There has been no widely accepted successful way of incorporating economic considerations into guidelines. However, the reasons for considering costs are clearly stated: ‘Health interventions are not free, people are not infinitely rich, and the budgets of [healthcare] programs are limited. For every dollar’s worth of healthcare that is consumed, a dollar will be paid. While these payments can be laundered, disguised or hidden, they will not go away’ [8
]. Such opportunity costs are a universal phenomenon. It is also the case that while considerations of effectiveness may be applicable across different healthcare systems, considerations of cost and values are more likely to be healthcare system-specific. Therefore, a cost-effectiveness guideline may be less transferable than one based solely on clinical effectiveness.
In the USA, the 1992 IOM report [33
] offered the aspirational recommendation that every set of clinical guidelines should include information on the cost implications of the alternative preventive, diagnostic, and management strategies for each clinical situation. The stated rationale was that this information would help potential users to better evaluate the potential consequences of different practices. However, they then acknowledged that ‘the reality is that this recommendation poses major methodological and practical challenges.’ Although there is emerging practical experience, this position has not really changed. In addition, it has also become recognized that issues of cost are much more likely to be health system-specific (as compared to the clinical evidence areas of guideline development) and so, unless explicitly mandated—like the UK National Institute for Health and Clinical Excellence (NICE)—many guideline developers do not do this.
Some guideline development organizations (e.g., NICE) advocate the review of appropriate cost-effectiveness studies alongside the review of the clinical evidence, though, in their guideline development manual, they note that ‘only rarely will the health economic literature be comprehensive enough and conclusive enough that no further analysis is required. Additional economic analyses will usually be needed.’ The available ‘economic evidence’ may be limited in terms of general applicability to the specific context of the clinical guideline, but can be useful in framing the general bounds of cost-effectiveness of management options for a clinical condition and providing an explicit source for some of the assumptions that may have to be made.
The methods of incorporating economic considerations are shaped by the methods of guideline development [34
]. Early on in the development of each of the guidelines, there is a fundamental decision to be made about how to summarize the data and whether or not there are common outcomes across studies. If common outcomes are available, then it may be possible to use quantitative techniques (meta-analysis or meta-regression) leading to summary relative and absolute estimates of benefit, and it may then be possible to formally combine the elements of effectiveness and cost into a summary cost-effectiveness statistic. With relatively broad clinical areas (e.g.
, the management of type 2 diabetes), it is more difficult to do this, whereas for narrower areas (e.g.
, choosing a drug to treat depression) it is may be more feasible.
If the evidence summary is to be qualitative (a narrative review of studies) the data can be set out in ways that facilitate easy comparison between studies by using common descriptors (e.g., study design, study population, intervention, duration of intervention) using evidence tables. However, under these circumstances it may not be possible to make estimates of cost-effectiveness unless the evidence summary is dominated by one study with appropriate outcomes. For guidelines that use qualitative evidence summary methods (not amenable to meta-analysis), it is usually only possible to present cost data alongside the evidence of clinical effectiveness allowing a reader to make their own judgments about the relative weight to be ascribed to these two dimensions of evidence. It is possible to make cost minimization statements such as: ‘as the treatments appear equivalent clinicians should offer the cheapest preparation that patients can tolerate and comply with.’
For guidelines focused on a single decision, it may be possible to incorporate economic data into a formal decision analysis framework. Traditionally, it is the province of health economics to model (combine, adjust, extrapolate, represent) intermediate clinical outcome data and data from other sources to explore the overall costs and consequences of treatment alternatives. In principle, it is possible to map clinical data onto generic quality of life scores, model the advancement of disease and produce cost per quality-adjusted life year (QALY) estimates for each treatment decision. However, such a process contrasts with the above methods in a number of ways. First, although they may have a role in informing the questions, values, and assumptions that go into a model, there is no clear role for a multi-disciplinary guideline development group in deriving recommendations around the clinical decision—the ‘right decision’ is produced by the model. Second, the data are aggregated into a single metric, the constituent elements of which (and their associated uncertainty) are not transparent. Third, the complexity of modeling a single decision is often such that the viability of the method to deal with more complex clinical decisions, which have multiple interdependencies, has to be questioned. Therefore, the appropriate application of a decision analysis-driven guideline is currently unclear and a question for further research.