Does Deinstitutionalization Increase
Jangho Yoon and Tim A. Bruckner
Objectives. (1) To test whether public psychiatric bed reduction may increase suicide
rates; (2) to investigate whether the supply of private hospital psychiatric beds——sep-
arately for not-for-profit and for-profit——can substitute for public bed reduction without
increasing suicides; and (3) to examine whether the level of community mental health
resources moderates the relationship between public bed reduction and suicide rates.
Methods. We examined state-level variation in suicide rates in relation to psychiatric
beds and community mental health spending in the United States for the years 1982–
1998. We categorize psychiatric beds separately for public, not-for-profit, and for-profit
Principal Findings. Reduced public psychiatric bed supply was found to increase
suicide rates. We found no evidence that not-for-profit or for-profit bed supply com-
pensates for public bed reductions. However, greater community mental health spend-
ing buffers the adverse effect of public bed reductions on suicide. We estimate that in
2008, an additional decline in public psychiatric hospital beds would raise suicide rates
for almost all states.
Conclusions. Downsizing of public inpatient mental health services may increase
suicide rates. Nevertheless, an increase in community mental health funding may be
Key Words. Deinstitutionalization, suicide, community mental health, privatizat-
ion, psychiatric beds
Deinstitutionalization represents one of the most widespread changes in men-
tal health policy. This process has led to the massive transfer of severely
mentally ill persons out of institutional care in favor of community treatment
(Grob 1994). A crucial aspect of deinstitutionalization involves significant
structural changes in the public mental health system. From 1970 to 2000,
public psychiatric hospital beds dropped from 207 to 21 beds per 100,000
persons (Manderscheid et al. 2004). This reduction concerns mental health
professionals and policy makers because the declining capacity of public psy-
chiatric hospitals may jeopardize care for indigent, severely mentally ill pa-
tients that require treatment but lack sufficient economic resources.
rHealth Research and Educational Trust
Decreasing public psychiatric hospital beds (hereinafter public beds)
would be efficient if the demand for beds similarly declined. However, the
literature does not support this notion of efficiency; deinstitutionalization
rarely, if at all, followed reduced demand for inpatient psychiatric care. In-
stead, ideological rhetoric, welfare programs, and fiscal considerations by
states initiated and accelerated the process of deinstitutionalization (Cameron
1978; Gronfein 1985a; Mechanic and Rochefort 1990; Grob and Goldman
2006).Moreover, deinstitutionalization representsa raresocial policythat was
implemented faster and more extensively than anticipated (Mechanic and
Rochefort 1990). Thus, public bed availability may have dropped below the
level of demand. In this circumstance, public bed reductions may adversely
affect mental health for persons with severe mental illness in a community.
The last decades have also experienced rapid privatization of the inpa-
tient psychiatric market and proliferation of public community-based mental
health programs (Manderscheid et al. 2004). It is unclear whether these aug-
privatization does not influence the availability and quality of care, it should
not, ceteris paribus, alter mental health of severely mentally ill patients. How-
particularly for-profit hospitals, preferentially treat insured patients and those
with less severe, acute symptoms (Schlesinger et al. 1997; Mechanic 1999).
The clear distinction of service clientele across different ownership types im-
plies that private bed supply may not substitute for public bed supply. More-
over, due to its voluntary nature and chronic underfunding, community
mental health care maynotadequatelytreatseverely mentally ill patientswith
a history of dangerousness, co-occurring disorders or arrests (Lamb, Wein-
berger, and Gross 2004). Nevertheless, increased supply of public community
mental health resources provides free goods to the economically disadvan-
taged and may therefore buffer adverse effects of public bed reductions,
improving community mental health.
Our mainobjective is to examine the relationshipbetween the supply of
public beds, as a proxy for deinstitutionalization, and population mental
health. We focus on suicide rates as a measure of population mental health.
Despite recent declines in national prevalence (McKeown, Cuffe, and Schulz
Address correspondence to Jangho Yoon, Ph.D., M.S.P.H., Assistant Professor, Jiann-Ping Hsu
College of Public Health, Georgia South University, P.O. Box 8015, Statesboro, GA 30460-8015;
e-mail: email@example.com. Tim A. Bruckner, Ph.D., M.P.H., is an Assistant Professor at the
University of California at Irvine, Program in Public Health, Irvine, CA.
1386HSR: Health Services Research 44:4 (August 2009)
2006), suicide rates serve as a useful indicator of population mental health
becauseof their strongassociation withsevere psychiatric episodes (Blackand
Fisher 1992; Simpson and Tsuang 1996; Colton and Manderscheid 2006;
Miller, Paschall, and Svendsen 2006; Saha, Chant, and McGrath 2007). We
test whether private hospital psychiatric beds, separately for not-for-profit and
for-profit hospital psychiatric beds (hereinafter, not-for-profit beds and for-
profit beds, respectively), can replace public beds without increasing suicides.
We also analyze whether the relationship between public bed reduction and
suicide rates varies with the availability of public community-based mental
PRIOR STUDIES AND LIMITATIONS
Deinstitutionalization has also taken place, and been researched, outside the
United States. In Sweden, mortality due to suicides among patients with
(Salokangas et al. 2002). In Denmark, a significant negative association was
found between the number of psychiatric beds and suicide mortality (O¨sby
et al. 2000). A Norway study reported an increase in suicide mortality after
psychiatric bed reductions (Hansen, Jacobsen, and Arnesen 2001). In the
United States, Haugland et al. (1983) examined the mortality rate of 1,033
deinstitutionalized patients. The authors found that during a 31
period, patients were approximately eight times more likely to die of suicide or
accident than persons in the general population. This finding is in line with a
greater risk of suicide among young deinstitutionalized patients served in a
community mental health center (Pepper, Kirshner, and Ryglewicz 1981). In
contrast, Bachrach (1996) and McGrew et al. (1999) reported general improve-
ments in the quality of life and functioning among patients discharged and
treated in community settings due to the closure of state psychiatric hospitals.
been implemented without sufficient evaluation of possible health risks. Rel-
workhas several importantlimitations.Weaddressthe followinglimitationsin
the literature to inform policy in the era of community-based treatment.
First, the U.S. studies examined only subgroups of persons with severe
mental illness such as patients discharged from psychiatric hospitals (Hau-
gland et al. 1983) and former patients in state psychiatric hospitals who con-
tinued to receive treatment in the community after a discharge (Bachrach
Deinstitutionalization and Suicide1387
1996; McGrew et al. 1999). However, a reduced supply of public beds, ceteris
paribus, may also affect persons who did not use public psychiatric hospitals
previously but require intensive care in restricted settings as well as those who
did not access treatment after a hospital discharge.
Second, inpatient psychiatric care has become more privatized. In 2000,
private psychiatric and general hospitals accounted for 24 and 46 percent of all
inpatient treatment episodes, respectively, as compared with only 12 percent in
state psychiatric hospitals (Manderscheid et al. 2004). In addition, evidence
suggests that private hospitals may increasingly serve patients similar to those of
public hospitals (Olfson and Mechanic 1996; Mechanic, McAlpine, and Olfson
1998). However, little research evaluates the increasing role of private entities in
providing inpatient psychiatric care. To our knowledge, no research has ex-
plored whether an increased supply of private psychiatric beds could offset a
reduction in public beds, with no adverse effect on population mental health.
Third, the interaction between public inpatient and community mental
mental health resourcesmaybebetterpositionedthan otherregionsto absorb
a shock from a public inpatient reduction. Given the significance of the public
sector’s provision of mental health services, policy makers may want to know
reductions in public beds.
A change in psychiatric bed supply may relate to suicide rates because it may
influence whether an individual obtains services at the time of need. Bed
illness may self-medicate their symptoms when they experience limited access
Although public psychiatrichospitals have historically served as a safety
net provider for many severely mentally ill persons, it remains unclear
whether a reduction in public beds leads to higher suicide rates. The devel-
opment of psychopharmacology beginning in the 1950s enabled community
treatment of severe mental illness and reduced the need for long hospitaliza-
tion (Morrissey 1989; Mechanic and Rochefort 1990; Grob 2001). With con-
tinued advances of psychotropic medications and treatment, community
1388 HSR: Health Services Research 44:4 (August 2009)
options might achieve similar or improved patient outcomes as suggested by
Bachrach (1996) and McGrew et al. (1999). In addition to technological in-
novations, however, strong ideological consensus, regulations of welfare pro-
grams such as Medicaid rules, and financial considerations have reportedly
served as catalysts for rapid and ongoing public bed reductions (Cameron
1978; Gronfein 1985a; Mechanic and Rochefort 1990; Frank, Goldman, and
Hogan 2003; Grob and Goldman 2006). Current data suggest that this down-
sizing led to a shortage of psychiatric beds and increased waiting lists for
psychiatric hospital admissions (National Association of State Mental Health
Program Directors Research Institute [NRI] 2006a). Therefore, deinstitution-
alization may have proceeded faster than the reduction in the demand for
public beds. If this were the case, we would expect a negative relationship
between public bed capacity and suicide rates.
Among private psychiatric facilities, ownership status may affect hos-
pitals’ treatment behavior. For-profit hospitals are more inclined than public
and not-for-profit entities to maximize profits (Frank, Salkever, and Mullann
1990; Sloan 2000) and therefore may avoid indigent and high-cost patients
usually served by public psychiatric hospitals (Schlesinger et al. 1997; Me-
chanic1999).Moreover, due tothevoluntarynatureofcommunity treatment,
for-profit psychiatric facilities may not address needs of a subgroup of patients
with severe mental illness, especially those who do not respond to treatment
and lack affordable housing. Thus, ceteris paribus, increased for-profit beds
may not offset public bed reductions.
We expect not-for-profit psychiatric hospitals to derive their utility in
part from patient well-being and thus may improve overall access to mental
health services, which could subsequently reduce suicide rates. However, not-
for-profit hospitals serve those with less severe symptoms than do public psy-
chiatric hospitals. Despite the evidence that the case mix difference across
ownership types diminished in recent years particularly among general hos-
pitals (Olfson and Mechanic 1996; Mechanic, McAlpine, and Olfson 1998),
public hospitals appear most likely to treat indigent patients with severe psy-
chiatric disorders (Schlesinger and Dorwart 1984; Manderscheid et al. 1985;
Gray and McNerney 1986; Dorwart et al. 1991; Culhane and Hadley 1992;
Fisher et al. 1992; Frank and Salkever 1994; Olfson and Mechanic 1996;
et al. 2001). Therefore, an increase in not-for-profit beds may not have the
same suicide-reduction effect as would the public psychiatric hospitals.
The effect of bed reduction may depend on levels of public resources for
community-based treatment. Regions with more community mental health re-
Deinstitutionalization and Suicide1389
sources may better absorb negative effects of the reduced supply of public beds.
Thus, we postulate that the negative effect of public bed reduction on suicide
A central component of suicide prevention involves treatment of psy-
chiatric disorders via proper pharmacotherapy (Goldsmith et al. 2002). More-
over, placement ininstitutional psychiatricsettings servesthefunction, at least
in the short term, of restricting access to common means to attempt suicide
such as nonprescription drugs and firearms (Mann et al. 2005). Taken to-
gether, these circumstances imply that a change in mental health resources
may influence the incidence of suicide concurrently.
Psychiatric bed supply and community mental health resources varied sub-
stantially across states and times (Morrissey 1989; Mechanic and Rochefort
1990; Grob and Goldman 2006). This variation resulted from traditions and
circumstances unique to each state. Some of these factors included the size of
patient populations, the political clout of public hospitals and the professional
psychiatric community, the strength of deinstitutionalization ideologies, and
Goldman 2006). This state variability persists even in the contemporary men-
tal health care setting (NRI 2006a).
We use the states’ variation in the timing and size of changes in psy-
suicide rates. Suicide rates also exhibited substantial interstate variation (see
supporting information Figure S1). We control for potential confounders re-
ported in the literature as well as unobservable characteristics unique to each
state and time period.
We estimated the following equation to examine the relationship between
public bed supply (PUBLIC) and suicide rates (SUICIDE):
SUICIDEst¼a1PUBLICstþ a2NFPstþ a3FPstþ a4CMHEst
ZXstþ Ssþ Ytþ est
wheres and t indexstateandyear, respectively. Wecontrolledforthe number
of not-for-profit (NFP) and for-profit (FP) beds and community mental health
1390 HSR: Health Services Research 44:4 (August 2009)
expenditures (CMHE) because these factors have accompanied public bed
reductions and may also affect suicide rates.
X refers to a vector of each state’s sociodemographic characteristics and
economic conditions as well as changes in other mental health policies or
resources. We specified in a set of sociodemographics age structure, sex ratio,
racial composition, and urbanization variables. Economic conditions may
affect both the supply of public beds and suicide rates. Thus, our covariates
included the poverty rate, unemployment rate, and per-capita income. We
also controlled for changes in mental health care financing and welfare state
such as state mental health parity laws, the proportion of residents on Med-
icaid, and the proportion of AFDC/TANF residents. The number of psychi-
atrists was included as a proxy for changes in state mental health workforce. It
may also reflect overall population mental health levels that may influence
both public bed supply and suicide rates. We also controlled for unobserved
state differences that do not change over time (S) and secular changes in
suicide rates common to all states (Y ).
we may find that greater not-for-profit beds reduce suicide rates, holding other
things constant. This finding, however, does not imply by axiom that not-for-
profit bed supply could substitute for public bed reduction. It only suggests the
suicide rates. A more appropriate test of substitutability is to examine whether
an increase in the ratio of not-for-profit beds (or for-profit beds) to public beds
affects suicide rates, holding fixed the sum of not-for-profit and public beds (or
the sum of for-profit and public beds) and other confounders.
Our empirical model takes the following form:
SUICIDEst¼ aBED CMHEstþ ZXstþ Ssþ Ytþ est
where BED_CMHE refers to a vector of main independent variables. We
included in BED_CMHE the ratio of not-for-profit (or for-profit) beds to public
beds, the sumofnot-for-profit(orfor-profit) andpublicbeds, for-profit(or not-
for-profit) beds, and community mental health expenditures. The ratio vari-
able measures whether the substitution between not-for-profit (or for-profit)
and public beds affects suicide rates.
To address our third aim of whether the effect of public bed reduction
on suicide rates varies with the availability of community mental health
Deinstitutionalization and Suicide 1391
resources, we estimated the following equation including an interaction term
of public beds and community mental health expenditures (PUBLIC ?
SUICIDEst¼a1PUBLICstþ a2NFPstþ a3FPstþ a4CMHEst
lPUBLIC ? CMHEstþ ZXstþ Ssþ Ytþ est
In our equations, the magnitude of the error term may be inversely correlated
with population size. Unweighted estimates could produce heteroskedasticity
and render findings difficult to interpret. We rejected the null hypothesis of
data: (1) panel heteroskedasticity, that is, each state may have its own error
variance; (2) contemporaneous correlation, that is, the error variance for one
state may be correlated with the errors for other states; and (3) serial corre-
for that state. We applied the method of panel corrected standard errors
(PCSE) that has excellent statistical properties for time-series-cross-section
(TSCS) data (Beck and Katz 1995, 1996). Although this technique has not yet
been widely employed by health services researchers, it serves as a modern
econometric technique for TSCS data and addresses important issues related
to correct inferences in the current analysis.
of serial correlation.
We retrieved state-leveldata from varioussourcesfortheyears 1982–1998 for
50 U.S. states and the District of Columbia. Table 1 provides definitions and
summary statistics for the variables used in this study.
We derived state-level suicide rates from the National Center for Health
Statistics Compressed Mortality File (NCHS 1982–1998). The mortality file
1392 HSR: Health Services Research 44:4 (August 2009)
provides information from death certificates on cause of death, including
death from suicide or self-inflicted injuries (ICD-9 codes E950-E959). Suicide
rates are calculated as the number of suicides per 100,000 population for
persons aged 15–64.
Table1: Variable Definitions and Summary Statistics
Number of death from suicides per 100,000 persons 15.824.16
Number of psychiatric beds per 100,000 persons34.0
State mental health agencies’ per-capita expenditures
on community mental health programs (in 1998
dollars using the consumer price index )
Per-capita income State per-capita income
Unemployment State unemployment-to-population ratio
PovertyProportion of the poor
Parity lawEquals 1 for state with any mental health parity laws;
Medicaid Proportion of Medicaid recipients
AFDC/TANF Proportion of AFDC/TANF recipients
Psychiatrist Number of psychiatrists per 100,000 persons
Ratio of not-for-profit (or for-profit or community mental
health expenditures) to public psychiatric hospital beds
Proportion of residents within each category of age0.078
Ratio of male to female residents
Proportion of black residents
Proportion of non-black non-white residents
Proportion of residents in metropolitan areas0.66
CMHE, community mental health expenditures; FP, for-profit hospital psychiatric beds; NFP,
not-for-profit hospital psychiatric beds; PUBLIC, public psychiatric hospital beds.
Deinstitutionalization and Suicide 1393
We retrieved the number of psychiatric beds from American Hospital Asso-
ciation’s Annual Survey of Hospitals (AHA 1982–1998). Psychiatric care
in general hospitals. We collapsed observations at the state level and calcu-
lated the per-capita number of psychiatric beds per 100,000 persons, sepa-
rately by public, not-for-profit, and for-profit status.
Community Mental Health Expenditures
We used state mental health agencies’ (SMHA) per-capita expenditures on
community-based mental health programs from the NRI. NRI has intermit-
tently conducted the SMHA revenues and expenditures study in 1981, 1985,
1987, 1990, 1993, 1997, and 2001. We linearly interpolated expenditure data
mental health including medications and drug and alcohol programs (Lutter-
man and Hogan 2001).
Sociodemographic controls include age categories including the proportions
of the state residents 20–24, 25–34, 35–44, 45–54, and 55–64 years old, a ratio
of male to female residents, the proportions of black and nonblack–nonwhite
residents, and the proportion of metropolitan residents in a state. Economic
factors include poverty rates, state unemployment rates, and state per-capita
income. We retrieved data from the U.S. Census Bureau, the Bureau of Eco-
nomic Analysis, and the Bureau of Labor Statistics.
We specified several variables reflecting changes in mental health fi-
nancing and workforce as well as welfare state, including state mental health
parity laws, the proportion of Medicaid recipients, the proportion of welfare
(AFDC/TANF) recipients, and the per-capita number of psychiatrists per
100,000 persons. The parity law variable takes the value of 1 for the years that
each state had any mental health parity laws and 0 otherwise. We accessed
parity law data from the National Conference of State Legislatures (2008).
Information on Medicaid and welfare recipients came from the U.S. Census
Bureau. The per-capita number of psychiatrists per 100,000 persons was
retrieved from the American Medical Association’s Physician Characteristics
and Distribution in the United States (1982–1999).
1394 HSR: Health Services Research 44:4 (August 2009)
Supply of Public Beds and Suicide Rates
The supply of public beds was negatively associated with suicide rates (see
Table 2). A one public bed reduction per 100,000 persons was associated with
an increase of 0.025 suicides per 100,000 persons annually, holding constant
the supply of not-for-profit and for-profit beds and community mental health
funding. To gauge the magnitude of this effect, we calculated the predicted
persons corresponds to approximately 1,818 fewer public beds nationwide.
Using our coefficient in Table 2 (i.e., ?0.025), this crude calculation shows
that a one public bed decrease per 100,000 persons would result in about 45
additional suicides per year (?0.025 ? 1,818), or about 1,988 years of poten-
tial life lost before the age of 80 (CDC 2008).
No association was found between suicide rates and the supply of not-
for-profit and for-profit beds. We observed a positive significant relationship
result, however, was not robust to different specifications and the removal of
outlying states(see the Robustness section). The existence of parity lawsand the
proportions of metropolitan and nonblack–nonwhite residents were nega-
tively correlated with suicide rates. Unemployment rates and the proportion
of residents aged 55–64 were positively correlated with suicide rates.
Substitutability between Public and Private Psychiatric Beds
Table 3 presents results from the models that examine whether an increase in
not-for-profit beds (see Model 1) and for-profit beds (see Model 2) can sub-
stitute for public bed reduction. There was a statistically nonsignificant rela-
tionship between suicide rates and the ratio variables. This finding suggests
that the substitution of public with not-for-profit or for-profit beds did not
increase suicide rates. However, this result was not robust to the removal of
outliers (see Robustness section).
Interaction Effect of Public Beds and Community Mental Health Spending
We find that levels of community mental health resources modify the effect of
a decrease in public beds (see Table 4). The coefficients of public beds and the
the relationship between public bed supply and suicide rates appears to vary
by the level of the per-capita community mental health expenditures.
Deinstitutionalization and Suicide1395
Relationship between Public Psychiatric Bed Supply and Suicide
Panel corrected standard errors are in parentheses.
CMHE, community mental health expenditures; FP, for-profit hospital psychiatric beds; NFP,
not-for-profit hospital psychiatric beds; PUBLIC, public psychiatric hospital beds.
1396 HSR: Health Services Research 44:4 (August 2009)
To determine the conditions under which a reduction in public beds has
a statistically significant negative effect on suicide rates, we calculated corre-
sponding 95 percent confidence intervals. Once the per-capita community
spending was greater than roughly US$107 in 2008 dollars, a decrease in
public beds no longer had a significant negative effect on suicide rates. We
applied this result to recent data on state-level community mental health ex-
penditures in 2004 (NRI 2006b). Estimates indicate that an additional reduc-
tion in public beds would increase suicide rates for all states except
Pennsylvania and Vermont. In these two states, per-capita community men-
tal health spending is US$120 and US$109 in 2008, respectively.
We assessed the robustness of our results in several ways (see supporting
information in Table S1). We began by including state-specific time trends to
Ratios and Suicide Rates
Relationship between AdditionalIncreaseinRelativeHospitalBed
Main VariablesModel 1 Model 2
Panelcorrectedstandard errors areinparentheses. Onlythe coefficientsonthe mainindependent
variables are reported. Suppressed covariates include the same sociodemographics, economic
variables, other mental health policy and resources, and state and year fixed effects.
CMHE, community mental health expenditures; FP, for-profit hospital psychiatric beds; NFP,
not-for-profit hospital psychiatric beds; NFP/PUBLIC, ratio of not-for-profit to public beds; FP/
PUBLIC, ratio of for-profit to public beds; NFP1PUBLIC, sum of not-for-profit and public beds;
FP1PUBLIC, sum of for-profit and public beds.
Deinstitutionalization and Suicide1397
control for state trends in suicide rates. The coefficient on public beds appears
attenuatedbutconsistentwithourmainfindings (e.g.,^ a1¼ ?0:0173;standard
error50.0065; po.01). However, both ratio variables became positive
although still insignificant.
Because our main results use WLS, which places greater weights on
states with larger population, all regression models were re-estimated after
removing the five most populous states. We also examined the sensitivity of
the results to removal of five states with the highest suicide rates. Results were
similar to our initial findings. However, the finding on the for-profit ratio
variable was not consistent.
We then re-estimated all regression models with OLS and adjusted
standard errors for arbitrary forms of error correlations but left unadjusted
between-panel error correlation. Next, we fitted the models using feasible
generalized least squares, allowing for heteroskedastic and correlated error
structures. Results were quite similar.
Community Mental Health Spending on Suicide Rates
Interaction Effect of Public Psychiatric Hospital Beds and
PUBLIC ? CMHE
p-value of joint significant test of PUBLIC and PUBLIC ? CMHE
Panelcorrected standarderrorsare inparentheses.Onlythecoefficients onthemain independent
variables are reported. Suppressed covariates include the same sociodemographic and economic
variables, other mental health policy and resources, and state and year fixed effects. Although the
interaction term is not significant at the .05 level, it must be in the equation because we are
interested in the interaction effect of PUBLIC and CMHE (e.g., Wooldridge 2003). PUBLIC and
PUBLIC ? CMHE are jointly significant.
CMHE, community mental health expenditures; FP, for-profit hospital psychiatric beds;
NFP, not-for-profit hospital psychiatric beds; PUBLIC, public psychiatric hospital beds;
PUBLIC ? CMHE, interaction between PUBLIC and CMHE.
1398HSR: Health Services Research 44:4 (August 2009)
We tested whether outlier states influenced our results by checking
whether there were states for which trends in public, not-for-profit, and for-
the not-for-profit ratio variable became positive and significant. We also
checked for states with large changes in public, not-for-profit, and for-profit
beds and community mental health expenditures over the study period.
Results remained robust.
The transformation of the mental health system in the United States continues
at an unabated pace. The philosophy of community treatment of severe men-
tal illness, which has guided national mental health policies for several de-
cades, is now evolving toward a recovery-oriented, consumer-operated, and
culturally competent system. California’s recent Mental Health Service Act of
provides a cautionary note regarding this transformation as we find that
downsizing of public inpatient mental health services may lead to increased
suicide rates. If other conditions do not change, retaining public psychiatric
hospital beds may have a suicide prevention effect.
To help gauge the cost-effectiveness of maintaining public beds, we es-
timated the cost per life-year saved due to retaining public beds. Using data on
national expenditures for inpatient treatment in state psychiatric hospitals
(US$7,447 million in 2002 dollars; see NRI 2006b) and the number of public
psychiatric hospital beds in 2002 (57,263 beds; see Manderscheid et al. 2004),
we estimate the cost of maintaining a public bed at US$130,049 per year.
One public bed per 100,000 persons, therefore, costs US$236,428,082
(US$130,049 ? 1,818 beds). Under the assumption that this additional reten-
tion of public beds prevents 1,988 years of potential life lost due to suicide, we
estimate a cost to society of about US$118,928 per year of life saved. This
amount appears substantially lower than suggested thresholds used to deter-
mine cost-effectiveness (e.g., US$200,000 per life-year; see Ubel et al. 2003).
Our findings show that although the substitution of private beds for
public beds did not affect suicide rates, it appeared to increase suicide rates
when outlying states were removed. In addition, ceteris paribus, greater pri-
vate beds did not reduce suicide rates. The substitution issue warrants further
investigation. Nevertheless, our discovered effect of increasing community
Deinstitutionalization and Suicide1399
mental health funding may be promising because this spending may reduce
the sequelae of public psychiatric bed reductions. We note that, at the current
adverse population mental health outcomes. Taken together, our results sug-
gest that growth in community treatment options has not fully compensated
for the reductions in the ‘‘safety net’’ capability of public beds.
Thereadershould interpret our results in light of several limitations. We
report a positive, but nonrobust, relationship between community mental
healthfunding and suicide.Advocateshave suggestedthat community mental
health resources inadequately serve a growing body of mentally ill persons in
the community (Lamb, Weinberger, and Gross 2004). Increased spending,
therefore, may serve as a marker for increased mental illness in that state but
may not reach adequate levels to prevent suicide. We, however, found that
increasing community funding reduces suicide rates only above a particular
increased suicide rates, but the growth of funding for community mental
health remained below the level of need.
We used suicide rates to gauge population mental health. Suicide is a
relatively rare event and may be subject to considerable volatility even at the
state level. Nevertheless, the suicide rate is a useful outcome for this particular
study because of the frequently reported correlation between severe psychi-
atric episodes and suicide. Persons with severe mental illness, particularly
schizophrenia, and substance abuse comorbidity are at an elevated risk of
premature deaths, primarily due to unnatural causes such as suicides and
Hiroeh et al. 2001; Colton and Manderscheid 2006; Miller, Paschall, and
Svendsen 2006; Saha, Chant, and McGrath 2007). Since this population
comprises the largest group of patients served by public psychiatric hospitals
(Milazzo-Sayre et al. 2001), death from suicide may serve as a useful measure
of mental health for a study that examines deinstitutionalization.
Another limitation includes measurement error in that suicide may be
inappropriately classified as an accident or undetermined. Coroners appear
morelikely tomisclassifysuicideswhen,forexample,they havefewerperson-
hours to investigate the case (Douglas 1967; Rockett, Samora, and Coben
2006). This misclassification is largely unidirectional since the risk of ruling
a nonsuicide as a suicide appears small (Moyer, Boyle, and Pollock 1989;
O’Carroll 1989). It remains possible, therefore, that states with relatively many
health resources may more accurately measure suicides. This circumstance
1400 HSR: Health Services Research 44:4 (August 2009)
measurement error of suicide may attenuate the true magnitude of the effect.
Other features of community mental health programs that we did not
investigate (e.g., the effective organization and utilization of resources and ser-
vices) may have important implications. For example, inpatient services in
community mental health centers or comprehensive support programs may
effects on suicide. We view this as an important agenda for future research.
This study focused on the contemporaneous effect of a change in mental
health resources on suicide rates. However, it remains possible that mental
health resources could influence suicides in the following year. We explored
this possibility with 1-year lagged values of the main independent variables.
The discovered coefficients on the lagged explanatory variables bolster our
main findings as they provide the same implications as those from the con-
temporaneous variables, although the size of the associations was smaller.
Future studies with a priori hypotheses of a lag structure, particularly with an
emphasis on causal mechanisms, may help better understand the sequence of
the effect of a change in mental health resources on population mental health.
Joint Acknowledgment/Disclosure Statement: Jangho Yoon is supported by
the National Institute of Mental Health through the Ruth Kirschstein (T-32)
National Research Service Award (MH 070335-01A1). Tim A. Bruckner is
supported by the Agency for Healthcare Research and Quality through the
would like to thank two anonymous reviewers for their valuable comments
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Additional supporting information may be found in the online version of this
Appendix SA1: Author Matrix.
Figure S1. Year-To-Year Percent Changes in the Number of Public
Psychiatric Hospital Beds and Suicide Rates for Selected States, 1982–1998.
Table S1. Robustness Test Results for Tables 2–4.
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tionality of any supporting materials supplied by the authors. Any queries
(other than missing material) should be directed to the corresponding author
for the article.
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