Aprendizaje por observación

This section reviews in detail the cost-effectiveness plane (CE plane), followed by a discussion of the decision rules for cost-effectiveness analysis. Once the relevant parameters in a decision model are determined and the appropriate distributions applied, probabilistic sensitivity analysis can be performed. Random values form each parameter distribution are sampled randomly using Monte Carlo simulations with 1,000 iterations as mentioned in the previous section in order to provide different cost, effect and cost-effectiveness outcomes for each vector of the input parameters. NICE guidelines for methods of technology appraisal 2013 suggest standard deciding factors should be followed when combining costs and QALY, these should reflect when

dominance or extended dominance exists, and present a thorough incremental cost-effectiveness ratio (ICERs) (NICE, 2013).

Cost-effectiveness analysis on the CE plane

The purpose of cost-effectiveness analysis is to compare the cost and health outcomes of one treatment compared to some relevant alternatives (O'Brien et al., 1994a) (Shepard and Thompson, 1979) (Sculpher et al., 1997). In other words, a new experimental therapy (or treatment group) may be compared with and some current practice (or control). In terms of costs, the true costs of the new therapy (C_t) versus the control therapy (C_c) are presented and the true effectiveness of the new therapy (E_t) versus the control therapy (E_c) are also illustrated, as shown in Table 2.6. Four situations have been identified by O’Brien and colleagues that can occur with regard to the incremental cost and effectiveness of therapies, as outlined in (O'Brien et al., 1994b) (Drummond and McGuire, 2007).

Table 2.6 Characteristics of cost-effectiveness and not-cost-effectiveness regions in the cost-effectiveness plane (CE)

Situations Interpretation CE plane

quadrants 1. Ct – Cc > 0; Et – Ec < 0 dominance – reject experimental therapy as it is

both more expensive and less effective than existing therapy

NW

2. Ct – Cc > 0; Et – Ec > 0 trade-off consider magnitude of the additional cost of the new therapy relative to its additional cost

NE

3. Ct – Cc < 0; Et – Ec < 0 Trade-off consider magnitude of the cost-saving of the new therapy relative to its reduced effectiveness

SW

4. Ct – Cc < 0; Et – Ec > 0 dominance – accept experimental therapy as it is both cheaper and more effective than existing therapy

SE

Base on page 174, chapter 8 of economic evaluation in health care (Drummond and McGuire, 2007)

Four situations in are equivalent to the four quadrants of the CE plane. This plane has been advocated for the analysis of cost-effectiveness results (Anderson et al., 1986). The difference in cost and the different in health outcome between two therapies can fall into one of four quadrants of the CE plane. There are a lot of authors discussed and presented the CE plane in different way. The four situations are presented in different ways. The most popular used is compass direction which shown in north, south, east and west (Hoch et al., 2002) (Fenwick et al., 2006) (Briggs, 2007). Another

way to present the result in different quadrants of the cost-effectiveness plane is Roman numbers (Black, 1990) (Briggs, 1998) (Drummond, 2005b).

This thesis presents the cost-effectiveness plane by compass direction. Figure 2.2 illustrates the cost-effectiveness plane. In the diagram, the horizontal axis represents the difference in effect between the therapies of interest, and the vertical axis represents the difference in costs. A therapy can be placed anywhere on this diagram according to its incremental costs and effectiveness. In the SE and NW quadrants one intervention is simultaneously cheaper and more effective than the other (situation 1&4). However, quadrants NE and SW (situation 2&3) on the CE plane represent where an intervention is both more effective and more costly. A trade-off must then be made between the additional health outcomes and the additional resources required. Or, in other words, a judgement needs to be made concerning whether the additional cost of the more expensive therapy is justified by the additional effectiveness associated with that therapy.

In order to summarise this trade-off, an incremental effectiveness ratio (ICER) is calculated. If this ICER is less than the maximum acceptable cost-effectiveness ratio then the treatment is considered cost-effective. The ICER is discussed below. A straight line is drawn across the NE and SW quadrants and through the origin (as shown in Figure 2.2) and represents the maximum acceptable cost-effectiveness ratio. The line divides the CE plane into two parts; cost-effective and non-cost-effective. The right side of the line indicates that therapies are effective, while the other side indicates cost-ineffective therapies.

Figure 2.2 The cost-effectiveness plane

Based upon figure 2.3, Uncertainty in cost-effectiveness of health care intervention (Briggs, 1998)

Incremental cost effectiveness ratio

The results of CEA are summarised in a cost-effective ratio (CER) (Phillips, 2009).

According to the individual programme, the result may be an average cost-effectiveness ratio (ACER). An independent programme requiring ACER is calculated for each programme, by comparing total costs and total outcomes. The ACER can be calculated by equation below. However, ACER does not provide guidance in decision making and is inappropriate to maximise the health effects for a specific share of resources (Karlsson and Johannesson, 1996). Therefore, ACER is inconsistent with the underlying decision rules of cost-effectiveness analysis.

Ct Cc

ACER= and

Et Ec

It is likely that choices will normally have to be made between different therapy options for the same condition, different dosages/treatment compared with prophylaxis.

What must be questioned however is the amount of benefit that can be achieved from a new therapy and what cost it is associated with? To answer this question incremental cost-effectiveness ratios (ICER) are used. ICER can be calculated, which obtains a summary of the cost-effectiveness of one intervention compared to the other. Similarly, ICER is the difference in costs between the two interventions divided by the difference in

their consequences, and can be described as the incremental price of a health unit outcome from the intervention, compared to the other. The interventions that have a low cost-effectiveness ratio are good value and would be the preferred option. Alternatively, where the costs and benefits of each alternative are calculated and compared with their next best alternative, rather than with a common alternative. The ICER can be calculated by the following equation.

Ct Cc Ct-Cc

ICER=

-Et Ec

Et-Ec

The ICER determines the appropriate measure of cost-effectiveness rather than the ACER. The difference of two average ratios is not equal to ratio of the differences (Briggs et al., 2006). The first problem with ACER, in order to make the judgement concerning whether therapy represents good value for money, decision-makers need to consider the additional cost of new therapy, as treatment A, over the control therapy, as treatment B, in comparison to the additional effect, that is the ICER. Suppose that we are comparing treatment A versus treatment B. If Treatment B gives the lowest cost per unit effect, treatment A shows the greatest overall effect. It could be that society wishes to provide treatment A rather than treatment B even though its average cost per unit effect is higher. Another problem with ACERs is that they give no information on the relative position of the two treatments in the cost-effectiveness space.

Incremental net benefit

In this section, two methods for developing point estimates for the difference in cost and effect, the cost-effectiveness ratio and net monetary benefit (NMB) are described. If both cost and effectiveness are higher with the new intervention, the question will come up with will decision maker, should a new intervention be accepted as cost effective or not.

To answer this question, the decision rule is applied. Decision rule requires the decision maker to know the maximum amount that the payer would be willing to spend for and additional benefit or maximum acceptable cost-effectiveness ratio. In the other words, the maximum willingness to pay for a benefit is known as the cost-effectiveness ceiling ratio, which can be plotted as a line through the origin on the CE plane, as demonstrated in figure 2.3. The ICER remains the most popular method of presenting the result of CEA and CUA (Drummond, 1987). Interpretation of ICER requires the choice of a cost-effectiveness ceiling where representing the maximum that society would be willing to pay for an incremental health benefit, and the development of the decision rule based on this maximum. If the estimated ICER is below some maximum willingness to pay for

health gain then that intervention represents good value for money. For example, if the ceiling ratio was £ 30,000 per QALY gained, then an intervention which presents incremental costs of £10,000 and increased QALY by 0.4. Thereby, it would have an ICER at £ 25,000 per QALY and would be considered to be cost-effective in comparison to the alternative. If the ceiling ratio presents at £20,000 per QALY, then an ICER of

£25,000 per QALY would not be considered cost-effective. The cost-effectiveness decision rule rearrangement by ICER can be calculated by equation 2.3. The maximum acceptable willingness to pay or ceiling ratio is denoted by λ.

Ct-Cc Decision-rule= <λ

Et-Ec

One of the most major drawbacks of the ICER relates to the mathematical difficulty in creating confident intervals for a ratio (McFarlane and Bayoumi, 2004). The net benefit approach employs a simple re-arrangement of the cost-effectiveness decision rule of equation 3 in order to overcome the problems with cost-effectiveness ratios. The limitation of ICER have led some authors to prefer the incremental net monetary benefit (INMB) (Hoch et al., 2002) (McFarlane and Bayoumi, 2004). The INMB is calculated by the increase in effectiveness multiplied by the amount of the maximum acceptable willingness to pay and subtracting from this the incremental cost of achieving the benefit, as shown in equation below. Using the NMB approach, a therapy is deemed to be cost-effective if a positive incremental net-benefit suggests that the therapy represents good value for money, while a negative side suggests the intervention is cost-ineffective (Drummond, 2005b). >

   

INMB= Ct-Cc λ- Et-Ec 0

The INMB expression is probably most familiar to economists, and is the one most often referred to as “net benefit” in the literature, as mention above. Thus, one potential advantage of INMB compared with cost-effectiveness ratios is that we can directly compare the difference in arithmetic mean monetary benefits between treatment groups to determine NMB by use of the same types of univariate and multivariable methods. Moreover, using the net benefit approach, it is also possible to re-arrange the inequality in another way to define the net health benefit (NHB), as shown in equation below.

  ^(Et-Ec)

NHB= Et-Ec - >0

λ

For both expressions, a positive incremental net benefit presents the health gain greater than that from investing the same resources in an alternative therapy. A negative incremental net benefit suggests the intervention is cost-ineffective.

2.18 Decision making, uncertainty and the value of