may offer more accurate clues about how providers respond to competition than inferences drawn from a simple analysis of structural competition. Subsidized Treatment

There are several ways an agency can finance subsidized care. Government contracts and entitlements pay for a large portion of subsidized mental health treatment, but CMHAs can increase the amount of subsidized care they give by raising money from individual donors or by soliciting grants from private charities. In addition to these direct subsidy approaches, a provider can subsidize treatment indirectly by using excess revenues from insured patients or private contracts to pay for care given to people who do not have insurance. Using the indirect subsidy approach will lower the percentage of an agency’s total visits that are subsidized but may increase the amount of subsidized care it can give. Agencies using only the direct subsidy approach might appear to be more concerned about



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the public good because a high percentage of the treatment they provide is free or subsidized; but agencies that successfully combine the direct and indirect approaches may be able to offer more subsidized care than those that focus on only one strategy. Stiff competition for either, or both, types of funding is likely to lower the amount of subsidized care an agency supplies and may adversely affect its general financial stability. An agency’s ability to implement successfully one of these strategies depends on economic demand and the need for treatment in its service area. Agencies located in areas of high economic demand, where incomes are relatively high and a significantportion of the population has adequate insurance coverage, may be better able to subsidize treatment with excess revenues. The indirect subsidy approach may be less viable in relatively poor areas or in markets where competition from private practitioners reduces the amount of insurance revenue a CMHA can capture. In such cases direct subsidization may be the only option. Price, Quality, and Efficiency

The market for mental health services has been characterized as monopolistically competitive (Klevorick and McGuire 1987), meaning that providers compete on the basis of both price and quality. But the relative importance (and meaning) of these two factors may vary depending on the potential purchaser. These differences stem from varying consumer incentives and difficulties in judging quality. While most governmental purchasers specify standards for quality, their standards are often minimal and they usually give price greater weight in decision making (Davidson et a1. 1991). Insured clients, insulated from having to pay directly for services, may focus more on quality than on price. Unfortunately, information on the effectiveness of various therapies or providers is rarely available. This leads insured clients to emphasize observable provider characteristics and convenience in choosing a therapist or treatment facility. The relative importance of price and quality to private purchasers may depend on the particular service they are buying; however, private purchasers have significant incentives to consider both price and quality. Because they pay directly for services and, in the cases of individuals or programs focused on employees, may stand to benefit from effective treatment, private purchasers are more likely to weigh both aspects when purchasing mental health care. Still, the difficulty of judging the quality of treatment is a problem for all consumers and purchasers. State governments are so concerned about this issue that many have chosen to buy




services primarily from public and nonprofit agencies,where they believe the lure of profits is less likely to induce providers to skimp on quality. Although it reduces incentives to give substandard care, removing the profit motive may also lower incentives for efficiency. In theory, pricebased competition increases efficiency. Increased efficiency is important because money for mental health treatment is finite; more efficient service delivery may increase the number of people who can be served. Unfortunately, it is hard to measure the efficiency of CMHAs because quality is usually poorly defined and difficult for the unskilled observer to identify. Without a way to judge accurately the quality of treatment, it is impossible to know if lower unit costs result from greater efficiency or from offering a lower-quality product (Weisbrod 1988). Efficiency is also a reason for states buying services from private providers instead of offering them directly through public agencies. Nonprofits have greater potential for efficiency because they can be more flexible than bureaucratically controlled public agencies; but the problem of monitoring the quality of services may undermine the fulfillment of this expectation. Considering hospitals, Newhouse ( 1970) argued that nonprofits are less efficient than for-profits because they tend to provide higher-quality services than consumers would purchase if they paid for treatment directly, instead of through health insurance. There is, in fact, some evidence that when price and diagnosis are held constant, nonprofit mental health agencies provide more intensive care per episode of treatment than do public agencies (Hall and McGuire 1987). Nonprofits can raise funds by treating insured clients or by soliciting charitable contributions, but they can also use the additional money for higher salaries, more attractive facilities, or other amenities instead of providing additional services. Thus, even if nonprofit CMHAs are more efficient, there is no guarantee that the savings will be converted to additional treatment for indigent clients. Shifting from public provision to services purchased from nonprofit agencies could actually decrease the supply of services available, rather than increase it as economic theory and conventional wisdom suggest. Ad ministrators' Views of Cornpetition

Most CMHA administrators report competition from at least one source. In a survey, described below, we asked administrators of mental health agencies to rate on a three-point scale the extent to which they face competition from other providers. They rated the extent for insured clients,



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35

6

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Private htitioners

30

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$ *s

25

. I

z %

20 15

: B

10

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k

5 0

insured Clients

Government

Contracts

Private Contracts

Figure 1 Administrators’Ratings of the Extent of Competitionfrom Other Providers for Clients and Contracts Note. The columns show the percentage of administrators who answered “toa great extent,” when asked to rate the competition they faced from other providers for clients and contracts.

for government contracts, and for private contracts as being either not at all, to some extent, or to a great extent (Figure 1). Administrators chose private practitioners as the group from which they most often faced extensive competition for insured clients, followed by health maintenance organizations and other mental health agencies. While other mental health agencies were less often sources of extensive competition, administrators saw them as more likely than HMOs to compete at all. This finding is probably due to the fact that agencies were more likely to have another mental health agency in their market area than to have an HMO. When competition was for government contracts, other CMHAs were far more likely than private practitioners or HMOs to be identified as competitors. Ratings of competition for private contracts were more ambiguous, with all three types of providers roughly equal in the percentage competing to a great extent. Since CMHAs derive the majority of their funding from government sources, the administrators’ ratings suggest that other CMHAs may be their most important competitors. But in the market for insured clients, private practitioners appear to be the most formidable challengers. Thus, both types of providers may affect the amount of subsidized care a CMHA can provide. The ratings suggest, however, that private practitioners and other CMHAs achieve this effect through different means; the former by reducing the pool of insured clients treated at CMHAs and the latter




by reducing the amount of government funds available. It is important to remember, however, that these are administrators’ perceptions and, therefore, subject to a variety of biases. To test the robustness of these perceptions, we used more objective structural measures of competition along with measures of demand and agency characteristics to examine the effects of competition on community mental health agencies. Hypotheses

Since the vast majority of CMHAs are nonprofit or public, we expected that, in comparison to other demographic and economic factors, competition would play a moderately influential role in explaining the supply of subsidized visits. We hypothesized that, based on administrators’ perceptions, other CMHAs would be the most significant source of competition for outpatients, and private practitioners and HMOs would be somewhat less important. We further hypothesized that, as competition from all sources increased, agencies would reduce the amount of subsidized care they gave. A possible alternate hypothesis is that “creaming” or shifting of unprofitable clients to CMHAs by other providers would actually increase the amount of subsidized care they give. The latter hypothesis is consistent with the development of a two-tier system of care for insured and uninsured clients. Our data did not allow us to test the idea that nonprofit CMHAs are more efficient than public agencies, but we did examine the notion that nonprofits provide more subsidized care than public CMHAs. We also hypothesized that soliciting funds from nongovernment sources would increase an agency’s ability to subsidize treatment. Finally, we suspected that a combination of longevity and favorable treatment by state and federal government would give federally initiated agencies a competitive advantage over other agencies. We predicted that this advantage would result in more subsidized visits. Methods

We analyzed data from a survey conducted jointly in 1989 by the Center for Social Policy (at the John F. Kennedy School of Government, Harvard University) and the National Council of Community Mental Health Centers (NCCMHC). We used measures of competition, demand, regulatory climate, and agency characteristics to predict the number of visits



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provided to consumers free or at prices below the cost of the service. We describe these variables in greater detail below. Sample Description

A total of 633 (59 percent) out of 1,070 multiservice agencies and outpatient clinics returned questionnaires. CMHAs from all fifty states responded. Of these agencies, 426 reported on subsidized care. Nonprofit agencies comprised the majority of r6spondents with 68 percent, 28 percent were publicly owned, and 4 percent were for-profit organizations. These percentages compare favorably to those obtained by the National Institute of Mental Health’s Inventory of Mental Health Organizations. Further analysis of respondents revealed small biases in favor of NCCMHC members , community mental health centers initiated with federal funds , and agencies located outside the Northeast. To correct for the nonrandom response pattern, we computed a hazard rate and included it as an independent variable in our regression analysis.I Defining Market Areas

There are a variety of ways to define health care market areas: geopolitical boundaries, distance between competitors, and patient origin (Garnick et al. 1987). In this study we asked agency administrators to name each county from which their organization drew 10 percent or more of its clientele. Then we constructed market areas for each agency. Thus, the smallest possible market area was one county. This method may have led us to overestimate market size in some cases. However, since 75 percent of the agencies responding to the survey told us they defined their service area as a county or group of counties, this method was accurate in most cases. We eliminated from the analysis mental health centers located in Alaska, where county divisions are not relevant. Using counties as our smallest geographic unit allowed us to match data supplied by agencies with information on sociodemographic and demand characteristics from the Area Resource File (U.S. DOC 1988), the Inventory of Mental Health Organizations (NIMH 1990), and other geographically based data sources. 1 . A series of variables indicating whether an agency was an NCCMHC member, its location, and if it was initiated with federal funds was used to predict whether or not an agency responded to the survey. Predicted values from the probit analysis using these variables were entered into the equationhi =f(zi)/l - F ( z i ) , i.e., the hazard rate equals the density of the negative predicted values divided by 1 minus the cumulative distribution of those values (Berk 1983).




Measuring Competition

Competition is an often-used but poorly understood term. The operational definition of competition typically focuses on market structure. Economists often measure competition by examining the dispersion of market power. When a significant portion of the market for a particular good is concentrated in the hands of a few providers, there is little competition, but when a market includes many firms, none of which dominates the market, competition is high. The most widely accepted economic measure of competition is the Herfindahl Index, which is the sum of the squared market shares of all firms in a market. Unfortunately, this measure requires information on the number of units sold by each firm in the market, which is often difficult to obtain. Because we lacked complete data on the market share of each provider, we used the number of providers per 100,000 population as our structural measure of competition. For each market area, we computed a measure of competition from mental health organizations, from health maintenance organizations, and from psychiatrists. Market-level information on other private practitioners was not available; however, we included categorical variables indicating separately the presence of vendorship laws for psychologists and for social workers. We estimated two separate models of competition. The first model treated structural measures as exogenous, or independent of background factors. In the second model, we treated the number of outpatient facilities per 100,000 population, the number of HMOs per 100,000,and the number of practicing psychiatrists per 100,000 as endogenous variables. We estimated the effects of demand and the supply of other providers on each structural measure, then used the results of these equations as variables to predict the number of subsidized visits given by a CMHA. The second model attempts to separate the purely competitive effects from those effects that are related to background factors that influence the number of providers in a given market area. Because demand and supply factors affect both the number of treatment providers in a given area and the amount of subsidized care a particular CMHA supplies, we accounted separately for these effects. Estimating the influence of these factors on the number of each type of provider using ordinary least-squares regression accounted for the relationship between demand and the number of providers in markets. Using the predicted values from these estimates in the second regression allowed us to observe the direct effects of demand and the effects of the number of providers (taking into account the influence of demand) on the number of subsidized visits an agency supplied. Published by Duke University Press


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Table 1 Variables Used in Regression Models of Competition among Providers of Mental Health Care

Mean

Variable

Number of Subsidized Outpatient Visits 22,167 10.00 Number of Subsidized Outpatient Visits (log) Outpatient Mental Health Facilities per 100,OOO Population 2.53 HMOs per 100,OOO Population 0.30 Psychiatrists per 100,OOOPopulation 9.67 Per Capita Income (log) 9.40 Unemployment Rate (1 986) 7.31 Median Years of School-Residents Aged 25 and Older 12.38 0.28 Percentage of Population under Age 18 0.12 Percentage of Population over Age 65 Percentage of Population Belonging to a Minority Group 0.14 Percentage of Population Living in Urban Areas 67.40 CMHA in a State with Mandated Outpatient Insurance Benefits 0.57 Percentage of State Population Uninsured 16.51 Per Capita State Spending for Community Mental Health 10.81 CMHA in State with a Vendorship Law for Social Workers 0.31 CMHA in a State with a Vendorship Law for Psychologists 0.88 CMHA Publicly Owned 0.28 Initiated with Federal CMHC Funds 0.41 CMHA Located in the West 0.14 CMHA Located in the Midwest 0.35 CMHA Located in the South 0.28 CMHA Receives Contributions from Charities 0.38 CMHA Solicits Contributions from Individuals 0.24 Hazard (Adjustment for Sampling Bias) 3.22

Standard Deviation 76,486 1.35 1.44 0.52 11.64 0.20 2.79 0.04 0.18 0.03 0.13 26.51 0.50 4.14 5.64 0.46 0.32 0.45 0.49 0.35 0.48 0.45 0.49 0.43 4.56

Measures of Demand and Agency Characteristics

In addition to our measures of competition, we included several variables to measure demand, agency characteristics, and location (Table 1). Factors such as per capita income, unemployment rate, region of the country in which the CMHA was located (Northeast, South, Midwest, or West), and the percentage of population living in urban areas were included in our model. Several state-level demand variables were also used to predict subsidized visits. These included the percentage of the population that is uninsured, state spending for community mental health, and whether or not the agency is in a state with mandatory insurance coverage of outpatient mental health treatment. Published by Duke University Press



We used two categorical variables to indicate the agency’s ownership (public or private) and whether the agency had been initiated with federal community mental health center funds. The latter variable combines many different factors that might influence an agency’s response to competition. In 1980 the federal government discontinued direct funding for mental health centers, so federally initiated agencies must have been in operation for at least nine years at the time of the study and in many cases much longer. Since we do not know how long each agency had been in operation, this variable is, in part, a measure of longevity. Also, federal funding for capital and operating expenses may have given these community mental health centers a competitive advantage over others, during the first years of operation. Finally, since federally initiated agencies were required to provide services without regard to clients’ ability to pay, they could have retained this orientation and thus be less likely to restrict the amount of subsidized care they give. We included two categorical measures indicating whether the agency received funds from charities or solicited contributions from individuals and used these variables to examine CMHAs’ ability to increase the amount of subsidized care they provide, in addition to that financed by government programs. Results

Because of large variations in reported visits, the dependent variable was transformed into its natural logarithm. The first column of Table 2 shows the results of our first regression model, which treats competition as independent of background factors. The coefficients show a negative relationship between the number of mental health facilities per 100,000 and the log of reduced-price visits. The relationship is significant at the p < .0001 level. Results for HMOs and psychiatrists per 100,000 were also negative, but not statistically significant. Variables indicating the presence of vendorship laws for psychologists and social workers also failed to pass the .05 statistical criterion. None of the demand variables had a significant effect on subsidized care. Public agencies showed a p < .05 trend toward giving more subsidized visits than did their privately owned counterparts. Federally initiated agencies provided substantially more reduced-price visits than did other agencies ( p < .0001). Results of the two-stage least-squares (2SLS) analysis are presented in Tables 2 and 3 . Table 3 shows how the three endogenous variables for the number of outpatient facilities, HMOs, and psychiatrists per 100,000



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Table 2 Determinantsof Subsidized Visits to Community Mental Health Agencies (t-statistics in parentheses) Subsidized Visits (log) 2SLS

Subsidized Visits (log) Normalized

( -4.488)a

-0.03 1d (-0.248)

-0.164d (-0.248)

HMOs per 100,OOO Population

-0.087 (-0.722)

- 1.261b*d (-2.387)

-0.176b.d (-2.387)

Psychiatrists per 100,OOO Population

-0.004 (-0.538)

( -2.6 18)

(- 2.6 18)

-0.081 (-0.143)

-0.012 (-0.143)

Subsidized Visits (log)

Variable Outpatient Mental Health Facilities per 100,000Population

Per Capita Income (log)

-0.21 1

-0.645 (- 1.275)

Unemployment Rate ( 1986)

-0.034a.d

-0.229

a*d

-0.014

-0.047

-0.098

( -0.504)

(- 1 S77)

(- 1 S77)

Percentage of Population Living in Urban Areas

0.001 (1.666)

0.002a (3.624)

0.304 a (3.624)

CMHA in a State with Mandated Outpatient Insurance Benefits

0.010 (0.070)

0.133 (0.938)

0.049 (0.938)

Percentage of State Population Uninsured

0.005 (0.279)

0.006 (0.293)

0.019 (0.293)

Per Capita State Spending for Community Mental Health

-0.014 (- 1.191)

-0.010 (-0.828)

-0.042 (-0.828)

CMHA in a State with a Vendorship Law for Social Workers

0.065 (0.409)

-0.034 (-0.197)

-0.012 (-0.197)

CMHA in a State with a Vendorship Law for Psychologists

0.215 (1.115)

0.293 (1.481)

0.070 (1.481)

CMHA Publicly Owned

0.276b (2.014)

O.24Oc (1.738)

0.08OC (1.738)

Initiated with Federal CMHC Funds

0.741 a (5.694)

0.777a (5.907)

0.283a (5.907)

CMHA Receives Funds from Charities

0.053 (0.382)

0.026 (0.184)

0.009 (0.184)

CMHA Solicits Contributionsfrom Individuals

0.001 (0.058)

0.065 (0.401)

0.021 (0.401)

0.004

0.013 (0.280)

Hazard (Adjustment for Sampling Bias)

-0.010 (-0.072)

(0.280)




Table 2 Continued

Subsidized Visits (log)

Subsidized Visits (log) 2SLS

Subsidized Visits (log) Normalized

Intercept

19.5tia (4.07)

13.846b (2.530)

0.003 (0.060)

Adjusted R 2

0.169

0.152

0.152

Variable

a. p < .01. b. p < .05. c. p < .lo. d. Endogenous variable (see Table 3)

population were constructed. Each model is unique, reflecting differences in the factors determining the various provider types and the need to minimize collinearity among explanatory variables in the second stage. The finding, shown in Table 3, that the log of per capita income was a positive predictor of psychiatrists per 100,000 and a negative predictor of CMHAs per 100,000illustrates the complexity of the relationship among variables. Although there were some common predictors, the factors contributing to the number of each type of provider appeared to be quite different. The rather large differences in the size of coefficients in the exogenous and endogenous models show that the number of each type of provider, but especially HMOs, is heavily influenced by demand. Coefficients for the endogenous variables for CMHAs, HMOs, and psychiatrists, shown in column 2 of Table 2, were all negative in the 2SLS analysis, however the coefficients for HMOs per 100,000and psychiatrists per 100,000 were statistically significant ( p < .05). Results for federally initiated and public centers were consistent with results from the first model. The coefficient for the percentage of population living in urban areas was positive and statistically significant, indicating more subsidized care in urban settings. Variables for receiving charity contributions and fund-raising were positive but not significant. In order to compare the relative contribution of factors in the second model, variables were transformed into standardized units (mean = 0, standard deviation = 1). Comparing coefficients for the standardized variables (betas), psychiatrists appear to exert slightly greater influence on subsidized care than do HMOs, but more urban settings and federally initiated status each produced greater change in subsidized visits than either of the competition variables.



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Table 3 Determinants of Variables Used in 2SLS Analysis of Competition among Mental Health Care Providers (t-statistics in parentheses) Mental Health Facilities per

100,Ooo Population

Variable Outpatient Mental Health Facilities per 100,Ooo Population HMOs per 100,OOO Population

0.258b (2.113)

Psychiatrists per 100,OOO Population

0.027 a (3.479)

Per Capita Income (log) Unemployment Rate ( 1986) Median Years of SchoolResidents Aged 25 and Older Percentage of Population under 18 Percentage of Population over 65

-2.063a (-4.003)

Psychiatrists per100,000 Population

HMOs per 100,OOO Population

1.003a (3.535)

0.047b (2.506)

1.207' (1.654)

0.005' (1.668) 24.890a (8.689)

-0.019

0.038 (1.323) 0.704a (3.362) -1.187 (-0.369) 12.2Ooa (4.151)

(- 1.596)

1.028 (0.784)

- 1.094 (-0.864)

-21.647

-0.384 (-0.319)

(- 1.213)

- 1 .537a (-2.749)

3 1.093a (9.837)

Percentage of State Population Uninsured

-0.084 a (-4.91 1)

0.121 (0.77 1)

0.255 (1,708)

-0.566 -0.573)

CMHA in a State with a Vendorship Law for Psychologists

-0.146 (-0.758)

0.088 (1.075)

-95.049a (-5.125)

Percentage of Population Belonging to a Minority Group

CMHA in a State with a Vendorship Law for Social Workers

-0.263 (- I .204)

-0.015 (- 1.465)

1.123 (0.994) 0.001 a (2.977)

Percentage of Population Living in Urban Areas CMHA in a State with Mandated Outpatient Insurance Benefits

2.561 a (3.037)

Per Capita State Spending for Community Mental Health

0.175b (2.445)





Clark and Dorwart

CMHAs 535

facilities significantly affects subsidized care, but these effects appeared to be due primarily to variations in the demand for treatment, rather than the behavior of CMHAs themselves. This interpretation is consistent with other analyses of the data that showed few changes in management practices as a result of increased competitionfrom other CMHAs (Clark 1991). When the effects of demand on the supply of providers were taken into account in the endogenous model, HMOs and psychiatrists emerged as more important influences. It is not clear exactly how larger numbers of HMOs and psychiatrists cause CMHAs to reduce subsidized treatment, but the administrators’ ratings, shown in Figure 1 , offer one plausible explanation. Administrators rated pressure from HMOs and private practitioners highest when competition was for insured clients. Even though CMHAs derive a large proportion of their budgets from government sources, income from insured clients may be an important source of revenue for subsidizing outpatient treatment. It is unlikely that, as a group, the outpatient clientele of CMHAs have characteristics identical to those of groups served primarily by HMOs or psychiatrists, but there is apparently some overlap. When competition is lower, CMHAs may treat a larger number of insured clients and, therefore, have more money for subsidized treatment. Growing numbers of alternate providers, particularly those that clients might perceive to be of higher quality, reduce revenue available for treating low-income clients. Our findings did not support the idea that nonprofit agencies provide more subsidized care. In fact, it appears that public agencies may provide more care. Further, we found no evidence that agencies significantly increase the number of subsidized visits by raising money from charities or individuals. The greater flexibility implied by nonprofit ownership does not appear to help them provide additional subsidized treatment. In both models, agencies initiated with federal funds provided more subsidized visits than other CMHAs. It is difficult to isolate a single explanation for this finding; it could be due to longevity, favorable treatment from state mental health authorities, continued funding through federal block grants to states, economies of scale, or a sense of mission retained from earlier federal requirements. As we discussed above, agencies initiated with federal community mental health center funds are likely to have been in operation for a relatively long period of time, allowing them to build consumer loyalty and to develop referral relationships.Windle et al. (1987) showed that federally initiated centers have had a strong influence on the supply of care in their service areas. They may influence markets in other ways as well.




Federal block grants to states still allow some funding for CMHAs and, although states differ in their relationships with community mental health agencies, many facilities that were begun with federal funds still enjoy a special status when public funds are allocated. In some states, these agencies have a virtual monopoly on public mental health expenditures in their catchment area. Because they tend to be larger than other agencies, they may be in a better position to bid on contracts with large purchasers, but size alone may not explain all of the difference in subsidized visits provided. Despite the idea, advanced by some, that federally initiated agencies have moved away from their original goal of access for all (Woy et al. 1981 ; Naierman et al. 1978), these providers may still place universal access to care high on their list of priorities. In a secondary analysis of data from the survey, we found differences in management practices that may explain a portion of the difference between federal initiates and other agencies. Comparing the management practices of federally initiated centers with other CMHAs, we noted that the former tended to be more aggressive in collecting revenue, and were more likely to have private contracts. They were also somewhat more likely to cut administrative costs and to emphasize group treatment over individual treatment. Some observers interpret such management practices as evidence that federal initiates place greater value on private than on public clients (Woy et al. 1981), but these same practices may increase subsidized care by raising additional revenues and by making more efficient use of existing dollars. The latter interpretation suggests that, as a group, these centers have not abandoned their original mission but are instead seeking to fulfill their goals by balancing entrepreneurial management strategies with more traditional public orientations. There is probably no single “best” explanation for differences between federal initiates and other CMHAs. Rather, some combination of the factors we have described make federally initiated centers more stable and more welcoming community agencies for clients who need subsidized care. Community mental health agencies depend heavily on public funds for their survival; nevertheless, they are subject to market forces in much the same way as other small businesses. Competition, by reducing revenues, appears to reduce CMHAs’ ability to subsidize care. Traditionally, CMHAs have been an essential source of community treatment for people who for financial or other reasons cannot get treatment elsewhere. If CMHAs are to continue playing this role effectively, we need to understand more completely how market forces shape their behavior.



Clark and Dorwart

9

CMHAs 537

Conclusions

Our analysis indicates that, at the agency level ,competition reduces access to treatment. Even if competition among CMHAs is low, high concentrations of private practitioners or HMOs may impede access. It is important to note, however, that our data do not allow us to draw inferences about how competition affects the total amount of subsidized care provided at the market level. While it is conceivable that the entire burden for subsidized care is simply spread across a larger number of providers, it seems unlikely that psychiatrists in private practice or HMOs would provide a large amount of subsidized treatment,especially under conditions of increasing competition. There appears to be no way that agencies can consistentlycounteract the forces of competition, although federally initiated CMHAs appear to be somewhat less susceptible to the vagaries of the market. For an individual agency, the amount of subsidized care it provides seems to be largely determined by factors beyond its control. Soliciting funds from charities or individuals may allow some agencies to provide more outpatient care, but on the whole, these activities do not seem to increase the number of subsidized visits. Increasing the percentage of care given to insured clients, in hopes of cross-subsidizingcare, may not be a workable strategy in the face of competition from private practitioners or HMOs. This suggests either that these efforts do not raise a sufficient amount of revenue to increase subsidized visits or that these funds are consistently used for services other than outpatient treatment. Our data also suggest that states hoping to improve access by contracting with private agencies could actually reduce access. Nonprofits had no advantage over public agencies in their ability to subsidize care and, in fact, seemed to provide less of it. But since our study did not control for differences in the quality of treatment we do not know if public and private agencies offer treatment of comparable quality, or even if they serve the same types of clients. If we assume, for the sake of argument, that the services of public agencies are either of equal quality or of lesser but still acceptable quality in comparison to those provided by a private CMHA, then there appears to be no advantage to contracting with a private agency to provide outpatient mental health care. But, if the care provided by public agencies is substandard, then we could make an argument for contracting with private agencies for higher-quality service. Our data do not, however, support an argument for contracting with private agencies on the basis of increased access to care for financially disadvantaged consumers.




As a strategy for controlling costs, the effects of competition are not clear, but some apparent cost savings might be achieved by reducing the amount of care available to clients who need but cannot afford services. These reductions could actually result in higher costs elsewhere, for example, through increased hospitalization. Not everyone served by CMHAs has a serious mental illness (Windle et al. 1988), and it is not possible with these data to tell who is being denied subsidized care at CMHAs. Our data suggest, however, that CMHAs, by themselves, can do little to increase access. The only workable alternative for improving financial access to CMHAs appears to be government intervention. We need further study to increase our understanding of how competition affects access to treatment. Our analysis suggests, however, that states should monitor access to outpatient treatment carefully, particularly in areas with high ratios of providers to population. If the goal of increasing competition is to reduce costs without regard to access, then market-oriented strategies may be effective. By depending on markets to cut costs, however, states may find that cost reductions are achieved at the expense of individuals who truly need treatment. It is unlikely that policies encouraging competition are, by themselves, sufficient to ensure that we achieve socially desirable goals. We must combine market-oriented strategies with careful government monitoring to avoid unintended consequences.

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Seawright, H. R . , P. J. Handal, and T. M. McCauliffe. 1989. The Relationship between Public Mental Health Admission Rates, Institutional Constraints, and Unemployment. Administration and Policy in Mental Health 17:33-42. Shatkin, B. F., L. K. Frisman, and T. G. McGuire. 1986. The Effect of Vendorship on the Distribution of Clinical Social Work Services. Social Service Review 60: 437-48. Thurow, L. C. 1985. Medicine versus Economics. New England Journal of Medicine 3131611-14. U.S. DOC (U.S. Department of Commerce). 1988. User Documentation for the ODAM Area Resource File (ARF) as of March 1988. Springfield, VA: U.S. Department of Commerce, National Technical Information Service, Office of Data Analysis and Management, Bureau of Health Professions. Weisbrod, B. 1988. The Nonprofit Economy. Cambridge, MA: Harvard University Press. Wells, K. B., W. B. Manning, N. Duan, J. P. Newhouse, and J. E. Ware. 1986. Sociodemographic Factors and the Use of Outpatient Mental Health Services. Medical Care 24 :75-85. White, S. L., and T. N. Chirikos. 1988. Measuring Hospital Competition. Medical Care 26 :256-62. Windle, C . , R. D. Bass, and L. Gray. 1987. The Impact of Federally Funded CMHCs on Local Mental Health Service Systems. Hospital and Community Psychiatry 38 :7 29-34. Windle, C., J . W. Thompson, H. H. Goldman, and N. Naierman. 1988. Treatment of Patients with No Diagnosable Mental Disorders in CMHCs. Hospital and Community Psyhiatr), 39:753-57. Woy, J . R., D. B. Wasserman, and R. Weiner-Pomerantz. 1981. Community Mental Health Centers: Movement away from the Model? Community Mental Health Journal 17:265-76.


Creating a mental health consultation package for community agencies.

Training Community Mental Health Agencies in Cognitive Therapy for Schizophrenia.

A model for the introduction of infant mental health services to community mental health agencies.

A mental health consultation-education program with group service agencies in a disadvantaged community.

Addressing disparities in mental health agencies: strategies to implement the National CLAS Standards in Mental Health.

Fiscal resource development for state mental health agencies.

Rebranding "community mental health".

Community mental health centres.

Results of a pragmatic effectiveness-implementation hybrid trial of the Family Check-up in community mental health agencies.

Community mental health in California.

Radio psychiatry and community mental health.

Psychoanalysis and the community mental health movement.

A case for range and versatility within agencies in planning mental health services.

Association of mandated language access programming and quality of care provided by mental health agencies.

Community mental health in Italy today.

Community mental health accreditation: a pilot study.

Community influences on mental health program evaluation.

Community-oriented integrated mental health services.

Community mental health initiatives in Pakistan.

Taking mental health into the community.

Community Care in the Mental Health Services.

Police as a community mental health resource.

Imroving mental health through community action.

Letter: More on community mental health.