Service conSiderationS

The cost of mood disordersanita Patel

AbstractMood disorders place substantial clinical, social, and economic burdens

on individuals with the disorders, their families, and wider society. at

the same time, the scarcity of health-care resources necessitates the

efficiency of alternative treatments to be examined. newer, more expen-

sive, treatments always bring new cost concerns. However, costs alone

are not an informative basis for decisions about the allocation of scarce

resources. When broader perspectives are taken, such treatments can

often demonstrate cost-effectiveness through improved clinical and/or

quality-of-life outcomes, reduced use of other health-care resources, and

improved participation in employment.

Keywords bipolar disorder; cost-effectiveness; costs; depression; eco-

nomic evaluation; mood disorders; psychological therapies; resources;

SSri; tricyclic

The relevance of economics in mental health care

There is an accumulating body of evidence about the epide-miological burden of mental health. For example, in 1996 the World Health Organization reported that psychiatric disorders (two of which were unipolar depression and bipolar affective disorder) accounted for five of the ten leading causes of dis-ability worldwide.1 In addition to the clinical and social burden that mental health problems place on individuals, families, and communities, there are substantial associated economic conse-quences that have an impact at all levels of society. Together with limited professional, pharmaceutical, and other resources, economic considerations inevitably have to be accounted for in mental health policy and practice. One factor that has generated a great deal of interest in the economics of mental illness over the past decade or so is the apparently high cost of some new treatments; for example, the acquisition costs of third-generation antidepressants are many times higher than those of the older treatments they could potentially replace, raising questions about their value-for-money in an environment of resource pressures.

Anita Patel PhD is Senior Lecturer in Health Economics at the Institute

of Psy­chiatry­, London, UK. Her research interest is in applied economic

evaluation, and she has conducted evaluations of pharmacological,

psy­chological, and other treatments across a wide diagnostic

spectrum both within and outside of the mental health field. Conflicts

of interests: Pay­ment received from servier (www.servier.com) for

preparatory­ work in relation to the economic evaluation of their

antidepressant product.

PSYcHiatrY 8:2 76

Another area of growing interest is the value of psychological therapies, particularly cognitive behavioural therapy (CBT), and the related severe shortage of qualified therapists who are able to deliver them.

Economic consequences of mood disorders

The most obvious economic consequence of any disorder is the cost of health care. Health-care costs for mood disorders need to be considered in the context of particular features of the dis-orders and their treatment (Table 1).

Under-treatmentA European study of depression in the community found a 6-month prevalence rate of 17% among a sample of 78,463 adults across six countries.2 Although the study was carried out at a time when understanding of mood disorders and their poten-tial treatments was encouragingly on the increase, 43% of those suffering from depression were found not to have sought any treatment. Furthermore, 69% had received no drug treatment. There is also evidence that sufferers who do present to services are often treated inadequately – for example, not receiving anti-depressants, not receiving the most appropriate antidepressant, or receiving sub-therapeutic doses of antidepressants. There are also issues of over-presentation to services: the stigma associated with mental illness results in sufferers presenting with physical symptoms, leading to unnecessary use of resources for investiga-tions and treatment. Thus, under-treatment for mood disorders

• the broad economic impacts of mood disorders, such as the

inability of some sufferers to participate fully in work and the

consequent societal productivity losses and social security

burden, are causing increasing concern

• Psychological therapies are currently being seen as important

alternatives or adjuncts to pharmacological treatments in

certain patient groups, leading to initiatives to improve access

to these currently limited-supply treatments in the hope that

costs will be offset by increased participation in work

What’s new?

Factors influencing the economic consequences of mood disorders

• High prevalence

• chronic/recurrent course

• High levels of co-morbidity

• Low levels of presentation to services

• High levels of under-recognition

• High levels of under-diagnosis

• High levels of under-treatment

• High levels of inappropriate treatment

Table 1

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can obscure the impact on health-care resources. More impor-tantly, it leads to major economic effects elsewhere.

Impact on societyEconomists often aim to take a ‘societal perspective’, also tak-ing into consideration the consequences on areas of society other than the health-care sector. One of the most significant impacts of mood disorder is on employment, or, more specifi-cally, the inability of sufferers to work, increased absenteeism, and impaired performance. These effects are referred to as ‘lost productivity’, to describe losses to society resulting from an individual not participating fully in the job market. The low levels of treatment found in the study by Lepine et al.2 inevi-tably had consequences on sufferers’ ability to work: over a 6-month period, those with major depression took an average of 13 days off work due to illness, compared with 2.5 days for those without depression. Lost productivity is an important issue in mood disorders, because these illnesses often strike during working age and their chronic nature leads to the accu-mulation of lost productivity throughout a person’s working life. The cost of suicide-related mortality is also often mea-sured in terms of productivity lost to society. It is still fairly unusual for studies of new treatments to consider impacts on these employment outcomes. For example, it would be rele-vant to consider whether the clinical improvements associated with new antidepressants translate into improved occupational outcomes.3

Cost-of-illness estimates

The types of consequence described above (plus many others) are often described and summed up in the form of ‘burden of disease’ or ‘cost of illness’ (COI) studies. COI estimates are help-ful to try to convert the multiple economic impacts into a single, cost-based measure of the consequences of an illness. They allow a better overall understanding of its relative magnitude com-pared with burdens associated with other illnesses, and indicate the potential for reducing costs through more effective treatment. COI studies often classify costs into three conventional categories (Table 2).

Direct costs describe the costs of treatment, such as in-patient, out-patient, and community services (including social services).

Indirect costs are the ‘knock-on’ effects of the illness, such as the employment and premature death effects described above and the time that family members commit to providing informal care to sufferers. In fact, informal care is now recognized as such a major component of care provision (in terms of both size and importance), particularly for chronic illness sufferers, that it is now commonly counted as a direct cost.

Cost categories

• direct – expenditure on providing health and social care

• indirect – lost opportunities for work and leisure

• intangible – reductions in well-being

Table 2

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Intangible costs are those that are widely acknowledged but difficult to measure in monetary terms, such as the emotional burden placed on carers. However, there are now methods that make such valuations possible (e.g. the willingness-to-pay approach). The relative size of the contribution of these differ-ent types of cost to the total cost of depression is illustrated in Figure 1.

DepressionCOI estimates for depression in the USA vary between $12.4 billion per year for direct treatment costs (28% of total soci-etal costs) and $4 billion per year for the consequences of not treating depression.4,5 One of the earliest UK COI studies for depression was carried out by Kind and Sorensen, who esti-mated National Health Service and local authority costs for England and Wales to be nearly £420 million (1991 prices) per year.6 These were far outweighed by indirect costs, estimated at £2.973 billion in lost earnings associated with depression. They further estimated that 90,189 life-years were lost due to depression-related mortality. Jonsson and Bebbington estimated a lower figure of £222 million (1990 prices) for the direct costs of depression in the UK.7 COI estimates can, of course, date owing to subsequent changes in care provision (e.g. in relation to prescribing and care settings) and other factors. Thomas and Morris’ more recent estimates for England in 20008 accounted for such evolutions in depression care and calculated direct treatment costs as £370 million, which is not too dissimilar to earlier estimates after accounting for inflation. Their total cost estimate of more than £96 billion (detailed in Figure 1) largely comprised loss of earnings for those living with depression, but also included the smaller, but nevertheless important, impact of loss of future earnings due to premature death by suicide and accidental antidepressant poisoning.

Contribution of different types of cost to overall costsof depression

Adapted from Thomas and Morris (2003)8

Loss of earnings due to morbidity

Loss of earnings due to mortality

Health-care costs

Medication

In-patient care

Out-patient care

Day-case care

GP consultations

Figure 1

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Bipolar disorderAnnual societal costs to the UK of bipolar disorder have been estimated at £2.055 billion (or nearly £7000 per person with the disorder).9 This total consists of: • costs to the health service (£199 million) • other statutory services (£86 million) • indirect costs arising from employment effects and suicide

(£1.77 billion).An earlier estimate from the USA stood at $45.21 billion for

about 2.5 million adults with the disorder (or $18,000 per per-son).10 Both of these studies drew comparisons with COI esti-mates for schizophrenia from other studies, in order to illustrate differences in treatment patterns between the two disorders. Bipolar disorder costs amounted to 54% and 70% of schizophre-nia costs in the UK and USA respectively. However, compari-sons between COI studies should be treated with caution. For example, Wyatt and Henter10 calculated costs to care-givers at $6 billion, whereas Das Gupta and Guest9 excluded these costs from their calculations after finding no evidence from published litera-ture that unemployment rates for carers of people with bipolar disorder were different from those in the general population.

Interpreting cost-of-illness studiesFrom just these few studies, it can be seen that COI estimates vary widely depending on the methods and assumptions used. Therefore, when constructing or using COI estimates, it is impor-tant to consider factors such as which prevalence/incidence rates, services, unit costs, and inclusion/exclusion criteria are used. Nevertheless, a common finding of such studies is that indirect costs far outweigh the direct costs of care and treatment, highlighting that treatment costs may form only a small propor-tion of the total economic burden of mood disorders on society.

Economic evaluation

In addition to the methodological problems associated with COI estimates, they have a more important limitation: they do not indicate solutions. COI estimates say nothing about the relative efficiency or equity of the way in which resources are used, and thus a more useful approach is to examine costs alongside evid-ence of the effectiveness of alternative approaches to treatment.

Economic evaluation offers a range of evaluative tools to answer questions about efficiency, the best known being cost-effectiveness, cost–benefit, cost–utility, and cost–consequences analyses. Each of these examines the relationship between costs and outcomes. The issues involved in identifying, measuring, and valuing costs are identical across all types of evaluation (see Knapp, 1995, for a detailed description of approaches to costing in mental health care11), but outcomes are measured in different ways.

Cost-effectiveness analysis looks at a relevant single effective-ness dimension, such as the number of symptom-free days or the duration of time to relapse. An ideal (although rare) scenario is one in which a new treatment produces better outcomes at lower cost. However, it is more common to find that improved outcomes come at a higher cost. In such cases, ratios can be calculated to represent the additional cost per additional unit of outcome for one treatment against another (a low ratio is desirable). Linking costs with outcomes in this way allows for the possibility that a

PSYcHiatrY 8:2 7

treatment that comes at a higher cost, such as the use of selective serotonin-reuptake inhibitors (SSRIs), can be more cost-effective if there are associated improvements in outcomes. Examining ratios based on point estimates of costs and outcomes carries the limitation of not representing any of the variability, and therefore uncertainty, surrounding these estimates. However, techniques such as cost-effectiveness acceptability curves can deal with this and are increasingly used alongside, or instead of, ratios, because they carry the added advantage of accounting for how much value a policy-maker places on the outcome of interest (see Fenwick and Byford12 for a brief guide). This technique can also be applied to cost–utility analyses (described below). One weak-ness of this cost-effectiveness analysis approach in general is that it focuses on only a single outcome when multiple outcomes are likely to be of interest. Three approaches allow the comparison of multiple outcomes, as follows.

Cost–consequences analysis is the most straightforward. This presents the full range of costs and outcomes, without computa-tion of summary measures, so that decision-makers can weigh up the relative costs and outcomes more informally.

Cost–benefit analysis, on the other hand, attaches monetary weights to multiple dimensions of outcome so that they can be aggregated into a single summary measure. The decision is then to see whether the monetary benefits exceed the monetary costs for each treatment option being considered. The methodological challenges of applying monetary values to clinical outcomes are discussed by Knapp.11

Cost–utility analysis also seeks to reduce outcomes to a sin-gle dimension and can be seen as a specialized form of cost-effec-tiveness analysis. It measures and then values outcomes from different treatment approaches in terms of improvements in pref-erence-weighted, health-related quality of life. The quality-of-life improvement is measured in terms of ‘utility’, usually expressed by a combined index of the mortality and quality-of-life effects of an intervention, such as quality-adjusted life years (QALYs). The use of such a generic measure of outcome usefully allows com-parisons to be made across different diagnostic groups, which is why it plays a central role in cost-effectiveness considerations made by decision-makers such as National Institute for Health and Clinical Excellence (NICE). However, there is a concern that existing generic utility measures are not sensitive to change in mental health status,13 and cost–utility analyses of treatments for mood disorders are still relatively uncommon. A review of the few such evaluations that exist showed that pharmacologi-cal interventions for depression tended to have lower costs per QALY (compared with other types of intervention), and that psy-chotherapy and care management have lower costs per QALY compared with usual care.14

State of the cost-effectiveness evidence

SSRIs versus tricyclic antidepressantsRelative to a large body of evidence of clinical outcomes of dif-ferent treatment approaches for mood disorders, there is little linking these outcomes with costs, and what there is mainly con-cerns comparisons of SSRIs versus the older tricyclic antidepres-sants. Although such evidence may now seem redundant owing to the falling costs of SSRIs, it does in fact remain relevant be-cause cost-effectiveness considerations extend beyond drug costs

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to other care costs, non-care costs, and clinical and quality-of-life outcomes. Claims for the cost-effectiveness of SSRIs are generally based on two clinical advantages: • they are better tolerated, leading to improved compliance • they are safer in overdose and thus help prevent suicide.

Hotopf and co-workers15 acknowledged these advantages but argued that there was insufficient evidence that they justified the extra cost of SSRIs, mainly because much of the cost-effectiveness evidence at that time was heavily reliant on crude modelling approaches. Modelling studies simulate the management of a disorder using existing evidence where available, supplemented with methods of estimation (e.g. expert opinion) to fill evidence gaps. Not surprisingly, this leaves a fair amount of scope for the introduction of bias. Many other cost-effectiveness studies are based on retrospective designs that also carry limitations.

A subsequent assessment by Frank et al.16 suggested that methodological advances were taking place in retrospective stud-ies, and that the higher acquisition costs of SSRIs were at least offset by reductions in other costs. At the time of their review, Hotopf and colleagues15 found no randomized controlled trials (RCTs) with simultaneous economic evaluations. Five years later, Frank et al.16 could identify only two, both of which showed few differences in costs and outcomes when fluoxetine was com-pared with tricyclics and with sertraline. However, they pointed out that economic evaluations within RCTs also have limitations, one of which is that they are rarely sufficiently powered to detect differences in costs or cost-effectiveness.

Two other reviews of the cost-effectiveness of antidepressants are worth noting as they also highlight the need for more good-quality evidence. Woods and Baker17 reviewed one prospective, four retrospective, and 15 modelling studies, and hesitantly con-cluded that first-line treatment with SSRIs may not be cost-effec-tive from a health-care perspective. As with other reviews, the tentative nature of their conclusion arises from methodological limitation of the studies reviewed and they too argue for more prospective cost-effectiveness studies. More recently, Barrett and colleagues18 identified a further four cost-effectiveness stud-ies from prospective trials or naturalistic settings, each of which indicated equivalent or better cost-effectiveness compared with the comparators used in the studies.

The state of the cost-effectiveness evidence for bipolar dis-order treatments is similarly equivocal. However, a review of studies published since 1966 found that preliminary data sug-gested important differences in the onset of action between three treatments – lithium, valproate, and carbamazepine – and that these differences had an impact on length of stay in hospital.19 Impacts on in-patient stays are important in cost-effectiveness analyses from a health-care perspective, because in-patient costs are usually the largest component of overall care costs.

Third-generation antidepressantsAlthough concerns about SSRI costs may abate because they are now available in generic form at lower prices, the appearance of a third generation of antidepressants (such as venlafaxine and mirtazapine) raises fresh concerns. Again, evidence of their cost-effectiveness has begun to be built using modelling stud-ies, leading to the same inconclusiveness and limitations that early evidence on SSRIs suffered. For example, Montgomery et al.20 reviewed studies carried out between 1993 and 2003, and

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concluded that modelling-based studies tended to report third-generation antidepressants as cost-effective compared with tricy-clics and SSRIs, whereas studies based on patient-level cost data were less conclusive. It is therefore clear that study design has an important impact on the reliability of economic evidence. Iqbal and Prashker21 have provided a helpful critique of methods used in economic evaluations of antidepressants and how these may impact upon the reliability of study conclusions.

Psychological treatmentsThere are of course non-pharmacological treatments to consider, such as CBT and interpersonal psychotherapy. Evaluations of these have been encouraging, showing clinical efficacy and, importantly, acceptability to patients. Although economic evalu-ations of pharmacological interventions have balanced towards modelling studies, those of psychological interventions have tended to come from prospective trials.

A meta-analysis of four studies of counselling for depression compared with usual care suggested that it can produce better clinical outcomes in the short term but not in the long term, and that it was associated with higher direct costs (an average of £92 more in the short term and £110 more in the long term).22 Barrett et al.’s review of other psychological therapies (such as CBT and psychotherapy) also indicated equivalent or lower cost-effec-tiveness compared with other treatments owing to significantly greater costs, particularly when compared with pharmacological treatments.18

These findings are unsurprising as the necessary intensive inputs from qualified professionals can be costly. However, cost-effectiveness can vary across different types of patients and set-tings. Following a review of the clinical and cost evidence for depression treatments, NICE recommended that ‘when patients present initially with severe depression, a combination of anti-depressants and individual CBT should be considered as the combination is more cost-effective than either treatment on its own’.23 Following that, further guidance has recommended that psychological therapies should be offered for at least 3 months’ duration as a first-line treatment for children and young people presenting with moderate to severe depression,24 and new fund-ing has been committed to increase the supply of, and therefore access to, psychological therapies.

Economic evaluations of psychological therapies for bipolar disorder are still quite rare, but Lam and co-workers25 reported a trial comparing the use of mood stabilizers alone with mood stabilizers combined with cognitive therapy. People receiving the therapy had 110 fewer days of bipolar episodes and £1300 lower costs over a 30-month follow-up period.

Conclusion

Cost-of-illness studies related to mood disorders serve to confirm their enormous social impact. Cost-effectiveness evidence of dif-ferent treatment approaches aids the vast range of objective and subjective judgements that need to be made about care, at both individual patient and health-care system level.

With depression set to become the second largest cause of disability worldwide by 2020, cost-of-illness studies demon-strate that expenditure on drugs comprises only a small com-ponent of health-care costs, a fact that is sometimes overlooked

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in discussions about new and more expensive treatments. It is, of course, important to examine carefully the cost-effectiveness of any new treatment because of resource pressures, but dis-cussions of the higher costs of new drugs and of new forms of psychological treatment need to see them in the context of other, more significant, costs. Large economic impacts (e.g. carer bur-den, lost productivity) that are often hidden, and the long-term nature of the disorders, need to be considered in decisions about the cost-effectiveness of treatments. ◆

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FURThER READIng

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London: Martin dunitz, 2002.

(A short and highly­ accessible introductory­ overview of economic

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