Journal of Mental Health Policy and Economics 

About: Journal of Mental Health Policy and Economics is an academic journal published by Wiley. The journal publishes majorly in the area(s): Health care & Mental health. It has an ISSN identifier of 1099-176X. Over the lifetime, 401 publications have been published receiving 10464 citations.

Cost of depression in Europe.

Abstract: Background Depression is one of the most disabling diseases, and causes a significant burden both to the individual and to society. WHO data suggests that depression causes 6% of the burden of all diseases in Europe in terms of disability adjusted life years (DALYs). Yet, the knowledge of the economic impact of depression has been relatively little researched in Europe. Aims of the study The present study aims at estimating the total cost of depression in Europe based on published epidemiologic and economic evidence. Methods A model was developed to combine epidemiological and economic data on depression in Europe to estimate the cost. The model was populated with data collected from extensive literature reviews of the epidemiology and economic burden of depression in Europe. The cost data was calculated as annual cost per patient, and epidemiologic data was reported as 12-month prevalence estimates. National and international statistics for the model were retrieved from the OECD and Eurostat databases. The aggregated annual cost estimates were presented in Euro for 2004. Results In 28 countries with a population of 466 million, at least 21 million were affected by depression. The total annual cost of depression in Europe was estimated at Euro 118 billion in 2004, which corresponds to a cost of Euro 253 per inhabitant. Direct costs alone totalled dollar 42 billion, comprised of outpatient care (Euro 22 billion), drug cost (Euro 9 billion) and hospitalization (Euro 10 billion). Indirect costs due to morbidity and mortality were estimated at Euro 76 billion. This makes depression the most costly brain disorder in Europe, accounting for 33% of the total cost. The cost of depression corresponds to 1% of the total economy of Europe (GDP). Discussion Our cost results are in good agreement with previous research findings. The cost estimates in the present study are based on model simulations for countries where no data was available. The predictability of our model is limited to the accuracy of the input data employed. As there is no earlier cost-of-illness study conducted on depression in Europe, it is, however, difficult to evaluate the validity of our results for individual countries and thus further research is needed. Conclusion The cost of depression poses a significant economic burden to European society. The simulation model employed shows good predictability of the cost of depression in Europe and is a novel approach to estimate the cost-of-illness in Europe. IMPLICATIONS FOR HEALTH CARE PROVISION AND POLICIES: Health and social care policy and commissioning must be evidence-based. The empirical results from this study confirm previous findings, that depression is a major concern to the economic welfare in Europe which has consequences to both healthcare providers and policy makers. One important way to stop this explosion in cost is through increased research efforts in the field. Moreover, better detection, prevention, treatment and patient management are imperatives to reduce the burden of depression and its costs. Mental healthcare policies and better access to healthcare for mentally ill are other challenges to improve for Europe. Implications for further research This study has identified several research gaps which are of interest for future research. In order to better understand the impact of depression to European society long-term prospective epidemiology and cost-of-illness studies are needed. In particular data is lacking for Central European countries. On the basis of our findings, further economic evaluations of treatments for depression are necessary in order to ensure a cost-effective use of European healthcare budgets.

The impact of depression on the academic productivity of university students.

Abstract: Background: Depression is a common disorder that impacts an individual’s ability to perform life activities, including those required by the workplace. Academic performance can be viewed as a direct parallel to workforce performance, with students belonging to a unique set of individuals whose ability to perform can be measured on criteria applied by an observer and by self-report. While the prevalence of depression for this group is high and preparation for entry into the workplace is critical for these individuals, this relationship has not been adequately investigated. Aims of the Study: This study investigates the relationship between depression and its treatments and the academic performance of undergraduate students. Methods: Data regarding academics, health and productivity for students from Western Michigan University were obtained from the University’s Registrar’s Office, the campus Health Center and a survey delivered to the students. The primary outcomes of interest were the student’s grade point average (GPA), an objective, observer generated measure of academic productivity, and the students’ self-reported academic performance. Results: Diagnosed depression was associated with a 0.49 point, or half a letter grade, decrease in student GPA, while treatment was associated with a protective effect of approximately 0.44 points. The self-reported data regarding the impact of depression on the performance of academic tasks was consistent with these findings. Depressed students reported a pattern of increasing interference of depression symptoms with academic performance peaking in the month of diagnosis and decreasing thereafter with the lowest levels reported in months 4 through 6 post-diagnosis, each of which is significantly less than the month of diagnosis. Discussion: The finding of a significant relationship between depression and academic performance was robust to the variety of analyses employed within this study. However, interpretation of the findings must be tempered by a number of facts. The sample was drawn from a subset of students at a single university, those willing to complete a questionnaire regarding their health and productivity. Due to non-availability of the treatment data from other health care providers, the treatment variable used within the regression models represents an imprecise proxy for the totality of treatment methods received by depressed subjects from a variety of on-campus and offcampus health care providers. Another challenge to the interpretation of this data is the interrelatedness of depression and school performance. Because of this, it was not possible to evaluate the extent to which the association between depression and academic performance is driven by causality in either direction. Implications for Health Care Provision and Use: While depression and its effects have been studied in many different population groups and subgroups, the effect of this disease on college students has not been well documented. This research demonstrates the impact of depression and the effectiveness of its treatment on a student sample. From a public health perspective, this analysis highlights the importance of access to mental health treatment facilities among the college aged and the potential value of efforts to educate this population segment on the availability of that resource.

Costs of nine common mental disorders: Implications for curative and preventive psychiatry

Abstract: BACKGROUND: Mental disorders are highly prevalent and are associated with substantial disease burden, but their economic costs have been relatively less well researched. Moreover, few cost-of-illness studies used population-based psychiatric surveys for estimating direct medical, direct non-medical and indirect costs, and were able to do so for several well diagnosed mental disorders. AIMS: To calculate the cost of nine common mental disorders. The costs were calculated at individual level (per capita costs), and at population level per one million population for both prevalence (current cases) and incidence (new cases). METHOD: Data were derived from the Netherlands Mental Health Survey and Incidence Study (Nemesis), a population-based psychiatric cohort study among 5,504 adults in the age bracket of 18-65 years. DSM-III-R disorders were assessed with help of the Composite International Diagnostic Interview (CIDI). The costs of health service uptake, patients' out-of-pocket costs, and production losses were calculated for the reference year 2003. Robust regression methods, with 1,000 bootstrap replications, were used to estimate the excess costs of the distinct mental disorders and their 95% confidence intervals, while adjusting for physical illnesses and concurrent mental disorders in the regression equation. RESULTS: The annual per capita excess costs of the mood disorders (5,009 euros) were higher than those of the anxiety disorders (3,587 euros) and alcohol-related disorders (1,431 euros). Being more prevalent, the excess costs of anxiety disorders are higher than those of mood disorders at population level. The annual influx of new cases (incidence) accounts for 39.2% of the costs at population level. It appeared that in the general population, in the productive age of 18-65 years, the bulk of the costs (85%) were related to production losses. DISCUSSION: The study has some strengths and limitations. The data were derived from a large and representative population-based sample. Disorders were assessed with a reliable instrument. The costs were comprehensive in that they included direct medical, direct non-medical and indirect costs. The costs attributable to mental disorders were obtained with robust regression models while adjusting for the presence of somatic illnesses. For several reasons the costs figures must be seen as conservative lower bounds of the true costs. (i) People who were hospitalised were likely to be underrepresented in the sample, and it is well known that hospitalisation is one of the major cost drivers. (ii) Resource use was based on self-report, and this is likely to have resulted in underreporting. (iii) Work loss days were included in the analysis, but work cutback data were unavailable, while it is known that the costs due to work cutback can be substantial. IMPLICATIONS: (i) The costs of mental disorders are comparable to those of physical illnesses. This throws some light on the allocation of budgets for research and development in mental versus physical illnesses. (ii) At population level a substantial part of the costs are caused by new cases, and this is a strong argument for strengthening the role of preventive psychiatry in public health with the aim to reduce incidence and avoid the future costs. (iii) In particular, reducing the incidence of major depression, panic disorder, agoraphobia and dysthymia should be considered as public health priorities, because these disorders are associated with substantial disability, and have, in addition, important economic ramifications. (iv) The bulk of the costs are due to production losses; this makes employers pertinent stakeholders in mental health promotion, and thoughts should be given to the question how to involve them more actively in health promotion. (v) It is well to emphasise that adoption of the above mentioned policies will require that first more prevention trials and cost-effectiveness studies are conducted in the selected disorders.

Cost of schizophrenia in England

Abstract: Background: Despite the wide-ranging financial and social burdens associated with schizophrenia, there have been few cost-of-illness studies of this illness in the UK. Aims of the Study: To provide up-to-date, prevalence based estimate of all costs associated with schizophrenia for England. Methods: A bottom-up approach was adopted. Separate cost estimates were made for people living in private households, institutions, prisons and for those who are homeless. The costs included related to: health and social care, informal care, private expenditures, lost productivity, premature mortality, criminal justice services and other public expenditures such as those by the social security system. Data came from many sources, including the UKSCAP (Schizophrenia Care and Assessment Program) survey, Psychiatric Morbidity Surveys, Department of Health and government publications. Results: The estimated total societal cost of schizophrenia was £6.7 billion in 2004/05. The direct cost of treatment and care that falls on the public purse was about £2 billion; the burden of indirect costs to the society was huge, amounting to nearly £4.7 billion. Cost of informal care and private expenditures borne by families was £615 million. The cost of lost productivity due to unemployment, absence from work and premature mortality of patients was £3.4 billion. The cost of lost productivity of carers was £32 million. Estimated cost to the criminal justice system was about £1 million. It is estimated that about £570 million will be paid out in benefit payments and the cost of administration associated with this is about £ 14 million. Discussion: It is difficult to compare estimates from previous costof-illness studies due to differences in the methods, scope of analyses and the range of costs covered. Costs estimated in this study are detailed, cover a comprehensive list of relevant items and allow for different levels of disaggregation. The main limitation of the study is that data came from a variety of secondary sources and some official data publicly available was not the latest. Implications for Health Care Provision: Schizophrenia continues to be a high cost illness because of the range of range of health needs that people have. Despite the shifting balance of care away from hospital-based care, the health care costs of treating and supporting people with schizophrenia remain high. Implications for Health Policies: Decision-makers need to recognise the breadth of economic impacts, well beyond the health system as conventionally defined. For example, as nearly 80% of schizophrenia patients remain unemployed, the cost of lost productivity is especially large. Implications for Further Research: Better measurement of criminal justice services costs, private expenditures borne by families and valuation of lost quality of life could improve the estimates further.

Lost productivity among full-time workers with mental disorders.

Abstract: BACKGROUND: Few studies have systematically compared the relationship between lost work productivity (work impairment) and mental disorders using population surveys. AIMS: (1) To identify the importance of individual mental disorders and disorder co-occurrences (comorbidity) as predictors of two measures of work impairment over the past month - work loss (number of days unable to perform usual activities) and work cutback (number of days where usual activities were restricted); (2) to examine whether different types of disorder have a greater impact on work impairment in some occupations than others; (3) to determine whether work impairment in those with a disorder is related to treatment seeking. METHOD: Data were based on full-time workers identified by the Australian National Survey of Mental Health and Well-Being, a household survey of mental disorders modeled on the US National Comorbidity Survey. Diagnoses were of one-month DSM-IV affective, anxiety and substance-related disorders. Screening instruments generated likely cases of ICD-10 personality disorders. The association of disorder types and their co-occurrences with work impairment was examined using multivariate linear regression. Odds ratios determined the significance of mental disorder prevalence across occupations, and planned contrasts were used to test for differences in work impairment across occupations within disorder types. The relationship between work impairment and treatment seeking was determined for each broad diagnostic group with t-tests. RESULTS: Depression, generalized anxiety disorder and personality disorders were predictive of work impairment after controlling for impairment due to physical disorders. Among pure and comorbid disorders, affective and comorbid anxiety-affective disorders respectively were associated with the greatest amount of work impairment. For all disorders, stronger associations were obtained for work cutback than for work loss. No relationship was found between type of occupation and the impact of different types of disorder on work impairment. Only 15% of people with any mental disorder had sought help in the past month. For any mental disorder, significantly greater work loss and work cutback was associated with treatment seeking, but comparisons within specific disorder types were not significant. DISCUSSION: A substantial amount of lost productivity due to mental disorders comes from within the full-time working population. The greater impact of mental disorders on work cutback compared to work loss suggests that work cutback provides a more sensitive measure of work impairment in those with mental disorders. Work impairment was based on self-report only. While there is evidence for the reliability of self-assessed work loss days, no reliability or validity studies have been conducted for work cutback days. The low rates of treatment seeking are a major health issue for the workforce, particularly for affective and anxiety disorders, which are important predictors of lost productivity. IMPLICATIONS FOR HEALTH POLICIES AND FURTHER RESEARCH: Future research should investigate the validity of work cutback, given its importance as a measure of lost productivity in people with mental disorders. Employers need to be aware of the extent to which mental disorders affect their employees so that effective work place interventions can take place. Treatment should be targeted at people with affective and anxiety disorders, particularly where they co-occur.