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Neil J Preston a Mental Health Directorate, Fremantle Hospital and
Health Service, PO Box 480 Fremantle, WA 6160, Australia, b University Department of Psychiatry at Fremantle Hospital,
University of Western Australia, 16 The Terrace, Fremantle, c Health
Information Centre, Health Department of Western Australia, 189 Royal
Street, East Perth, WA 6004 Correspondence to: N J Preston
neil.preston{at}health.wa.gov.au
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Abstract |
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Objective:
To examine whether community treatment
orders for psychiatric patients reduce subsequent use of health
services in comparison with control patients not placed on an order.
Design:
Epidemiological study with a before and
after, two stage design of matching and multivariate analysis,
controlling for sociodemographic variables, clinical features, and
psychiatric history.
Setting:
All community based and inpatient
psychiatric services in Western Australia, covering a population of 1.7 million people.
Participants:
228 subjects placed on a community
treatment order, matched with an equal number of controls to give a
total of 456 patients.
Main outcome measures:
Inpatient admissions, bed
days, and outpatient contacts one year after subjects were placed on a
community treatment order or the index date of matched controls.
Results:
Both subjects and their matched
controls had reduced inpatient admissions and bed days in hospital.
Subjects had significantly more outpatient contacts. Multivariate
analysis indicated that being placed on a community treatment order was associated with increased outpatient contacts in the subsequent year compared with the control group. Otherwise, orders did not affect
subsequent use of health services. Other factors associated with
increased use of health services were age and inpatient admissions, bed
days, and outpatient contacts before the order or index date. No
covariates were shown to be associated with changes in within pair
differences in inpatient admissions or bed days.
Conclusions:
The introduction of compulsory treatment
in the community does not lead to reduced use of health services.
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What is already known on this topic
Studies have often lacked epidemiological sampling frames and control for possible confounding factors What this study adds
Placement of an order did not predict subsequent use of services Community treatment orders may not be an effective alternative to assertive community treatment programmes |
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Introduction |
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Enforcing psychiatric treatment in the community has become a feature in Australia, New Zealand, the United Kingdom, and the United States.1-3 In the United States more than half the states have some form of compulsory community treatment,2 and in Australasia similar provisions exist in Victoria, Western Australia, New South Wales, and New Zealand.3-5 Initiatives in the United Kingdom have included extended leave for patients leaving hospital and the supervision register. 6 7 The recent white paper Reforming the Mental Health Act contains provisions for compulsory treatment in the community.8 Studies indicating limited but improved outcomes in terms of readmission to hospital, length of stay, and adherence to treatment have often not controlled for selection bias, variations in treatment, and differing criteria for compulsory treatment in the community.3
The new Mental Health Act of Western Australia, implemented in 1997, includes the provision of involuntary treatment in the community
through the introduction of a community treatment order. The aim of our
study was to compare the rate of inpatient admissions, bed days, and
outpatient contacts of patients one year before and one year after
placement on a community treatment order.
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Methods |
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We compared data for subjects placed on a community treatment order with those for a matched control group and then entered them into a multiple regression equation to examine variables predicting the use of health services after placement on an order. The purpose was to identify similar patients not placed on an order as matched controls and examine whether keeping patient characteristics constant could contribute to similar outcomes for inpatient admissions, bed days, and outpatient contacts in the year before the index date.
The Mental Health Information System was linked to a database administered by the Mental Health Review Board in terms of involuntary admissions under the Mental Health Act. This enabled us to include all patients who had been made subject to a community treatment order for the entire state of Western Australia.
Selection of subjects
We selected patients placed on orders
between 13 November 1997 (the date of implementation of the Mental
Health Act 1996) and 31 November 1998. Of the 313 patients who were
preliminarily selected, seven died during the one year observation
period after their index dates and 32 had not had a full year's
contact with the mental health registry before their index dates,
leaving 274 subjects.
Selection of matched controls
We selected 266 controls
matched for sex; Aboriginal ethnicity; age; diagnosis at index date;
length of stay; number of hospital admissions; occasions of service
use; and involuntary status in the year before the index date. Suitable matched controls could not be identified for 38 subjects, leaving 228 patients in each group.
Analysis
We used the paired samples t test
to test for differences between subjects and controls. We performed
each analysis on the logarithmically transformed dependent variables. To further adjust for possible differences between the two groups, we
generated standard multiple regression models to examine the contribution of patient characteristics and use of services before the
index date to subsequent inpatient admissions, inpatient bed days, and
outpatient contacts. We examined predictor variables for each
regression model by entering service use, including inpatient admissions, bed days, and outpatient contacts, before the index date
and data on patient characteristics such as age, sex, Aboriginal ethnicity, and whether subject or control. We also used a multiple linear regression model to further assess within pair differences in
use of health services before and after the index date, with adjustment
for possible confounders.9
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Results |
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Comparisons between subjects and controls revealed no
significant differences in admissions before the index date (mean
paired percentage difference
1.0, 95% confidence interval
2.3 to
0.3). Inpatient bed days (3.9, 1.4 to 6.4) and outpatient contacts
(32.7, 26.6 to 38.8) were significantly higher for subjects than for controls.
Use of health services before and after the index
date
Inpatient admissions and bed days decreased for both
subjects and controls. Outpatient contacts increased for subjects only
(table 1).
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Significant predictors of bed days within the model included
age, admissions, and inpatient bed days before the index date (table
2). Group membership (subject versus control) did not significantly
predict subsequent inpatient bed days.
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Admissions and outpatient contacts before the index date
were significant predictors of subsequent admissions (table 2).
Aboriginal people showed a trend to be admitted more frequently than
non-Aboriginal people. Community treatment order status did not
significantly predict subsequent inpatient admissions.
Predicting outpatient contacts after the index
date
Outpatient contacts before the index date and being placed
on a community treatment order were associated with significantly
higher subsequent outpatient contacts (table 2). Residential location
showed a tendency for more outpatient contacts to occur in metropolitan
areas than in rural or remote areas of Western Australia.
Within pair differences
We assessed the effects of
placement on a community treatment order on inpatient admissions and
bed days over the year before and after the index date by using
multiple regression models with within pair differences as dependent
variables. No covariates were shown to be associated with the within
pair differences in inpatient admissions and bed days, and no variation in results was seen after adjustment for covariates (age, Aboriginal ethnicity, diagnosis type, marital status, occupation, region).
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Discussion |
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Limitations of the study
Although the matching process allowed selection of controls with
similar characteristics to the patients placed on community treatment
orders, significant differences in prior outpatient contacts and
inpatient bed days existed. This meant that these variables had to be
included in the regression models to control for their effects.
Controlling for variables, however, may not be sufficient, and
additional confounders may be present. For example, it was not possible
to control for variables such as social disability or dangerousness
with the available database. Patients placed on an order may have
greater degrees of dangerousness or social disability. These factors,
in turn, may effect subsequent use of health services.
Both groups showed a reduction in inpatient bed days, suggesting a regression to the mean in that patients with high rates of use will have lower rates of subsequent use. The finding that this effect was seen equally in both groups may indicate that the groups were similar. The regression results for within pair differences in inpatient admissions or bed days, and their covariates, also showed the similarity of the two groups. In addition, the design permitted a before and after comparison of subjects and controls.
Are community treatment orders effective?
This study provides mixed results. Although orders reduce
admission rates and bed days, the effect is no greater than that seen
in a group of patients who are not on such an order, after adjustment
for possible confounders. The study therefore raises questions about
the effectiveness of such an invasive procedure as enforcing treatment
in the community. If efficacy is in part defined by reduced hospital
admissions and length of stay, our results suggest that the policy is
no more effective than not enforcing community treatment. Our results
are consistent with previous studies of community treatment orders,
which showed no significant improvements in outcome compared with
matched controls,
10 11
but not with findings from England
and Massachusetts, where patients on "extended leave" or
involuntary outpatient treatment spent less time in hospital than did
matched controls.
6 11
Possible explanations might be
differing selection criteria and the fact that only age, sex, and
diagnosis were controlled for in the design of both these studies. On
the other hand, the British study included an assessment of
dangerousness that was not recorded in the Western Australia Mental
Health Information System.
This study examines only whether community treatment orders reduce immediate use of health services, as this has been the main reason for their introduction and hence the focus of previous research into their effectiveness.6 Such orders may reduce use of health services in the longer term or produce benefits in other areas, such as psychosocial functioning.
Some researchers have called for randomised assignment of patients to community treatment orders as a way of measuring the efficacy within a quasi-experimental paradigm,12 but this can be logistically difficult if the order is tied to statutory legislation. An alternative would be to compare patients from jurisdictions with and without community treatment orders and matched on sociodemographic, clinical, and health service characteristics.
This study shows that legislative solutions such as community treatment orders may not always offer a solution to the need to provide appropriate services for psychiatric patients within limited resources. It is important to examine what role such orders have in providing effective mental health treatment and whether therapeutic gains could be better delivered by enhancing the quality and assertiveness of community treatment for high risk patients.
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Acknowledgments |
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We thank Tom Pinder and Alan Joyce at the Mental Health Information Centre, Health Department of Western Australia, and Neville Barber and Sue Lewis at the Mental Health Review Board for their assistance in the merging and extraction of Mental Health Information System data and community treatment order data.
Contributors: See bmj.com
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Footnotes |
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Funding: Medical Research Foundation of Fremantle Hospital, Western Australia.
Competing interests: None declared.
The full version of this paper
appears on bmj.com
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References |
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(Accepted 3 December 2001)