Economic Evaluations in Psychiatry

INTRODUCTION

Economic evaluations play a vital role in healthcare decision-making, especially in resource-constrained settings, by helping to balance costs with health outcomes effectively. Healthcare resources are limited in all societies, including developed countries, necessitating the rationing of these resources and making complex decisions regarding their allocation. Funding for mental health services remains disproportionately low despite the high global burden of disease due to psychiatric morbidities.¹ This is particularly crucial in India, where low insurance coverage and a high risk of poverty due to medical expenses make cost-effective policies essential.² The decisions about resource allocation require a thorough evaluation of the costs and outcomes of proposed health interventions and services. Additionally, opportunity costs must be considered, as investing in one health intervention or service inevitably reduces the investment available for other areas. Hence, economic evaluations play a crucial role in assisting with these decision-making processes.³ Economic evaluation is the comparative analysis of alternative courses of action regarding their costs and consequences.⁴ Assessing the costs and benefits of different options can be complex and also influenced by perspective and time horizons. The perspective determines whose costs and benefits are considered (patients, health care providers, society, etc.). For example, a drug for schizophrenia might help a patient manage their symptoms and enable them to return to work, thus benefiting society as well. In economic evaluations, perspective is crucial. For instance, reducing inpatient psychiatry beds might be cost-effective for a healthcare trust, but this may not hold true from the viewpoint of society or patients. The time horizon is the period over which costs and benefits are measured. A longer time horizon can capture long-term effects and outcomes, such as the prophylactic effect of lithium in a bipolar patient or the reduction of suicide risk due to dialectical behavior therapy in patients with emotionally unstable personality disorders, which might not be apparent in the short term. The type of economic evaluation selected depends on the specific decision required and the data available for the analysis.

Over the past three to four decades, the significance of economic evaluation has grown, driven not only by rising costs and demands but also by the need to make scientifically sound decisions to ensure transparency and reliability. Additionally, the availability of better data and advancements in economic methodologies have made economic evaluation a vital component of the decision-making process for pharmaceutical companies and government agencies like the National Institute of Health and Care Excellence (NICE) in the UK. To support such decision-making, the Government of India established the Health Technology Assessment in India (HTAIn) with the primary aim of generating evidence on the cost-effectiveness of healthcare interventions. The HTAIn secretariat operates under the Department of Health Research.⁵ Most funded randomized controlled trials now include economic analysis. This paper aims to provide a brief overview of economic evaluations for psychiatrists.

The economic evaluations discussed below use the same approach to measuring cost impacts but differ in assessing health effects [Table 1].

COST-BENEFIT ANALYSIS (CBA)

CBA assesses both costs and benefits in monetary terms when the benefits of alternative options are not identical. If outcomes are identical, then the decision can be made to go with the cheaper option, referred to as cost-minimization analysis. It is used in many areas, such as businesses using CBA to assess the potential return on investment for a new project or the government assessing the feasibility of infrastructure projects. As costs and benefits are measured in monetary terms, it allows comparison across different sectors. CBAs are easy to interpret as costs and outcomes are measured in the same units, and outcomes can include both health and non-health benefits. Assigning a monetary value to a health outcome (such as death or the cost of relapse) is very difficult. One possible approach is assessing the cost of a health outcome’s “willingness to pay.” It signifies the highest amount an individual is prepared to spend (accept compensation to avoid) on a particular health outcome, and its value is derived from surveys of affected individuals. Conducting a CBA presents several challenges, including the complexity of assigning monetary value to health outcomes, especially regarding psychiatry, such as relapse of a psychiatric disorder or suicide. The other complexity concerns gathering reliable data and considering differing stakeholders’ perspectives. Due to the above reasons, its use in psychiatry has been minimal. O’Mahony⁶ conducted a comprehensive economic CBA of person-centered medicine reviews performed by general practice pharmacists for patients at high risk of medicines-related harm.⁶ They calculated the costs involved, such as pharmacist time and resources, and the benefits, including cost savings from reduced medicine-related harm such as hospital admissions. The findings revealed significant cost savings due to decreased adverse drug events and hospital admissions.

COST-CONSEQUENCES ANALYSIS (CCA)

CCA is very similar to cost-benefit analysis (CBA), except that it assesses a wide range of costs and consequences of the alternative options and describes all the costs and benefits in a detailed and disaggregated way. No formal combination of costs and outcomes is attempted, leaving decision-makers to assess the relative importance of the alternative outcomes presented subjectively and align them best with their goals and constraints.⁷ In healthcare, CCA can be applied to alternative options with varied costs and benefits that include health, non-health, positive and negative effects, patients’ and carers’ costs, etc. Hence, it gives a broader perspective in comparison to other economic evaluations. The results are less generalizable due to the choices of relevant costs and effects, and the weighting attached to them is often context-specific. Chang et al.⁸ conducted a 1-year mirror-image study of the use of risperidone long-acting injection on service costs.⁸ The comparisons were made for service sectors (in terms of the number of visits, acute admissions, and relapse events) and cost components (outpatient, inpatient, emergency, medication, and non-medication costs). They reported that the depot treatment was linked to an overall increase in psychiatric service costs, alongside a reduction in inpatient service utilization and associated costs.

COST-EFFECTIVENESS ANALYSIS (CEA)

CEA assesses costs in monetary values but evaluates outcomes in non-monetary units, such as specific clinical measurements, including blood pressure and cholesterol levels, as well as the cost per reduction in symptoms. In terms of mental health, possible non-monetary unit measurements may be depression-free days achieved, relapses prevented, or changes in the severity of symptoms. The typical reporting format is the Incremental Cost-Effectiveness Ratio, which represents the average additional cost per unit of effect gained compared to the alternative option. For instance, a study of computerized cognitive behavioral therapy compared to standard practice found that achieving a one-point improvement on the Beck Depression Inventory would cost £21, or (more intuitively) the cost of achieving one additional depression-free day would be £2.50.⁹ The main advantage is that outcomes are expressed in clinically meaningful terms. However, most disease-specific symptom metrics do not allow for comparisons across different conditions. Survival-related outcomes such as life years gained do allow comparisons over a broader range of conditions. However, since these measures do not account for morbidity and quality of life, their application in psychiatry is challenging. Moreover, as CEA analyzes disease-specific outcomes, they cannot be used for the allocation of resources across different disease areas (such as physical and mental health).

COST-UTILITY ANALYSIS (CUA)

As mentioned above, CEA cannot compare the allocation of resources or different outcomes. For this, we need a generic metric that can reliably compare diverse disease populations. Therefore, CUA determines the cost of utilities (utility refers to a cardinal value that reflects an individual’s preferences for different health outcomes), considering both qualitative and quantitative outcomes. The commonly used metric is quality-adjusted life years (QALYs). QALYs measure the quality of life as a utility value on a scale of zero (dead) to one (perfect health), incorporating survival benefits and quality of life in a single measure. Utility is a measure of how good or bad a person feels in a certain health state, usually on a scale from 0 (death) to 1 (perfect health). It is measured by asking patients with that health condition to rate how they feel. The commonly used scale in Europe is EuroQoL-5D (https://euroqol.org). Due to the use of a generic metric, comparisons can be made across different conditions and interventions with different outcomes. In the UK, NICE uses CUA (incremental cost-effectiveness) to compare the gains associated with alternative options and to make decisions about recommending interventions for the National Health Services (NHS). The term cost-effectiveness is used because CUA is a type of CEA that measures outcomes using utility metrics. Apart from any life-prolonging cancer drug, the threshold for cost-effectiveness is set at £20,000/QALY.¹⁰ Any intervention with a higher cost utility is rejected. For example, NICE approved vortioxetine as a third-line drug for depression (the incremental cost-utility ratio for vortioxetine compared with other antidepressants was £9,000/QALY) and did not approve nasal ketamine as the incremental cost-utility ratio was highly uncertain and unlikely to be a cost-effective use of NHS resources.^11,12 There is no such cost-effectiveness threshold for India; due to different sources of healthcare funding (personal, government, and insurance companies), it might not be an easy task. Patel et al.¹³ evaluated a lay counselor–delivered intervention for depression and anxiety in primary care settings in Goa through a cluster-randomized trial. The intervention significantly improved recovery rates and was cost-effective (measured by the incremental cost-utility ratio). Compared to enhanced usual care. It demonstrated strong potential for scalable, low-cost mental health care in low-resource settings.¹³

CONCLUSION

Economic evaluations are important aspects of decision-making. Despite the increasing burden of mental illness, only a small proportion of resources is devoted to mental health services. It is imperative for psychiatrists to learn more about economic evaluations and collaborate with health economists, funders, and decision-makers to raise awareness about the economic impact of mental illness and interventions. In health services, economic evaluations are becoming essential to resource allocation. These evaluations can also shed light on the effectiveness of policies aimed at addressing broader social determinants of mental health, such as housing.