World Health Organization Collaborating Centre in Evidence for Mental Health Policy, School of Psychiatry, University of New South Wales at St Vincents Hospital, Sydney
School of Public Health and Community Medicine, University of New South Wales, Sydney
Correspondence: Professor Gavin Andrews, Clinical Research Unit for Anxiety and Depression, 299 Forbes St, Darlinghurst NSW 2010, Australia. Fax +612 9332 4316; e-mail: gavina{at}crufad.unsw.edu.au
See editorial, pp.
375376, and
invited commentary, p.
436, this issue.
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ABSTRACT |
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Aims To use epidemiological data on schizophrenia to model the cost-effectiveness of current and optimal treatment.
Method Calculate the burden of schizophrenia in the years lived with disability (YLD) component of disability-adjusted life-years lost, the proportion averted by current interventions, the proportion that could be averted by optimal treatment and the cost-effectiveness of both.
Results Current interventions avert some 13% of the burden, whereas 22% could be averted by optimal treatment. Current interventions cost about AUS$200 000 per YLD averted, whereas optimal treatment at a similar cost could increase the number of YLDs averted by two-thirds.Even so, the majority of the burden of schizophrenia remains unavertable.
Conclusions Optimal treatment is affordable within the present budget and should be implemented.
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INTRODUCTION |
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METHOD |
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In mental disorders, death by suicide or increased physical morbidity are rarely attributed to the underlying mental disorder. In the Australian Burden of Disease study only 2% of the burden of schizophrenia was attributed to YLLs, despite the reduced life expectancy and the suicide rate. In this series of papers we will mention the YLL but develop models using the more important and more easily available YLD data. The true burden of a disorder, defined as burden in the absence of treatment, is calculated from the burden observed in the population under study plus the burden presently averted by the current population coverage and mix of interventions (Assumption 3). The observed burden was calculated from the prevalence of each disorder (identified as a current principal complaint) multiplied by the disability weighting for that disorder, to give the YLD (Assumption 4). Consistent with a previous analysis (Melse et al, 2000), age weighting and discounting were not applied because the former is controversial and the latter was inappropriate given the cross-sectional prevalence perspective of the study.
We identified the YLDs averted by the current mix of services from the proportion of prevalent cases deemed to have received an effective treatment in the past year (Assumption 5). Calculating the YLDs averted by effective treatment is a new field. The primary outcome in mental disorders is measured as changes in symptoms, but improvements in functioning and quality of life are increasingly included (Smith et al, 1997). These are most appropriately represented as changes in the disability weighting in the YLD formula, estimated from the effect sizes in efficacy studies (Andrews et al, 2000) (Assumptions 6 and 7). The YLD averted by current treatment added to the observed burden gives baseline burden in the absence of treatment. This serves as a comparator in the analysis (Assumption 8) and provides the baseline for calculating the percentage of burden averted.
The respondents to the surveys listed the services used and treatments received for a mental health problem during the previous 12 months (Andrews et al, 2001) (Assumption 9). Unit costs for each service or procedure were obtained from published sources and expressed in the values of the reference year (19971998 constant Australian dollars) using the consumer price index health deflators. The cost of services used in the previous year was calculated for each person with a principal complaint of a mental disorder (Assumption 10). The average 12-month cost per case of each disorder was calculated and, when divided by the number of YLDs averted, gave a simple cost-effectiveness ratio in dollars per YLD averted for each disorder.
Next we calculated the proportion of the burden that could be averted with improved efficiency. We assumed that coverage remained at the present levels, that clinicians only used evidence-based treatments and that compliance with treatment paralleled that seen in efficacy studies (Assumption 11), and again calculated the cost per case and cost per YLD of optimal treatment. Accepting that there is unlikely to be a radical increase in the mental health service budgets, we ask whether the money spent on optimal treatment would be more or less than that spent on the current mix of treatments. If optimal treatment at the current level of coverage leaves money unspent, we ask if other, presently non-cost-effective interventions should be purchased or whether the money would be best spent on increased coverage (see Fig. 1).
These calculations were informed by a sensitivity analysis conducted with the @RISK version 4 software (Newfield, NY: Palisade Corporation) for Microsoft Excel, which uses a Monte-Carlo simulation approach to provide 95% confidence intervals around YLDs averted, total cost of treatment and cost per YLD averted. A multivariate stepwise linear regression was also conducted for each of the above three estimates, with this estimate as the dependent variable and the individual cost and outcome units of data as the independent variables. This analysis identifies the most important contributors to variance in each parameter. In addition, univariate sensitivity analyses were conducted on variables that were defined by the investigators in consultation with experts, with these variables varied individually to determine their impact on the above estimates. Finally, we calculated the effect of optimal treatment on burden averted, given total coverage and concordance, and expressed this as the proportion of burden theoretically avertable with existing knowledge. The remaining burden is that unavertable with existing knowledge and interventions (shown by the white box in Fig. 1) and is an indication of the need for investment in research and development.
Specific method for schizophrenia
Burden of disease
The YLD from schizophrenia was calculated from the prevalence of the
disorder multiplied by the disability weighting. The 1-month prevalence was
taken from Jablensky et al
(2000), a catchment area study
of low-prevalence psychotic disorders (n=980). This group was divided
into severity categories based on longitudinal course of illness
characteristics (Jablensky et al,
2000), with the proportion of the total group in each category as
follows: new incident cases (2%); people who experienced complete or partial
remission between episodes, defined as no psychotic symptoms but residual
anxiety and depression (30%); people who experienced negative symptoms between
episodes (23%); and people who experienced a continuous level of psychotic
symptomatology without resolution between episodes (45%). Apart from this last
group, it was estimated that 23% of a persons time would be spent in a
psychotic episode (Wiersma et al,
1998). A disability weighting of 0.82 for acute psychosis was used
(Sanderson & Andrews,
2001), whereas for time spent in remission with residual
anxiety/depressive symptoms the disability weighting of 0.34 for moderate
depression was applied (Sanderson &
Andrews, 2001) and for the time in remission with negative
symptoms a milder weighting of 0.46 for schizophrenia was applied (taking the
average of a milder and more severe schizophrenia weighting; Stouthardt et
al, 1997). These data provided a composite disability weighting of
0.638.
Current and optimal treatment
The type and amount of services currently being received was obtained from
Jablensky et al
(2000) and from additional
data supplied by those authors. Optimal treatment was defined by
recommendations in the clinical practice guideline literature, primarily the
PORT study recommendations (Lehman &
Steinwachs, 1998) (Assumption 12), which continues to be an
industry standard (Milner &
Valenstein, 2002). Interventions of interest were those that
improve clinical and functional outcomes, because these are directly relevant
for mapping to changes in the disability weighting used in calculating the
YLDs averted. These recommendations were operationalised into detailed
treatment regimes on the basis of published literature and expert opinion
(Assumption 12). Because there were numerous possibilities for the
distribution of the prevalence cohort across different treatment providers and
interventions, a range of values for these parameters was incorporated in the
sensitivity analysis (as described above). In both current and optimal
scenarios the interventions were linked to meta-analyses to estimate their
efficacy and hence the change in disability weighting, with analyses chosen
for methodological rigour and ability to code overall effect sizes of
treatment benefit (Skelton et al,
1995; Mojtabai et al,
1998; Leucht et al,
1999; Jones et al,
2000).
The benefits of medication plus psychosocial interventions were considered additive (Mojtabai et al, 1998), whereas if a person received more than one psychosocial intervention they were attributed the benefit of the treatment with the largest effect size. A transfer factor of 0.181 was derived and used to transform effect size superiority over placebo due to treatment into preference weighting change due to treatment (Andrews et al, 2000). Because the specific placebo effect is negligible in schizophrenia (Quality Assurance Project, 1984), the improvement observed in placebo groups represents natural history and/or regression to the mean, so these effect sizes represent the benefit in comparison with natural history and are thus consistent with the comparator of no treatment in the analysis (Assumption 8). Some patients remain asymptomatic despite sequential treatment with different drug categories, referred to as treatment resistance (Assumption 13). Treatment resistance was modelled at 20% (Conley & Kelly, 2001). It should be noted that effect sizes for specific interventions and not mode of delivery were used, because treatment outcome is largely dependent on interventions received rather than the system of care under which it is delivered (Thornicroft et al, 1999). Systems of care such as case management are included in the hypothetical model of optimal care for the present study because they are important for coordination of efficacious services (Lehman & Steinwachs, 1998), but costs rather than outcome have been attributed to these service systems. There is as yet no evidence for the prevention of schizophrenia (Warner, 2001), so overall prevalence remained unchanged.
Cost of services used
The perspective of this study was government or funder costs
and it does not take account of any out of pocket or indirect
costs. These additional calculations are available from Carr et al
(2003). Costs were calculated
for the reference year and unit costs obtained from other years were converted
to 19971998 costs using the health component of the consumer price
index. Costs are for 12 months of treatment. Two additional calculations were
included for the cost of current care for schizophrenia to ensure consistency
with other disorder analyses, because these other analyses were based on data
from the Australian National Survey of Mental Health and Well-Being
(Andrews et al, 2002).
Using responses from screener-positive cases on a psychosis screener used in
the National Survey, we estimated the total treatment costs for other contacts
for a mental health problem (including radiologists, pathologists, general
medical specialists and other counsellors). We also adjusted the number of
general practitioner contacts from the low prevalence survey
(Jablensky et al,
2000) (which were not specifically mental-health-related contacts)
by the proportion of all such contacts that were mental health related in the
National Survey (35.6%), such that we were costing only mental-health-related
general practitioner contacts.
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RESULTS |
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Description and outcome of current and optimal treatment
Current treatment
The Jablensky et al
(2000) survey was a catchment
area study that identified all persons known to medical and social services.
The pattern of contacts across various health sector providers and the
interventions received are presented in Tables
2 and
3. Nearly all persons were
being prescribed an antipsychotic medication (haloperidol or other typical
antipsychotic, 51%; atypical antipsychotic, 25%, clozapine, 12%). A much
smaller proportion was receiving a psychosocial intervention. The proportions
for social skills training and psychological therapies were discounted by 50%
in the efficacy calculation, because it was considered unlikely that the full
proportion were receiving an evidence-based version of this intervention
(Carr et al, 2003).
The disability weighting change attributed to these pharmaceutical and
psychosocial interventions was derived from the weighted effect size
multiplied by the transfer factor of 0.181, providing an overall disability
weighting improvement of 0.121. This drops to 0.097 when the 20%
treatment-resistant group is included. This produced a burden averted of 3774
YLDs (see Table 3). Thus, the
adjusted disability weighting for the null position of no treatment in the
Australian population was 0.638+0.097 or 0.734, and the untreated or baseline
disability burden of schizophrenia was thus 28 671 YLDs. These data show that
only 13.2% of the disability burden of schizophrenia is averted by current
services.
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Optimal treatment
We operationalised optimal care as described by the PORT study
(Lehman & Steinwachs,
1998) for the severity groups described earlier. The disability
weighting changes were derived from the effect sizes associated with the
treatments used, exactly as was done for current care (see
Table 3). The groups were new
incident cases (disability weighting change=0.227), complete or partial
remission (disability weighting change=0.220), remission with negative
syndrome (disability weighting change=0.213) and continuous psychotic symptoms
(disability weighting change= 0.159). This provides an overall disability
weighting change of 0.159, providing 6217 YLDs averted or 21.7% of baseline
YLDs.
Cost and efficiency of current and optimal treatment
Current treatment
The unit costs of treatment are provided in
Table 4, which were combined
with the data on service contact in Table
3 to provide the total cost. The average cost of a person with
schizophrenia being treated for 1 year was AUS$18 949 in 19971998 and
the total direct governmental cost of schizophrenia was the cost per case
multiplied by the number of cases, or AUS$740 million. This money averted 3774
YLD, giving a cost-effectiveness ratio of AUS$196 070 per YLD gained.
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Optimal treatment
As for current care, the unit cost data in
Table 4 were combined with
service use data in Table 2 to
estimate the total cost of treatment. The average cost of a person with
schizophrenia being treated for 1 year (AUS$17 113) was very similar to that
of current care, providing a total population cost of AUS$668 million. Bed-day
costs account for half of this expenditure, down from 85% with current care.
Optimal treatment models shorter overall bed-days, especially for longer-stay
beds with the advent of clozapine, and a greater use of community-based
services. For this expenditure a higher number of YLDs were averted (6217),
giving a cost-effectiveness ratio of AUS$107 482 per YLD gained.
Comparative efficiency
When current care and optimal care are compared, the number of YLDs averted
increases by two-thirds but the cost remains stable, so the AUS$/YLD averted
is reduced and efficiency improves. The proportion of burden averted changes
similarly, rising from 13% to 22% (Table
5). The 95% confidence intervals are also presented in
Table 5, indicating significant
variation according to the information used to estimate costs and outcomes. As
part of the sensitivity analysis, linear regression analyses showed that the
most important variables that determined variation in YLDs averted were the
cognitivebehavioural therapy and haloperidol effect sizes, and the
transfer factor to convert these to disability weighting changes. Similarly
for optimal care, the most important predictors were the
cognitivebehavioural therapy and risperidone effect sizes and the
transfer factor. Variation in total costs for both optimal and current care
were driven by the unit costs, with the largest variance estimates around case
manager contacts and bed-days. When these two estimates were put together to
provide cost per YLD averted, the most important predictors in variation were
the acute and non-acute bed-day unit costs and the cognitivebehavioural
therapy effect size for current care, and standard case manager unit cost,
intensive case management number of contacts and cognitivebehavioural
therapy effect size for optimal care.
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The univariate sensitivity analyses showed that although some investigator assumptions did have an impact on the cost per YLD, the overall conclusions were not affected. For current care, we estimated that 50% of those receiving psychosocial interventions received an evidence-based version of this treatment. If we take a more optimistic view and increase this to 80%, the cost per YLD reduces by 13% to AUS$170 297. If this is decreased to the more realistic scenario of 20%, the cost per DALY increases by 18% to AUS$231 473. Both estimates are still large and substantially less efficient than the point estimate for optimal care. Similarly, the conclusions for optimal care are not changed if we double the proportion of people on clozapine (cost-effectiveness decreases by 2% to AUS$109 098), or increase total bed-days by 50% (efficiency declines by 11% to AUS$118 917). If we reduce by 50% the proportion of people with a case manager as their primary clinician, and assign these people to psychiatrist-managed care, the efficiency improves by 17% to AUS$89 015. A more optimistic value of 10% of prevalent cases considered treatment resistant improves efficiency by 11% for current treatment and 9% for optimal treatment. If a more pessimistic scenario of 30% treatment resistance is modelled, efficiency is reduced by 14% for current treatment and 11% for optimal treatment.
The low prevalence study (Jablensky et al, 2000) identified patients known to services and it is not surprising that all were in receipt of some treatment. If they constitute the vast majority of people with schizophrenia, then the theoretical upper limit of the burden of schizophrenia that is able to be averted by current knowledge, even given perfect coverage, competence and compliance, is less than one-third of the burden, presuming that 90% of cases are already in treatment.
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DISCUSSION |
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Threats to validity
This is a modelling study and many assumptions have been made. The
assumptions and supporting references are listed in
Table 1. The prevalence and
coverage in the Jablensky et al
(2000) data came from what was
an urban-based treated prevalence study. Because 85% of Australians live in
urban regions and over 90% of the population are treated in urban regions, the
results should be considered representative. If the prevalence had been
corrected for the people in the community not known to services
(Link & Dohrenwend, 1980),
then the prevalence would rise to 0.35% and the coverage would drop to about
80%. The latter is closer to the 60% coverage calculated from the Dutch
NEMESIS survey (Bijl et al,
1998) once they added patients in institutions to those identified
in the community survey.
People with schizophrenia have a reduced life expectancy (Andrews et al, 1985) yet YLLs are poorly represented by the data, especially those due to suicide. Thus the burden of the disease will be greater than that estimated. Changes in DALYs due to intervention are calculated from changes in YLDs but we are unaware of any data showing that current or optimal treatment prolongs life. The estimate of the burden averted by treatment may not be low but the proportion of burden averted may be an overestimate. The method for estimating change in disability weighting was developed for this project. When compared with the few prospective studies that have measured both changes in mental health status and health state preference values, it gives comparable results (Chouniard & Albright, 1997; Andrews et al, 2000). From the evidence to date it is thus likely to be appropriate even if the transfer factor between effect sizes and disability weighting change is updated by future research. Modelling atypical antipsychotics in favour of typical antipsychotics is controversial (Geddes et al, 2000). If half of those modelled to receive an atypical antipsychotic under optimal treatment are moved to a typical antipsychotic (haloperidol), then efficiency is reduced by 6% to AUS$114 440 per YLD averted. Similarly, the evidence for the efficacy of social skills training has been questioned recently (Pilling et al, 2002). This intervention had the smallest effect size of the psychological strategies included and was only modelled to the two most severe groups. These two groups were also receiving one of the other recommended psychological therapies (family therapy or cognitivebehavioural therapy), so removing social skills training from the analysis does not alter the results.
The prevalence, service use and unit cost data are from Australia but because Australia has fewer psychiatric beds than other established market economies (World Health Organization, 2001) the current treatment is unlikely to be more expensive than in other developed countries. Nevertheless, there will be country-specific differences in bed-days and pharmaceutical costs. The finding that optimal care is no more expensive but twice as efficient is likely to be transferable. The costs of implementing evidence-based treatment have not been included and the magnitude of the added benefits in relation to these initial and ongoing costs may not always be favourable (Mason et al, 2001). The finding that only a modest degree of the burden of schizophrenia and schizoaffective psychosis is currently averted is consistent with clinical experience (McGlashan & Johannessen, 1996); the finding that optimal care would leave the majority of the burden unaffected is of serious concern.
Relation to other work
This work began with three questions. What proportion of the burden of each
mental disorder is being averted by current treatment? What proportion could
be averted by optimal treatment? And, if optimal treatment is superior, is it
affordable? The answer in schizophrenia is clear: optimal treatment costs no
more and substantially increases the health gain. This project has covered all
the common mental disorders (affective, anxiety and substance use disorders),
the results for these disorders are not dissimilar (publication forthcoming).
Whether results for a physical disease with similar impact would correspond is
not known. It would be interesting to evaluate the cost-effectiveness of
treatment for a disease such as rheumatoid arthritis.
Implications
The cost of treatment for schizophrenia is high. It is about AUS$20 000 per
year on average and AUS$30 000 per year for the substantial minority who have
continuous psychotic symptoms. This annual expenditure is simply unaffordable
by patients or their families, especially as treatment is not sufficiently
successful to return most sufferers to the labour force. Even targeted
interventions such as supported employment have only moderate efficacy
(Crowther et al,
2001). It is not surprising therefore that treatment of
schizophrenia in developed countries is largely supported by public sector
services. In Musgroves terms
(Musgrove, 1999), public
expenditure is justified on many grounds: catastrophic annual cost, poverty of
the sufferers, externality of danger that some patients pose to society and
the simple rule of rescue. The public is afraid of psychosis and demands that
people with schizophrenia be cared for. The public did so 50 years ago when
there was no effective treatment, an attitude that illustrates that
cost-effectiveness is not the only determinant of the provision of care.
Efficiency, measured as cost-effectiveness, is low. The affordable price in AUS$/DALY for health care in the public sector is not absolute, but does tend to be around the average annual wage for a country. The average weekly wage in Australia in 19971998 was AUS$591.40 (Australian Bureau of Statistics, 1998), which is equivalent to AUS$30 753 per annum. We estimated that current treatment for schizophrenia costs some AUS$200 000 per DALY, which is well above the affordable price. Even optimal care at half this figure is well above the affordable price. It is clear that current care should move towards the pattern of optimal care, that is, towards evidence-based medicine. The changes are not complex: reduced bed-days, particularly longer-stay, would reduce the cost; and increased use of atypical antipsychotic drugs and psychological treatments would increase the cost but also improve the effectiveness. But schizophrenia is complex and, because of the acuteness of many presentations, it is simply not possible always to carry out what is optimal. Emergencies, for example, are costly. It is likely therefore that the attainable cost-effectiveness in practice will lie somewhere between the current and optimal figures.
Faced with a costly and only modestly effective treatment, it is usual to say that more research is required. The question is whether it is reasonable to invest in an enlarged research programme. The World Health Organization five-step model for investing in health research and development (Ad Hoc Committee, 1996) suggests the following steps when thinking about this problem.
Schizophrenia has a high burden, being ranked 13th of all diseases in established market economies (Ad Hoc Committee, 1996: Table A1.3). We conclude that only 13% of the burden is presently being averted, in part because we do not make the best use of existing cost-effective interventions. Nevertheless, three-quarters of the burden seems unavertable with existing interventions, and new ones are required. The knowledge base does not yet identify the direction from which new interventions could be developed. Strategic research is necessary to strengthen that knowledge base. Until that occurs, one could not estimate the promise or cost of a research and development effort and it would be difficult to meet the criteria for deciding that the research would be a wise investment of resources (see Fig. 1). This is a serious conclusion.
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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 October 7, 2002. Revision received January 14, 2003. Accepted for publication February 5, 2003.
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