Importance of cost-benefit assessment in health services research

Health services research aims to improve the quality of care. Therefore, it is useful to first discuss the concept of quality of care. In health economics, quality of care refers not only to the level of services provided but also to how well the health services available in a country actually reach those with the greatest need. The question is therefore whether the population groups with the greatest need for health care are also receiving appropriate priority.

>> From a health economics perspective, the focus of health services research is therefore the question: "Are scarce resources actually reaching the place of most urgent need?" In health economics, we assume that resources are always scarce (Neubauer 2006). This also means that not everything medically possible can be provided. However, if not all needs can be met, economic rationality dictates that scarce resources be allocated to the most urgent needs. Ultimately, health services research is also about setting priorities.
Optimal allocation of scarce resources by KNB
From a health economics perspective, scarce resources must be distributed in such a way that a maximum level of needs is met, measured in terms of patient benefit. The logical calculation by which this optimum can be achieved is based on the rule that the optimum is achieved when the last euro invested achieves the same benefit in all possible areas of use. In other words: From an economic perspective, the optimal cost-benefit ratio is always important (Graf von der Schulenburg et al. 2007). In contrast, in medicine, resources are often allocated in such a way that the most effective measures are used, without considering the associated costs in the decision. Figure 1 outlines this relationship in a thought experiment. There are three possible uses for scarce resources. However, this also means that all three measures can only be used to a limited extent. Prioritization is necessary. From a medical perspective, the most effective measure (I) would clearly be preferred. From a health economics perspective, the relationship between the outlined cost pillar and the level of benefit is crucial. This means that from a health economics perspective, measure III is preferred because it offers the most favorable cost-benefit ratio.

Methods of cost-benefit analysis
A number of different economic evaluation methods are commonly used in healthcare, summarized in Figure 2. Of particular importance are the types of studies that consider clinical outcomes, namely cost-effectiveness analysis and cost-utility analysis. Cost-benefit analysis in the narrow sense is rarely used due to the difficulty of evaluating medical outcomes entirely in monetary terms. For simplicity, cost-effectiveness and cost-utility analyses are summarized below as "cost-benefit" analyses (CBA) in the broader sense.
At this point, it is important to briefly discuss the point in time at which a CBA is conducted. If a CBA is used ex ante, i.e., to evaluate possible alternative courses of action, it is referred to as an analysis. However, if a CBA is used to assess implemented measures, it represents an evaluation. The methods for both procedures are very similar. However, for an ex ante analysis, alternative courses of action must always be assessed comparatively, whereas an evaluation determines the actual cost-benefit ratio of an implemented healthcare concept.

Potential of CNA for health services research
Current practice in healthcare optimization is largely characterized by trial and error. Care concepts are often developed collaboratively and based on clinical expert opinions, and then, ideally, evaluated in a pilot project for medical characteristics and economic impact (IQWiG 2008). Analogous to the situation with randomized controlled trials (RCTs), this would roughly correspond to a "within-trial" analysis, with known strengths (e.g., precise cost recording) but also weaknesses (e.g., "protocol-driven costs," unclear external validity in a broader application). The existing methodology can also be used to plan care concepts in a significantly more evidence-based and efficient manner (Fig. 4).
The main difference from current practice is the information basis and, above all, the application of an ex ante economic analysis to theoretically compare different healthcare concepts with relatively little effort. Such experimental opportunities often produce unexpected results that deviate from conventional medical opinion. Furthermore, it is possible to model long time horizons that cannot otherwise be adequately considered. This is particularly important when dealing with epidemiological "risks" or chronic diseases: the effect of primary prevention, screening procedures, vaccinations, etc., which only becomes apparent after relatively long periods of time, is otherwise underestimated.
An example of the application of ex ante analysis is a study that models various cancer screening strategies for Chinese women (Woo PPS et al. 2007). It showed that a systematic program offered clear advantages over opportunistic cancer detection. If one then sets a budget that one is willing to spend on improving the quality of care, a combination strategy of 100 Pap screenings every 4 years and 30 colonoscopies every 10 years offered the best strategy. This study shows how theoretical considerations of cost-effectiveness can be used to optimize a care concept. A budget framework can also be set that specifies what is feasible: In this way, measures are selected and combined accordingly based on their cost-effectiveness, not on opinion or solely on medical effectiveness. Authorities such as NICE use a fundamentally similar approach when a cost-benefit threshold is applied to reimbursement decisions. The methodology can also be applied to optimize existing care procedures, for example, to optimize age criteria, recurrence rates, etc. of programs (Vaahtoranta-Lehtonen, H. et al. 2007). The method can be applied not only to diagnostics but also to care concepts. The existing uncertainty of the modeling can be made transparent through sensitivity analyses. In any case, the final care project (stage 3 in Fig. 4) can be designed and evaluated more specifically, since the relevant outcomes and parameters (and relevant comparison groups) are known from the previous modeling.
Inclusion of “real-life” quality of care
A meaningful cost-benefit analysis is usually only possible after several years of use in everyday care, depending on the indication. Health economic models provide suitable support for a preliminary cost-benefit analysis. After an appropriate observation period, a re-evaluation using everyday care data is useful. This applies not only to the cost-benefit analysis, but also to the benefit assessment per se. Since hard endpoints for many chronic diseases are often only measurable after 10 or more years, justified intermediate endpoints should also be accepted in such cases (Fig. 3).
A cost-benefit analysis must take into account the medical outcome, i.e. the assessment of the quality of care based on the overall result using defined target variables, social outcome variables taking socio-demographic factors into account, and the economic outcome from the perspective of the insured community or the contributors, including employers. The concept of costs (price, side effects, etc.) must be defined in a similarly broad manner. Only this overall assessment allows a conclusive analysis of the contribution, e.g. of a drug therapy or a medical-technical procedure for patient care. Since costs and outcomes change over time, re-evaluations are regularly useful. From a legal perspective, innovations would then only be permitted for a limited period of time. From an economic perspective, the level of cost coverage by health insurance companies and the level of patient cost participation would have to be designed to vary accordingly over time.
Limits of cost-benefit analysis
Optimized care that implements cost-effective diagnostic and therapeutic strategies can help save costs. However, this can only be achieved if the assessment is consistently implemented and existing healthcare structures are modified accordingly. This is likely to meet with considerable resistance. Accordingly, in many countries, the tool is only used for new, innovative therapies and diagnostics. Consistent use of these tools generally leads to an improvement in quality – but at higher costs. For example, the work of NICE, despite cross-therapeutic assessment with relatively clear cost-effectiveness thresholds, has led less to cost containment in England than to the standardization of higher treatment quality. A similar result can be expected from the use of CNB in Germany as part of consistent healthcare research. In summary, health economic cost-benefit analysis can be helpful in both the planning of healthcare concepts and in their implementation and optimization. The latter, however, aims more at improving quality than at containing costs.
outlook
As we have shown, health economics emphasizes the cost-benefit or effectiveness ratio in health services research. Health services research that ignores costs and focuses solely on effectiveness cannot result in optimal care from an economic perspective. For this reason, medicine is also called upon to pay more attention to cost-benefit analysis (Sickmüller et al. 2007). Simply optimizing therapeutic concepts without considering the associated costs ultimately leads to suboptimal care for the population. But we can no longer afford this in Germany.