Cost utility analysis of maintenance treatment for recurrent depression

Distinct resting-state effective connectivity of large-scale networks in first-episode and recurrent major depression disorder: evidence from the REST-meta-MDD consortium

Introduction

Previous studies have shown disrupted effective connectivity in the large-scale brain networks of individuals with major depressive disorder (MDD). However, it is unclear whether these changes differ between first-episode drug-naive MDD (FEDN-MDD) and recurrent MDD (R-MDD).

Methods

This study utilized resting-state fMRI data from 17 sites in the Chinese REST-meta-MDD project, consisting of 839 patients with MDD and 788 normal controls (NCs). All data was preprocessed using a standardized protocol. Then, we performed a granger causality analysis to calculate the effectivity connectivity (EC) within and between brain networks for each participant, and compared the differences between the groups.

Results

Our findings revealed that R-MDD exhibited increased EC in the fronto-parietal network (FPN) and decreased EC in the cerebellum network, while FEDN-MDD demonstrated increased EC from the sensorimotor network (SMN) to the FPN compared with the NCs. Importantly, the two MDD subgroups displayed significant differences in EC within the FPN and between the SMN and visual network. Moreover, the EC from the cingulo-opercular network to the SMN showed a significant negative correlation with the Hamilton Rating Scale for Depression (HAMD) score in the FEDN-MDD group.

Conclusion

These findings suggest that first-episode and recurrent MDD have distinct effects on the effective connectivity in large-scale brain networks, which could be potential neural mechanisms underlying their different clinical manifestations.

Altered functional connectivity in first-episode and recurrent depression: A resting-state functional magnetic resonance imaging study

Background

Functional magnetic resonance imaging (fMRI) studies examining differences in the activity of brain networks between the first depressive episode (FDE) and recurrent depressive episode (RDE) are limited. The current study observed and compared the altered functional connectivity (FC) characteristics in the default mode network (DMN), cognitive control network (CCN), and affective network (AN) between the RDE and FDE. In addition, we further investigated the correlation between abnormal FC and clinical symptoms.

Methods

We recruited 32 patients with the RDE, 31 patients with the FDE, and 30 healthy controls (HCs). All subjects underwent resting-state fMRI. The seed-based FC method was used to analyze the abnormal brain networks in the DMN, CCN, and AN among the three groups and further explore the correlation between abnormal FC and clinical symptoms.

Results

One-way analysis of variance showed significant differences the FC in the DMN, CCN, and AN among the three groups in the frontal, parietal, temporal, and precuneus lobes and cerebellum. Compared with the RDE group, the FDE group generally showed reduced FC in the DMN, CCN, and AN. Compared with the HC group, the FDE group showed reduced FC in the DMN, CCN, and AN, while the RDE group showed reduced FC only in the DMN and AN. Moreover, the FC in the left posterior cingulate cortices and the right inferior temporal gyrus in the RDE group were positively correlated with the 17-item Hamilton Rating Scale for Depression (HAMD-17), and the FC in the left dorsolateral prefrontal cortices and the right precuneus in the FDE group were negatively correlated with the HAMD-17.

Conclusions

The RDE and FDE groups showed multiple abnormal brain networks. However, the alterations of abnormal FC were more extensive and intensive in the FDE group.

Trajectories of relapse in randomised, placebo-controlled trials of treatment discontinuation in major depressive disorder: an individual patient-level data meta-analysis

BACKGROUND

Understanding patterns of relapse in patients who respond to antidepressant treatment can inform strategies for prevention of relapse. We aimed to identify distinct trajectories of depression severity, assess whether similar or different trajectory classes exist for patients who continued or discontinued active treatment, and test whether clinical predictors of trajectory class membership exist using pooled data from clinical trials.

METHODS

We analysed individual patient data from four double-blind discontinuation clinical trials of duloxetine or fluoxetine versus placebo in major depression from before 2012 (n=1462). We modelled trajectories of relapse up to 26 weeks during double-blind treatment. Trajectories of depression severity, as measured by the Hamilton Depression Rating Scale score, were identified in the entire sample, and separately in groups in which antidepressants had been continued or discontinued, using growth mixture models. Predictors of trajectory class membership were assessed with weighted logistic regression.

FINDINGS

We identified similar relapse trajectories and two trajectories of stable depression scores in the normal range on active medication and on placebo. Active treatment significantly lowered the odds of membership in the relapse trajectory (odds ratio 0·47, 95% CI 0·37-0·61), whereas female sex (1·56, 1·23-2·06), shorter length of time with clinical response by 1 week (1·10, 1·06-1·15), and higher Clinical Global Impression score at baseline (1·28, 1·01-1·62) increased the odds. Overall, the protective effect of antidepressant medication relative to placebo on the risk of being classified as a relapser was about 13% (33% vs 46%).

INTERPRETATION

The existence of similar relapse trajectories on active medication and on placebo suggests that there is no specific relapse signature associated with antidepressant discontinuation. Furthermore, continued treatment offers only modest protection against relapse. These data highlight the need to incorporate treatment strategies that prevent relapse as part of the treatment of depression.

FUNDING

National Institutes of Health, the US Department of Veterans Affairs Alcohol Research Center, and National Center for Post-Traumatic Stress Disorder.

A critical review of model-based economic studies of depression: modelling techniques, model structure and data sources

Depression is the most common mental health disorder and is recognized as a chronic disease characterized by multiple acute episodes/relapses. Although modelling techniques play an increasingly important role in the economic evaluation of depression interventions, comparatively little attention has been paid to issues around modelling studies with a focus on potential biases. This, however, is important as different modelling approaches, variations in model structure and input parameters may produce different results, and hence different policy decisions. This paper presents a critical review of literature on recently published model-based cost-utility studies of depression. Taking depression as an illustrative example, through this review, we discuss a number of specific issues in relation to the use of decision-analytic models including the type of modelling techniques, structure of models and data sources. The potential benefits and limitations of each modelling technique are discussed and factors influencing the choice of modelling techniques are addressed. This review found that model-based studies of depression used various simulation techniques. We note that a discrete-event simulation may be the preferred technique for the economic evaluation of depression due to the greater flexibility with respect to handling time compared with other individual-based modelling techniques. Considering prognosis and management of depression, the structure of the reviewed models are discussed. We argue that a few reviewed models did not include some important structural aspects such as the possibility of relapse or the increased risk of suicide in patients with depression. Finally, the appropriateness of data sources used to estimate input parameters with a focus on transition probabilities is addressed. We argue that the above issues can potentially bias results and reduce the comparability of economic evaluations.

Cost-effectiveness of transcranial magnetic stimulation in the treatment of major depression: a health economics analysis

INTRODUCTION

Transcranial magnetic stimulation (TMS) is a novel antidepressant therapy shown to be effective and safe in pharmacotherapy-resistant major depression. The incremental cost-effectiveness and the direct cost burden compared with sham treatment were estimated, and compared with the current standard of care.

METHODS

Healthcare resource utilization data were collected during a multicenter study (n=301) and a decision analysis was used to stratify the 9-week treatment outcomes. A Markov model with an acute-outcome severity-based risk of relapse was used to estimate the illness course over a full year of treatment follow-up. These model estimates were also compared to best estimates of outcomes and costs of pharmacotherapy treatment, using the published STAR(*)D outcomes. The cost-effectiveness of TMS was described using an incremental cost-effectiveness ratio (ICER) per quality-adjusted life year (QALY) gained and on a direct cost per patient basis across a varying range of assumptions. The model's sensitivities to costs due to losses in work productivity and to caregiver time were also examined.

RESULTS

Compared with sham treatment and at a cost of US$300 per treatment session, TMS provides an ICER of US$34,999 per QALY, which is less than the "willingness-to-pay' standard of US$50,000 per QALY for a new treatment for major depression. When productivity gains due to clinical recovery were included, the ICER was reduced to US$6667 per QALY. In open-label conditions, TMS provided a net cost saving of US$1123 per QALY when compared with the current standard of care. In the openlabel condition, cost savings increased further when the costs for productivity losses were included in the model (net savings of US$7621). The overall cost benefits of treating MD using TMS were greater in those patients at the earliest levels of treatment resistance in the overall sample.

CONCLUSION

TMS is a cost-effective treatment for patients who have failed to receive sufficient benefit from initial antidepressant pharmacotherapy. When used at earlier levels of treatment resistance, significant cost savings may be expected relative to the current standard of care.

Fluoxetine and imipramine: are there differences in cost-utility for depression in primary care?

RATIONALE

Depressive disorders generate severe personal burden and high economic costs. Cost-utility analyses of the different therapeutical options are crucial to policy-makers and clinicians. Previous cost-utility studies, comparing selective serotonin reuptake inhibitors and tricyclic antidepressants, have used modelling techniques or have not included indirect costs in the economic analyses.

OBJECTIVE

To determine the cost-utility of fluoxetine compared with imipramine for treating depressive disorders in primary care.

METHODS

A 6-month randomized prospective naturalistic study comparing fluoxetine with imipramine was conducted in three primary care centres in Spain. One hundred and three patients requiring antidepressant treatment for a DSM-IV depressive disorder were included in the study. Patients were randomized either to fluoxetine (53 patients) or to imipramine (50 patients) treatment. Patients were treated with antidepressants according to their general practitioner's usual clinical practice. Outcome measures were the quality of life tariff of the European Quality of Life Questionnaire: EuroQoL-5D (five domains), direct costs, indirect costs and total costs. Subjects were evaluated at the beginning of treatment and after 1, 3 and 6 months. Incremental cost-utility ratios (ICUR) were obtained. To address uncertainty in the ICUR's sampling distribution, non-parametric bootstrapping was carried out.

RESULTS

Taking into account adjusted total costs and incremental quality of life gained, imipramine dominated fluoxetine with 81.5% of the bootstrap replications in the dominance quadrant.

CONCLUSION

Imipramine seems to be a better cost-utility antidepressant option for treating depressive disorders in primary care.

The health value and cost of care for major depression

BACKGROUND

Trade-offs between costs and outcomes are a reality of health-care decisions. Cost-effectiveness analyses can guide choices toward interventions with the most health benefit for the least cost but are limited because generic measures of health value are infrequently available in the literature and are expensive to collect.

OBJECTIVE

We report on the application of a new approach to estimate the health value of alternative treatment patterns. We apply this approach to common treatment patterns for major depression, and we generate estimates of the change in health value that is attributable to a particular treatment. We also obtain estimates of treatment costs and report cost/health value ratios. We used a modified expert panel approach to estimate the change in health value attributable to different patterns of treatment. We used claims and pharmacy data to define usual care treatment patterns and estimate costs.

RESULTS

The lowest cost and most frequent treatment, 1 to 3 psychotherapy visits, produces minimal improvement. Treatments that include an antidepressant medication provide more health benefit per unit cost than all other treatments and adding a medication follow-up visit provides a lot of benefit for minimal cost.

CONCLUSIONS

We demonstrate the application of a new approach to estimate the health value of common depression treatment practices in the United States. Our results suggest cost-effective targets for quality improvement efforts by identifying ways in which treatment for depression could cost less to get to a given outcome. Because our approach uses a generic health outcome measure, it can be applied to other conditions, permitting comparisons of benefit across diseases.

The cost-utility of maintenance treatment with venlafaxine in patients with recurrent major depressive disorder

AIMS

The Prevention of Recurrent Episodes of Depression with venlafaxine XR for Two Years trial has reported advantages with maintenance treatment for patients with recurrent depressive disorder. The aim of this study was to assess the cost-utility of maintenance treatment with venlafaxine in patients with recurrent major depressive disorder, based on a recent clinical trial.

METHODS

A Markov simulation model was constructed to assess the cost-utility of maintenance treatment for 2 years in recurrently depressed patients in Sweden. Risk of relapse and recurrence was based on a recent randomised clinical trial assessing the efficacy and tolerability of maintenance treatment with venlafaxine over 2 years. Costs and quality of life estimations were retrieved from a naturalistic longitudinal observational study conducted in Sweden. Health effects were quantified as quality-adjusted life-years (QALYs). Sensitivity analyses were conducted on key parameters employed in the model.

RESULTS

In the base-case analysis, the cost per QALY gained of venlafaxine compared with no treatment was estimated at $18,500 over 2 years. In a probabilistic sensitivity analysis, we found that maintenance treatment with venlafaxine is cost-effective with 90% probability at a willingness to pay per QALY of $67,000 or less. Our long-term analyses also indicate that even under conservative assumptions about future risks of recurrences, maintenance treatment is cost-effective.

CONCLUSION

The present study indicates that maintenance treatment for 2 years with venlafaxine is cost-effective in patients with recurrent major depressive disorder.

Can discrete event simulation be of use in modelling major depression?

BACKGROUND

Depression is among the major contributors to worldwide disease burden and adequate modelling requires a framework designed to depict real world disease progression as well as its economic implications as closely as possible.

OBJECTIVES

In light of the specific characteristics associated with depression (multiple episodes at varying intervals, impact of disease history on course of illness, sociodemographic factors), our aim was to clarify to what extent "Discrete Event Simulation" (DES) models provide methodological benefits in depicting disease evolution.

METHODS

We conducted a comprehensive review of published Markov models in depression and identified potential limits to their methodology. A model based on DES principles was developed to investigate the benefits and drawbacks of this simulation method compared with Markov modelling techniques.

RESULTS

The major drawback to Markov models is that they may not be suitable to tracking patients' disease history properly, unless the analyst defines multiple health states, which may lead to intractable situations. They are also too rigid to take into consideration multiple patient-specific sociodemographic characteristics in a single model. To do so would also require defining multiple health states which would render the analysis entirely too complex. We show that DES resolve these weaknesses and that its flexibility allow patients with differing attributes to move from one event to another in sequential order while simultaneously taking into account important risk factors such as age, gender, disease history and patients attitude towards treatment, together with any disease-related events (adverse events, suicide attempt etc.).

CONCLUSION

DES modelling appears to be an accurate, flexible and comprehensive means of depicting disease progression compared with conventional simulation methodologies. Its use in analysing recurrent and chronic diseases appears particularly useful compared with Markov processes.

Cost-utility of selective serotonin reuptake inhibitors for depression in primary care in Catalonia

OBJECTIVE

To determine the cost-utility of selective serotonin reuptake inhibitors (SSRIs) for treating depressive disorders prescribed in primary care (PC).

METHOD

A total of 301 participants beginning antidepressant treatment with an SSRI were enrolled in a prospective 6-month follow-up naturalistic study. Incremental cost-utility ratios (ICUR) were obtained for several comparisons among different SSRIs. To address uncertainty in the ICUR's sampling distribution, non-parametric bootstrapping was carried out.

RESULTS

Taking into account adjusted total costs and incremental quality of life gained, fluoxetine dominated paroxetine and citalopram with 63.4% and 79.3% of the bootstrap replications in the dominance quadrant, respectively. Additionally, fluoxetine was cost-effective over sertraline with 83.4% of the bootstrap replications below the threshold of 33,936 US$/quality-adjusted life year (30,000 euro/QALY).

CONCLUSION

Fluoxetine seems to be a better cost-utility SSRI option for treating depressive disorders in PC.

An unadjusted NNT was a moderately good predictor of health benefit

BACKGROUND AND OBJECTIVE

Whether the number needed to treat (NNT) is sufficiently precise to use in clinical practice remains unclear. We compared unadjusted NNTs to quality-adjusted life years (QALYs) gained, a more comprehensive measures of health benefit.

STUDY DESIGN AND SETTING

From a subset (n = 65) of a dataset of 228 cost-effectiveness analyses, we compared how well NNTs predicted clinically important QALY gains using correlation analysis, multivariable models and receiver-operator curve (ROC) analysis.

RESULTS

NNT was inversely correlated with QALY gains (P < .001); this relationship was affected by quality of life and life-expectancy gains of treatment (P <or= .04). The NNT is a moderately accurate predictor of treatments that provide large health benefits (area under ROC 0.74-0.81). For ruling out therapies with low QALY gains (threshold <or=0.125 to <or=0.5 QALYs), an NNT >15 had a sensitivity of 82% to 100%. For ruling in therapies with high QALY gains (threshold >or=0.125 to >or=0.5 QALYs), an NNT <or=5 had a specificity of 77%.

CONCLUSION

Using NNT thresholds of <or=5 and >15 to rule in and out therapies with large QALY gains may provide general guidance regarding the magnitude of health benefit.

Benefits and costs of methadone treatment: results from a lifetime simulation model

Several studies have examined the benefits and costs of drug treatment; however, they have typically focused on the benefits and costs of a single treatment episode. Although beneficial for certain analyses, the results are limited because they implicitly treat drug abuse as an acute problem that can be treated in one episode. We developed a Monte Carlo simulation model that incorporates the chronic nature of drug abuse. Our model represents the progression of individuals from the general population aged 18-60 with respect to their heroin use, treatment for heroin use, criminal behavior, employment, and health care use. We also present three model scenarios representing an increase in the probability of going to treatment, an increase in the treatment length of stay, and a scenario in which drug treatment is not available to evaluate how changes in treatment parameters affect model results. We find that the benefit-cost ratio of treatment from our lifetime model (37.72) exceeds the benefit-cost ratio from a static model (4.86). The model provides a rich characterization of the dynamics of heroin use and captures the notion of heroin use as a chronic recurring condition. Similar models can be developed for other chronic diseases, such as diabetes, mental illness, or cardiovascular disease.

Evidence of cost-effective treatments for depression: a systematic review

BACKGROUND

High levels of public spending, rising costs of treatments and scarcity of mental health resources have intensified the need for information on the cost-effectiveness of interventions for depression. There have been few reviews that consider the cost-effectiveness of all treatments for depression together.

METHODS

Systematic review of published economic evaluations of interventions for depression to identify where evidence of cost-effectiveness exists and where ambiguity remains.

RESULTS

Fifty-eight papers met the criteria and were included in the review. The quality of the evaluations varied greatly. Evidence establishing the cost-effectiveness of interventions for depression is accumulating; selective serotonin reuptake inhibitors (SSRI) and the newer antidepressants venlafaxine, mirtazepine and nefazodone appear cost-effective compared with older drugs. Despite the availability of high quality economic evaluations of psychological therapies compared to usual care, there is limited evidence of their cost-effectiveness particularly when compared directly to pharmacotherapies. Changes to health systems have been found to be cost-effective in some patient groups, but there is no evidence that screening in primary care populations is a cost-effective strategy.

LIMITATIONS

Vastly different interventions, outcome measures and cost perspectives meant a meta-analysis of costs and effects was not considered possible.

CONCLUSIONS

On the basis of available evidence, it is not possible to identify the most cost-effective strategy for alleviating the symptoms of depression, although the SSRIs and newer antidepressants consistently appear more cost-effective than tricyclic antidepressants in many patient groups. Better quality economic evidence is needed.

Using the effect size to model change in preference values from descriptive health status

OBJECTIVES

This pilot study describes a modelling approach to translate group-level changes in health status into changes in preference values, by using the effect size (ES) to summarize group-level improvement.

METHODS

ESs are the standardized mean difference between treatment groups in standard deviation (SD) units. Vignettes depicting varying severity in SD decrements on the SF-12 mental health summary scale, with corresponding symptom severity profiles, were valued by a convenience sample of general practitioners (n = 42) using the rating scale (RS) and time trade-off methods. Translation factors between ES differences and change in preference value were developed for five mental disorders, such that ES from published meta-analyses could be transformed into predicted changes in preference values.

RESULTS

An ES difference in health status was associated with an average 0.171-0.204 difference in preference value using the RS, and 0.104-0.158 using the time trade off.

CONCLUSIONS

This observed relationship may be particular to the specific versions of the measures employed in the present study. With further development using different raters and preference measures, this approach may expand the evidence base available for modelling preference change for economic analyses from existing data.

Cost-effectiveness of a primary care depression intervention

OBJECTIVE

To determine the incremental cost-effectiveness of a quality improvement depression intervention (enhanced care) in primary care settings relative to usual care.

DESIGN

Following stratification, we randomized 12 primary care practices to enhanced or usual care conditions and followed patients for 12 months.

SETTING

Primary care practices located in 10 states across the United States.

PATIENTS/PARTICIPANTS

Two hundred eleven patients beginning a new treatment episode for major depression.

INTERVENTIONS

Training the primary care team to assess, educate, and monitor depressed patients during the acute and continuation stages of their depression treatment episode over 1 year.

MEASUREMENTS AND MAIN RESULTS

Cost-effectiveness was measured by calculating incremental (enhanced minus usual care) costs and quality-adjusted life years (QALYs) derived from SF-36 data. The mean incremental cost-effectiveness ratio in the main analysis was US dollars 15463 per QALY. The mean incremental cost-effectiveness ratios for the sensitivity analyses ranged from US dollars 11341 (using geographic block variables to control for pre-intervention service utilization) to US dollars 19976 (increasing the cost estimates by 50%) per QALY.

CONCLUSIONS

This quality improvement depression intervention was cost-effective relative to usual care compared to cost-effectiveness ratios for common primary care interventions and commonly cited cost-effectiveness ratio thresholds for intervention implementation.

Health care economic analyses and value-based medicine

Health care economic analyses are becoming increasingly important in the evaluation of health care interventions, including many within ophthalmology. Encompassed with the realm of health care economic studies are cost-benefit analysis, cost-effectiveness analysis, cost-minimization analysis, and cost-utility analysis. Cost-utility analysis is the most sophisticated form of economic analysis and typically incorporates utility values. Utility values measure the preference for a health state and range from 0.0 (death) to 1.0 (perfect health). When the change in utility measures conferred by a health care intervention is multiplied by the duration of the benefit, the number of quality-adjusted life-years (QALYs) gained from the intervention is ascertained. This methodology incorporates both the improvement in quality of life and/or length of life, or the value, occurring as a result of the intervention. This improvement in value can then be amalgamated with discounted costs to yield expenditures per quality-adjusted life-year ($/QALY) gained. $/QALY gained is a measure that allows a comparison of the patient-perceived value of virtually all health care interventions for the dollars expended. A review of the literature on health care economic analyses, with particular emphasis on cost-utility analysis, is included in the present review. It is anticipated that cost-utility analysis will play a major role in health care within the coming decade.

Do HEDIS measures reflect cost-effective practices?

PURPOSE

Whether the Health Plan Employer Data and Information Set (HEDIS) performance measures for managed care plans encourage a cost-effective use of society's resources has not been quantified. Our study objectives were to examine the cost-effectiveness evidence for the clinical practices underlying HEDIS 2000 measures and to develop a list of practices not reflected in HEDIS that have evidence of cost effectiveness.

DATA SOURCES

Two databases of economic evaluations (Harvard School of Public Health Cost-Utility Registry and the Health Economics Evaluation Database) and two published lists of cost-effectiveness ratios in health and medicine.

STUDY SELECTION

For each of the 15 "effectiveness of care" measures in HEDIS 2000, we searched the data through 1998 for cost-effectiveness ratios of similar interventions and target populations. We also searched for important interventions with evidence of cost-effectiveness (<$20,000 per life-year [LY] or quality-adjusted life year [QALY] gained), which are not included in HEDIS. All ratios were standardized to 1998 dollars. The data were collected and analyzed during fall 2000 to summer 2001.

DATA EXTRACTION

Cost-effectiveness ratios reporting outcomes in terms of cost/LY or cost/QALY gained were included if they matched the intervention and population covered by the HEDIS measure.

DATA SYNTHESIS

Evidence was available for 11 of the 15 HEDIS measures. Cost-effectiveness ranges from cost saving to $660,000/LY gained. There are numerous non-HEDIS interventions with some evidence of cost effectiveness, particularly interventions to promote healthy behaviors.

CONCLUSIONS

HEDIS measures generally reflect cost-effective practices; however, in a number of cases, practices may not be cost effective for certain subgroups. Data quality and availability as well as study perspective remain key challenges in judging cost effectiveness. Opportunities exist to refine existing measures and to develop additional measures, which may promote a more efficient use of societal resources, although more research is needed on whether these measures would also satisfy other desirable attributes of HEDIS.

Cost-effectiveness of a program to prevent depression relapse in primary care

OBJECTIVE

Evaluate the incremental cost-effectiveness of a depression relapse prevention program in primary care.

MATERIALS AND METHODS

Primary care patients initiating antidepressant treatment completed a standardized telephone assessment 6-8 weeks later. Those recovered from the current episode but at high risk for relapse (based on history of recurrent depression or dysthymia) were offered randomization to usual care or a relapse prevention intervention. The intervention included systematic patient education, two psychoeducational visits with a depression prevention specialist, shared decision-making regarding maintenance pharmacotherapy, and telephone and mail monitoring of medication adherence and depressive symptoms. Outcomes in both groups were assessed via blinded telephone assessments at 3, 6, 9, and 12 months and health plan claims and accounting data.

RESULTS

Intervention patients experienced 13.9 additional depression-free days during a 12-month period (95% CI, -1.5 to 29.3). Incremental costs of the intervention were $273 (95% CI, $102 to $418) for depression treatment costs only and $160 (95% CI, -$173 to $512) for total outpatient costs. Incremental cost-effectiveness ratio was $24 per depression-free day (95% CI, -$59 to $496) for depression treatment costs only and $14 per depression-free day (95% CI, -$35 to $248) for total outpatient costs.

CONCLUSIONS

A program to prevent depression relapse in primary care yields modest increases in days free of depression and modest increases in treatment costs. These modest differences reflect high rates of treatment in usual care. Along with other recent studies, these findings suggest that improved care of depression in primary care is a prudent investment of health care resources.

Assessment of clinical guidelines for continuation treatment in major depression

OBJECTIVE

The primary objective of this study was to assess the appropriateness of the existing Dutch clinical guidelines for the treatment of depression from a health-economic perspective. The existing guidelines recommend continuation treatment for a period up to 9 months.

METHODS

The assessment was based on a Markov model using decision-analytic techniques. For this analysis we defined six mutually exclusive states defined by the existence of depression and type of treatment. The outcomes for the model were defined as: time without depression (TWD), quality-adjusted life years (QALYs), direct medical costs, and cost of lost productivity. The primary perspective of the study was that of the third-party payer, while the secondary perspective was that of the society in 1999. The probabilities of clinical events and therapeutic choices as well as the utilities were based on published literature. The medical resource use related to each state was abstracted from published literature and expert opinion. The associated 1999 unit costs of the used medical resources were derived from official Dutch tariff lists of allowable reimbursements. Indirect costs in this model were based on lost productivity only.

RESULTS

The results of the primary analysis showed that the use of the guidelines is not cost-effective. Continuation treatment for a period of 9 months increases the total direct medical costs (NLG 1276 vs. NLG 474), decreases the costs resulting from lost productivity (NLG 304 vs. NLG 909), increases total costs (NLG 1580 vs. NLG 1383) and increases TWD (96.9% vs. 86.4%). However, continuation treatment does not change the utility outcomes (0.60 vs. 0.61 QALYs) for both treatment strategies. Hence continuation treatment is not cost-effective from either a third-party payer perspective or a societal perspective. A scenario analysis showed that an extension of the continuation treatment to maintenance treatment might result in a favorable cost-effectiveness outcome of the treatment guideline.

CONCLUSION

In conclusion, based on the assumptions used in the model, the current Dutch treatment guidelines for depression are only appropriate from a health-economic perspective if continuation treatment is extended to maintenance treatment.

UPBEAT: the impact of a psychogeriatric intervention in VA medical centers. Unified Psychogeriatric Biopsychosocial Evaluation and Treatment

BACKGROUND

The Unified Psychogeriatric Biopsychosocial Evaluation and Treatment (UPBEAT) program provides individualized interdisciplinary mental health treatment and care coordination to elderly veterans whose comorbid depression, anxiety, or alcohol abuse may result in overuse of inpatient services and underuse of outpatient services.

OBJECTIVES

To determine whether proactive screening of hospitalized patients can identify unrecognized comorbid psychiatric conditions and whether comprehensive assessment and psychogeriatric intervention can improve care while reducing inpatient use.

DESIGN

Randomized trial.

SUBJECTS

Veterans aged 60 and older hospitalized for nonpsychiatric medical or surgical treatment in 9 VA sites (UPBEAT, 814; usual care, 873).

MEASURES

The Mental Health Inventory (MHI) anxiety and depression subscales, the Alcohol Use Disorder Identification Test (AUDIT) scores, RAND 36-Item Health Survey Short Form (SF-36), inpatient days and costs, ambulatory care clinic stops and costs, and mortality and readmission rates.

RESULTS

Mental health and general health status scores improved equally from baseline to 12-month follow-up in both groups. UPBEAT increased outpatient costs by $1,171 (P <0.001) per patient, but lowered inpatient costs by $3,027 (P = 0.017), for an overall savings of $1,856 (P = 0.156). Inpatient savings were attributable to fewer bed days of care (3.30 days; P = 0.016) rather than fewer admissions. Patients with 1 or more pre-enrollment and postenrollment hospitalizations had the greatest overall savings ($6,015; P = 0.069).

CONCLUSIONS

UPBEAT appears to accelerate the transition from inpatient to outpatient care for acute nonpsychiatric admissions. Care coordination and increased access to ambulatory psychiatric services produces similar improvement in mental health and general health status as usual care.

Antidepressant treatment for depression: total charges and therapy duration*

BACKGROUND: The economic costs of depression are significant, both the direct medical costs of care and the indirect costs of lost productivity. Empirical studies of antidepressant cost-effectiveness suggest that the use of selective serotonin reuptake inhibitors (SSRIs) may be no more costly than tricyclic antidepressants (TCAs), will improve tolerability, and is associated with longer therapy duration. However the success of depression care usually involves multiple factors, including source of care, type of care, and patient characteristics, in addition to drug choice. The cost-effective mix of antidepressant therapy components is unclear. AIMS OF THE STUDY: Our study evaluates cost and antidepressant-continuity outcomes for depressed patients receiving antidepressant therapy. Specifically, we determined the impact of provider choice for initial care, concurrent psychotherapy, and choice of SSRI versus TCA-based pharmacotherapies on the joint outcome of low treatment cost and continuous antidepressant therapy. METHODS: A database of private health insurance claims identifies 2678 patients who received both a diagnosis of depression and a prescription for an antidepressant during 1990-1994. Patients each fall into one of four groups according to whether their health care charges are high versus low (using the median value as the break point) and by whether their antidepressant usage pattern is continuous versus having discontinued pharmacotherapy early (filling fewer than six prescriptions). A bivariate probit model controlling for patient characteristics, co-morbidities, type of depression and concurrent treatment is the primary multivariate statistical vehicle for the cost-effective treatment situation. RESULTS: SSRIs substantially reduce the incidence of patients discontinuing pharmacotherapy while leaving charges largely unchanged. The relative effectiveness of SSRIs in depression treatment is independent of the patient's personal characteristics and dominates the consequences of other treatment dimensions such as seeing a mental health specialist and receiving concurrent psychotherapy. Initial provider specialty is irrelevant to the continuity of pharmacotherapy, and concurrent psychotherapy creates a tradeoff through reduced pharmacotherapy interruption with higher costs. DISCUSSION: Longer therapy duration is associated with SSRI-based pharmacotherapy (relative to TCA-based pharmacotherapy) and with concurrent psychotherapy. High cost is associated with concurrent psychotherapy and choice of a specialty provider for initial care. In our study cost-effective care includes SSRI-based pharmacotherapy initiated with a non-specialty provider. Previous treatment history and other unobserved factors that might affect antidepressant choice are not included in our model. IMPLICATIONS FOR HEALTH CARE PROVISION: The decision to use an SSRI-based pharmacotherapy need not consider carefully the patient's personal characteristics. Shifting depressed patients' pharmacotherapy away from TCAs to SSRIs has the effect of improving outcomes by lowering the incidence of discontinuation of pharmacotherapy while leaving largely unchanged the likelihood of having high overall health care charges. Targeted use of concurrent psychotherapy may be additionally cost-effective. IMPLICATIONS FOR HEALTH POLICIES: The interaction of various components of depression care can alter the cost-effectiveness of antidepressant therapy. Our results demonstrate a role for the non-specialty provider in initiating care and support increased use of SSRIs as first-line therapy for depression as a way of providing cost-effective care that is consistent with APA guidelines for continuous antidepressant treatment. IMPLICATIONS FOR FURTHER RESEARCH: Further research that improves our understanding of how decisions regarding provider choice, concurrent psychotherapy, and drug choice are made will improve our understanding of the effects treatment choices on the cost-effectiveness of depression care. We have suggested that targeted concurrent psychotherapy may prove to be cost-effective; research to determine groups most likely to benefit from the additional treatment would further enable clinicians and healthcare policy makers to form a consensus regarding a model for treating depression.

Cost effectiveness of acute imipramine therapy versus two imipramine maintenance treatment regimens for panic disorder

OBJECTIVE

To examine the medical costs and effectiveness of acute treatment with imipramine versus acute treatment plus 2 different maintenance therapies for panic disorder.

METHODS

A clinical decision model was constructed to estimate 18-month costs and outcomes associated with these treatment scenarios based on the medical literature and clinician judgment. The clinical parameters and outcomes for the model were derived from a series of systematic clinical trials with imipramine utilising uniform dosage procedures and validated response criteria. Costs were calculated based on standardised treatment regimens. The outcome measures were 18-month medical costs, quality-adjusted life years (QALYs) and costs per QALY gained. A sensitivity analysis was performed to explore the impact of treatment withdrawals on outcomes.

STUDY PERSPECTIVE

US mental healthcare system.

RESULTS

Over 18 months, the total costs (1997 values) and QALYs associated with half-dose maintenance therapy (imipramine 1.1 mg/kg/day) [$US3377; QALYs = 0.991] and full-dose maintenance therapy (imipramine 2.25 mg/kg/ day) [$US3361; QALYs = 0.991] were almost identical; both were cost saving compared with acute imipramine therapy (2.25 mg/kg/day) with no maintenance treatment ($US3691; QALYs = 0.979). Whether patients withdrawing from treatment were considered to have continued to respond to treatment or to have relapsed, the half-dose and full-dose maintenance treatments were still cost saving compared with acute treatment alone.

CONCLUSIONS

The results indicate that imipramine maintenance treatment is cost effective compared with acute imipramine treatment for patients with panic disorder. The basic findings and conclusions are not affected after modifying model assumptions for clinical response in patients withdrawing from treatment.

Are pharmaceuticals cost-effective? A review of the evidence

The argument that prescription drugs are cost-effective has been made both by the pharmaceutical industry to support rising drug prices and expenditures, and by advocates of expanded drug coverage for elderly and low-income persons. A new database of 228 published cost-utility analyses sheds light on the issue. According to published data, some drugs do save money or are cost-effective, but the issue depends critically on the context in which the drug is used and the intervention with which it is compared. Cost-utility analyses funded by the drug industry tend to report more favorable results than do those funded by nonindustry sources. Cost-effectiveness analysis can help policymakers to determine whether drugs and other interventions offer value for money.

The cost-effectiveness of substance abuse treatment

Researchers have estimated the cost of treating substance abuse and its effects on medical care and social service expenses, but have rarely used the methods developed to evaluate medical care interventions. When outcomes are expressed as quality-adjusted life years, substance abuse treatment may be compared with other types of health care. This method has found smoking cessation and methadone maintenance to be highly cost-effective health care programs.

Economic comparisons of the pharmacotherapy of depression: an overview

As many countries find that their health care expenditure is taking up an increasing proportion of their financial resources, economic aspects of care processes have become more important in the choice of optimal strategies. This review of the economic studies of the comparative treatment of depression shows that nearly every aspect of treatment has important economic consequences. Cost-of-illness studies have documented the high burden on society of this disorder, and the associated loss of productivity and work. Comparative cost-effectiveness/utility studies, the majority of which are based on modelling techniques, have consistently shown a better cost-effectiveness ratio of the newer antidepressants over more traditional tricyclic antidepressants (TCAs), when all therapy-related costs are taken into account.

Dollars may not buy as many QALYs as we think: a problem with defining quality-of-life adjustments

The scale of health state quality that should be used to compute quality-adjusted life years (QALYs) ranges from 0 (death) to 1.0 (excellent health); this is called the "Q" scale. But many cost-utility analyses (CUAs) in the literature use the upper anchor of the scale to denote only the absence of the particular health condition under investigation, and weight the disease state proportional to this endpoint; these are called "q" scales. Computations using q-scale health-state weights ignore the fact that the average patient is still subject to chronic and acute conditions comorbid with the condition being analyzed; the absence of a particular condition is not in general the same as excellent health, i.e., the Q scale is longer than a q scale. CUAs based on q scales yield "qALYs." Incremental $/qALY ratios are generally lower than $/QALY ratios; in the example presented, $/qALY must be inflated by about 15% to yield $/QALY. Other CUAs correctly weight disease states using the Q scale, but erroneously assign a quality weight of 1.0 to absence of the disease in the CUA computations. The results of such analyses are called "NP-QALYs," as the correction factor to compute QALYs is not a simple proportional adjustment. The authors suggest that analysis doing cost-utility analyses without access to primary data from treated patients use average age-specific health-related quality-of-life weights from population-based studies to represent the state of not having a particular disease. Consumers of CUAs should closely examine the nature of the QALYs in any published analyses before making decisions based on their results.

Approaches to measuring quality of life and their relevance to mental health

OBJECTIVES

This paper describes the 'sociological' and health-related approaches to the measurement of quality of life and aims to describe their major findings, shortcomings and potential uses with mental health problems.

METHOD

The literature is selectively reviewed to illustrate the major developments and conclusions.

RESULTS

Despite the lack of an accepted definition of quality of life, sociological approaches have repeatedly shown in general populations, the mentally ill and the elderly that subjective assessments are more influential in determining expressions of happiness, wellbeing and life satisfaction than are the objective circumstances of a person's life. This supports the use of subjective judgements as the basis for quality-of-life determinations..

CONCLUSIONS

The quality-of-life approaches can help to answer a broad range of questions of interest to psychiatry. Health-related quality-of-life approaches are potentially useful methods of demonstrating the impact of mental illness and the benefit of interventions. Further work is required to determine whether the commonly used measures are sensitive to change.

Statistical methods for cost-effectiveness analyses

A statistical framework is presented for examining cost and effect data on competing interventions obtained from an RCT or from an observational study. Parameters of the join distribution of costs and effects or a regression function linking costs and effects are used to define cost-effectiveness (c-e) measures. Several new c-e measures are proposed that utilize the linkage between costs and effects on the patient level. These measures reflect perspectives that are different from those of the commonly used measures, such as the ratio of expected cost to expected effect, and they can lead to different relative rankings of the interventions. The cost-effectiveness of interventions are assessed statistically in a two stage procedure that first eliminates clearly inferior interventions. Members of the remaining admissible set are then rank ordered according to a c-e preference measure. Statistical techniques, particularly in the multivariate normal case, are given for several commonly used c-e measures. These techniques provide methods for obtaining confidence intervals, for testing the hypothesis of admissibility and for the equality of interventions, and for ranking interventions. The ideas are illustrated for a hypothetical clinical trial of antipsychotic agents for community-based persons with mental illness.