Introduction

Efficacy and safety have traditionally been the key evidentiary cornerstones for a new health technology to obtain market access. This evidence is a required part of the licensing of a new drug or medical device. However, over the last decade, with increasing pressure on health care budgets there has been a global trend for health care systems to also provide evidence of cost-effectiveness before they will reimburse or cover a new health care technology.^1,2 Indeed, many countries have established agencies such as the National Institute for Health and Clinical Excellence (NICE) in the United Kingdom (UK), with a mandate to undertake economic evaluations of new and emerging treatments and thus determine if they represent good value for money for that health care jurisdiction. Although often focused on drugs, the consequence of economic evaluation for medical devices, and therefore neurostimulation, are even more potentially challenging given their high up-front cost.

The first part of this chapter is an overview of the different types of economic evaluation and guidelines. The second part of this chapter illustrates these methods by reference to the evidence base for the cost-effectiveness of spinal cord stimulation (SCS).

Methods of Economic Evaluation

The term cost-effectiveness has become synonymous with health economic evaluation and has been used (and misused) to depict the extent to which interventions measure up to what can be considered to represent value for money. Strictly speaking, however, cost-effectiveness analysis (CEA) is one of a number of techniques of economic evaluation.

Economic evaluation is the “comparative analysis of [two or more] courses of action in terms of their costs and consequences”³ and is a tool to assist health care policy makers. A decision maker can then decide whether the intervention is worth paying for by comparing its benefits with the benefits foregone (so-called opportunity cost), in paying for it. Or, to put it another way, given that budgets are finite, economic evaluation seeks to maximize outcomes for the resources available (so-called economic efficiency).

There are four main types of full economic evaluation. Each characterizes costs in the same terms (i.e., in monetary units such as dollars). However, each has a different approach to characterizing health outcomes.

In cost-minimization analysis (CMA), the effectiveness of each of the interventions must have been demonstrated to be equal. Thus the analysis is simply a comparison of costs. The least costly option will be preferred.

In cost-benefit analysis (CBA), both costs and benefits are measured in monetary terms. This has the considerable advantage that the decision to proceed or not is simply a case of measuring whether the value of the benefits exceeds the cost. The disadvantage is that it is difficult (and sometimes objectionable) to effectively put a price on a life. Although often used in areas such as transportation policy, CBA is used infrequently in health care.

Cost-effectiveness analysis (CEA) is concerned with costs and health outcomes and describes health outcomes in naturalistic or disease-specific units. Therefore CEA can tell which strategy maximizes a given objective (e.g., which neurostimulation treatment provides the most pain relief with the lowest cost).

Cost-utility analysis (CUA) is a subgroup of CEA. But, whereas health outcome measures in CEA relate to one aspect of a patient’s well-being, health outcome measures in CUA attempt to capture all aspects of well-being in a single composite (utility) value. The quality adjusted life year (QALY) is the typical outcome measure in a CUA. Calculation of QALYs entails first measuring quality of life (utility) on a scale from zero to one (where zero equates to death and one equates to perfect health). The period of time (in years) over which this quality assessment applies is then multiplied by its quality weighting to give the number of QALYs. Given both the comprehensiveness of the QALY and that it allows policy makers to compare value for money across disease areas (e.g., cost-effectiveness of vagal nerve stimulation for refractory epilepsy vs. deep brain stimulation for Parkinson disease or analgesic drug treatments for the management of neuropathic pain syndromes), CUA has been widely regarded as the gold standard by many health economists and policy makers.

Grounded in economic theory, utility measures reflect the preferences of groups of persons for particular treatment outcomes and disease states and combine many different health domains into a single number, weighting the different domains with the values people have for the particular health states. Utilities can be elicited directly, using the standard gamble or time trade-off (TTO) methods, or indirectly, using questionnaire-based measures (such as EuroQol [EQ-5D] or Health Utilities Index [HUI] for which population preference weights have previously been obtained). Indirect preference measurement techniques obtain utilities using questionnaires to elicit individuals’ valuations of multiple attributes, or domains, of their quality of life (e.g., mobility, emotional well-being, and cognitive ability); responses are then converted into utility values using preestablished formulas. An example of the utility of a male patient age 65 years with diabetic neuropathic pain based on completion of the EQ-5D is shown in Box 24-1. The utility index of 0.228 is contrast to an age-sex matched score of 0.78 for an otherwise healthy member of the UK population.⁴