Centre for the Economics of Mental Health, Institute of Psychiatry, London
MRC Clinical Trials Unit, London
Department of General Psychiatry, St George's Hospital Medical School, London
School of Psychiatry and Behavioural Sciences, Manchester Royal Infirmary, Manchester
Psychology Department, Paterson Centre, London
Correspondence: Sarah Byford, Centre for the Economics of Mental Health, Institute of Psychiatry, De Crespigny Park, London SE5 8AF, UK. Tel: 020 7848 0043; Fax: 020 7701 7600; e-mail: s.byford{at}iop.kcl.ac.uk
Declaration of interest Funded by the UK Department of Health and NHS Research and Development programme.
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ABSTRACT |
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Aims To investigate factors that influence the cost of caring for patients with severe psychotic illness.
Method Univariate and multivariate analyses were used to examine associations between baseline characteristics and subsequent 2-year total direct costs in 667 patients from the UK 700 case management trial.
Results Significantly more money was spent on younger patients, those with longer duration of illness, those who had spent less time living independently and those who had spent longer in hospital for psychiatric reasons.
Conclusions Total costs of caring for patients with severe psychotic illness appear to be influenced to a large extent by age, duration of illness and past levels of dependence on statutory services. The strength of these relationships is greater than the impact of illness severity.
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INTRODUCTION |
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METHODS |
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Baseline measures
Baseline measures taken at the point of entry into the UK700 trial
included:
From the baseline variables available, a limited set of possible predictors of cost were selected (listed in Table 1) on the basis of current literature (Knapp et al, 1990, 1995; Chisholm et al, 1997; McCrone et al, 1998) and discussions with clinical experts in the four centres. Only total 2-year costs, the dependent variable, and intervention received over the period of the trial were post-baseline. The intervention group was considered in order to adjust for the impact that type of case management may have on total cost post-baseline.
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Total 2-year costs
Data on the use of all hospital and community services were collected
prospectively for each patient from entry to the trial for a period of 2
years, providing a total 2-year direct cost per patient
(UK700 Group, 2000). Resources
used included hospital and primary care services (in-patient, day patient,
out-patient, emergency and out-of-hours clinics, accident and emergency,
community mental health team, general practitioner, practice nurse and
medication), social and non-statutory services (social work, staff
accommodation, day and drop-in centres, sheltered work-shops, meals, home care
and transport) and prison and police custody. All unit costs were calculated
for the financial year 1997/98 and future costs were discounted at an annual
rate of 6%.
Statistical methods
A statistical analysis plan detailing the approach to be taken for
investigating the relationship between baseline measures and subsequent 2-year
cost was drawn up prior to inspecting the data. Univariate associations
between each of the specified predictors and subsequent total costs were
investigated. For categorical variables analysis of variance was used, and for
continuous variables simple linear regressions were fitted. Results for
continuous variables are presented in two groups split at the median value,
but analyses were actually carried out on the continuous data.
Multiple regression was used to reduce the variable set to those independently associated with costs. For these analyses, categorical variables were included in the usual way, with sets of indicators describing the groups as defined in Table 1. Variables were selected using an approach recommended by Collett (1994) for survival data. This involved, in the first instance, fitting a multiple regression model which included all variables that had important univariate associations with costs and discarding from this model all variables that ceased to be important. Second, each variable that did not have a univariate association with costs was added, one at a time, to the multiple regression model and retained if it added significantly to the model or otherwise discarded. The model finally arrived at was then checked to ensure that none of the terms currently excluded would add significantly to it. In carrying out this procedure a significance level of around 10% was used, but this was not rigidly applied (Knapp et al, 1990; Collett, 1994). Non-linearity of continuous covariates in the final model was examined by including higher-order terms. Pre-specified inter-actions were also considered.
Standard ordinary least-squares regression methods on untransformed costs were used for all analyses despite the skewed distribution of cost data. The advantage of this approach, as opposed to logarithmic transformation or conventional non-parametric tests, is the ability to make inferences about the arithmetic mean (Barber & Thompson, 1998). Results from the main analyses were, however, subject to two checks. First, they were compared with the results from non-parametric bootstrap regression to assess the robustness of confidence intervals and P values to non-normality in the cost distribution (Efron & Tibshirani, 1993). Second, they were compared with the results obtained from a generalised linear model where a non-normal distribution (gamma distribution) was assumed for costs (Blough et al, 1999).
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RESULTS |
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Univariate results
Table 1 details all
univariate analyses. In terms of demographic and socio-economic
characteristics, higher costs were significantly associated with being male,
young, unemployed, single, living alone, having little or no independent
living and having spent time in jail. In terms of diagnostic and other
clinical variables, higher costs were significantly associated with suicide
attempts over the previous 2 years, abnormal movements (AIMS), higher CPRS
scores, a great number of negative symptoms (SANS), a lower level of perceived
quality of life (LQOL), greater social disability (DAS), a greater number of
days in hospital for psychiatric reasons over the previous 2 years and a
greater number of unmet needs (CAN).
No significant univariate associations were found between costs and type of case management received, centre, ethnicity, social class, years of education, diagnosis, duration of illness and level of depression (MADRS).
Multiple regression
The final multiple regression model obtained before considering
interactions and non-linear effects is shown in
Table 2. The variables most
strongly associated with costs were age, months in independent living over the
previous 2 years, duration of illness and days spent in hospital for
psychiatric reasons over previous 2 years. On average, costs were lower for
older subjects, those spending more time living independently, those having
shorter periods of illness and those spending fewer days in hospital. Although
duration of illness was not found to be univariately associated with costs, it
became a significant factor in regression models that included age as a
covariate. This is because duration of illness in some way also describes age,
since those having longer durations of illness are generally older. This is
clear from the high correlation between age and duration of illness
(correlation coefficient=0.7). Controlling for the age effect, by including
age as a covariate, allows the effect of duration of illness alone to be
demonstrated. This effect is in the opposite direction to that of age, with
longer periods of illness being associated with increased costs.
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Marital status, level of social disability and number of unmet needs were also associated with total cost in the multiple regression model, but less strongly. The directions of these relationships were such that lower costs were associated with living as married, having lower social disability and fewer unmet needs, as would be expected.
Results from bootstrap regression analyses and those based on generalised linear models with gamma-distributed errors were not substantially different from the ordinary least-squares regression results reported in the tables.
Interactions and non-linear terms
Investigations of pre-specified interaction terms and non-linear
relationships among variables in the final model indicated a non-linear
relationship for age and two significant interaction terms between independent
living and social disability (DAS score) (P=0.02) and independent
living and hospitalisation for psychiatric reasons (P<0.001). The
multiple regression model extended to include these terms is shown in
Table 3.
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The non-linear relationship with age indicated that at low ages, costs initially decreased then levelled off as age increased. To allow for this effect, age was included in the model as a categorical variable grouped by quartiles. The significant interactions demonstrated that the relationships between cost and both DAS score and hospitalisation differed by independent living group. A greater number of days in hospital for psychiatric reasons over the previous 2 years was associated with increased total cost for all independent living groups, however, the effect was increasingly strong for those who had spent longer in independent living. A strong positive association between increasing social disability and cost was evident for those who had had no independent living. For those who had spent some months in independent living, however, no significant relationship between cost and social disability was evident.
Model adequacy
The adequacy of the multiple regression model for predicting cost can be
assessed using the multiple correlation coefficient R2.
For the final model including inter-action terms
(Table 3), 28% of the variance
of total costs is accounted for by the explanatory variables in the model. An
alternative representation to illustrate model adequacy for cost data is given
in Fig. 2. This shows a plot of
the percentage of the most expensive patients predicted by the model against
the percentage of the total cost incurred by those patients. A bad predictive
model is illustrated by a line close to the line of identity (y=x) and a more
appropriate model is given by curves which become increasingly more convex and
closer to the upper line shown in the figure.
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DISCUSSION |
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Demographic and socio-economic characteristics
Of the demographic characteristics included in the analysis, only age was
found to be significantly related to total costs in multiple regression. The
increased cost in younger age groups, also found in previous studies (Knapp
et al, 1990,
1995;
Chisholm et al, 1997;
McCrone et al, 1998),
is likely to be due to a number of factors. On the supply side, there is some
evidence to suggest that health professionals, both primary and secondary, may
concentrate efforts on the young and acute
(Hillerbrand & Shaw, 1989;
Verhaak, 1993;
Harrison et al,
1997), perhaps believing there to be greater scope for change or
reflecting a perception of greater severity. In addition, geographical
mobility, a variable found to be significantly and positively related to
longer periods in hospital (Lamont et
al, 2000), is likely to be more prevalent in the younger age
groups. On the demand side, young people may have parents who advocate for
them and a greater faith in the ability of health professionals to
cure them, because of more limited experience of the health care
system. With little research carried out in the UK into the demand for mental
health care or the preferences of patients and their families, however, this
hypothesis is tentative.
Of the socio-economic characteristics included, marital status and months in independent living over the previous 2 years were found to be independent predictors of total 2-year costs of care. The former relationship, although weak, is supported by Harrison et al (1997), who found an association between being married and slower access to psychiatric care, and McCrone et al (1998), who found living alone to be predictive of higher costs. This finding reflects the fact that patients who live alone have increased dependency on statutory service providers as compared with patients living as married whose partners are likely to play a significant supportive and caring role (Knapp et al, 1995). The higher costs associated with those who spent longer in dependent living accommodation prior to trial entry suggests that such service users remained a more dependent group after trial entry. Thus, past levels of dependency on supported accommodation appear to be predictive of future costs.
Diagnosis, severity of illness and need
Diagnosis was not found to be an independent predictor of total 2-year
costs, in common with similar research findings
(Knapp et al, 1995). Although the majority of measures of severity of illness were found to have a
statistically significant association with costs in univariate analyses, only
duration of illness, days in hospital for psychiatric reasons and level of
social disability were found to be independent predictors in multiple
regression models. The impact of illness severity on cost is, therefore,
weaker than would have been predicted and is perhaps being masked in multiple
regression by variables that are having a stronger effect.
Duration of illness was positively associated with total 2-year costs of care. At the onset of an illness, it seems reasonable to assume that suppliers of health care will be inclined to begin treatment with less invasive and cheaper alternatives. As the illness progresses, however, and these treatments are found to be ineffective or to become less effective over time, more expensive alternatives may be substituted or added. In addition, new services may be added at a greater rate than they are discontinued. On the demand side, social support, found to be negatively related to service utilisation (Faccincani et al, 1990), may deteriorate as the duration of illness increases, resulting in a greater need for statutory input. In particular, informal carers, such as parents or partners, may initially be prepared to provide a great deal of care and support, but as time progresses they may be unable or unwilling to continue, as a result of emotional, physical and financial pressures, documented by McGilloway et al (1997). The relationships between total costs and age and duration of illness appear to go in counter-intuitive directions. In fact, these findings may reflect poorer prognoses for young people with early onset of illness. This group is more likely to be diagnosed as suffering from more chronic illnesses, such as schizophrenia (Lelliot et al, 1994; Hafner & an der Heiden, 1997), and so their duration of illness will be relatively long and costs relatively high.
As with dependent living, the positive relationship found between total 2-year costs of care and days spent in hospital for psychiatric reasons in the 2 years prior to trial entry suggests that past levels of dependency on psychiatric services are predictive of future levels of dependency and therefore future costs, a finding supported by previous research (Keane & Fahy, 1982; McCrone et al, 1998). Tests of interaction found this relationship to be stronger for patients who had spent longer in independent living in the 2 years prior to trial entry, reflecting the fact that additional hospital costs will be offset by reductions in the cost of supported accommodation for those who are more dependent in their living situation.
Analysis of the interaction between social disability and independent living revealed a significant association between costs and level of social disability for patients with no independent living in the 2 years prior to trial entry. The total costs of care were found to increase as social disability increased, in line with similar findings (McCrone et al, 1998), reflecting the more dependent nature of this group of patients.
Although of less statistical significance, an association was found between total costs of care and level of unmet need at the point of entry into the trial. It is reasonable to assume that patients with a greater number of unmet needs will require a relatively greater intensity of support to meet these needs and will cost more than their counterparts. The results of this analysis support this assumption.
Explained variation
The multiple regression model explained just under 30% of the variation in
total costs. Although low, this figure is similar to that found in previous
research (Knapp et al,
1990,
1995;
Chisholm et al, 1997;
McCrone et al, 1998)
and in part reflects the baseline nature of the study, since costs will
obviously be influenced by post-baseline events as well
(Knapp et al, 1990;
McCrone et al, 1998).
The advantage of including baseline characteristics alone, however, is the
ability to determine causation in the relationships found. It is also possible
that such consistently high proportions of unexplained variation are the
result of a failure to measure certain variables that have a significant
impact on the variation in costs. Variables that are often excluded from
trials of this kind, which may be of some significance, include the
availability of local services, the travelling times involved and budgetary
constraints on service providers. Perhaps of more importance in this
population is the patient's perception of the quality and usefulness of the
available services and their perception of their own level of need. The
examination of such relationships would require the inclusion of a broader
range of quantitative variables and possibly a qualitative element in future
analysis.
Clinical implications
In this population with severe psychotic illness, total costs of care were
found to be more strongly influenced by levels of dependence and need than by
measures of severity of illness. Over a quarter of the total costs of care
were borne by the social services sector in the form of staffed accommodation,
which naturally will be determined by dependence and need, rather than
clinical diagnosis or severity of illness. By far the greatest burden,
however, fell on the National Health Service, which contributed approximately
65% of the total costs of care. Service planners in the health service should
be aware of the considerable cost implications of patients with a high degree
of dependency on statutory services and the implications this may have for
future resource allocation and the targeting of mental health services.
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Clinical Implications and Limitations |
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LIMITATIONS
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ACKNOWLEDGMENTS |
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Received for publication May 3, 2000. Revision received October 18, 2000. Accepted for publication October 27, 2000.
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