Cost Effectiveness Analysis

With the (possible) funding amount known, a business economic assessment of the product is in order to know if market success, on an economic level, is possible.

Within the Design process 1 and ”Classic“ business model fit phases, see Sections 4.2.1 and 4.2.7, the market need and the fit with RaM/the R&D-team have been assessed to see if market success is possible. With the amount of funding (to be) received clear, the outgoing costs can be planned, this is done within the research proposal, and laid down next to the expected sales to see what has to be done to enable profit for the project.

With a knowledge of the (general) funds of the producer received or to receive via the

applied funding, a business economic assessment of the product is in order to know if mar- ket success is possible. Using three types of cost-effectiveness analysis (CEA) the needed product quality (increase) and the maximal production costs are calculated. More gener- ally speaking, a CEA is one of the tools to rank the desirability of using an alternative, an alternative MT, in comparison with current practice. With its many similarities with the more economical cost-benefit analysis, most prefer to use CEA because it does not, on the foreground, places a monetary value on the health outcomes [15, 38].

If either of the three,Headroom analysis,Return on Investment analysis orThreshold anal- ysis, presents the R&D-team with a non-desirable outcome, the model redirects the flow via connector ”D“ to Design Process 2 presented in Section 4.2.14.

Cost-effectiveness: Headroom analysis

Cost-effectiveness is typically modelled using parameter estimates obtained from random- ized controlled trails (RCT). Note that these parameter data are still estimates.

In the case of a technology that is in an early stage of its life cycle, or even yet to be developed, the nature of the product is unclear [38]. However, instead of taking the route were the leading question is

How cost-effective will the project be?

containing the above described amounts of uncertainty, another question can be used.

Would it be cost-effective if the project develops as thought?

The use of this question allows for an estimation of the effectiveness gap present between the SotA and the level the purposed technology and a calculation of the corresponding incremental costs of the project to the point where it is still considered to be cost-effective. This way the headroom of the project is calculated, hence the term headroom analysis (HA) [38].

If there is too little headroom, when the net cost of using the product could not real- istically be held below this level, investment of resources should be allocated elsewhere [38].

Note that the reverse not holds true, the new technology might still fail despite an ade- quate estimated amount of headroom. The project might turn out to be less effective or more expensive than initially estimated or alternatives may emerge [38]. Taking this in consideration, a well preformed HA can lower the risk of embarking on a project [38]. This type of analysis will be suited for most of the projects presented by RaM, is given below. Equation 4.2 results in the amount of incremental Quality Adjusted Life Years (QALY) the new technology will provide [38].

∆QALY = (1−∆QoL)∗n[38] (4.2) with

Unit Name Description

QALY Quality Adjusted Life Year Life years weighted by quality of life

QoL Quality of Life Scale where 1 signifies perfect QoL and 0 represents death

n Amount of years

ICER Incremental Cost Effectiveness Ratio Extra cost per unit of benefit when comparing one treatment, technology or programme against another [15]

The incremental QALYs are to be converted into monetary terms when enough certainty is present, to offset the financial costs of the treatment, to arrive at a net health benefit for each treatment via a scenario analysis [1, 18]. Using Equation 4.3, ∆Costs expresses the headroom the project has based on the Willingness to Pay (WTP) of the specific region, the maximum additional cost of the new treatment over the comparator for the new treatment, to be [15, 38].

∆Costs = ∆QALY ∗W T P[38] (4.3)

4.2. The Decision Making Model

Often this ∆Costs is taken further to calculate the ICER as can be seen in Equation 4.4 and will be discussed in more detail in Sections 4.2.10 and 4.2.11.

ICER= ∆Costs

∆QALY [15] (4.4)

with

Unit Name Description

ICER Incremental Cost Effectiveness Ratio Extra cost per unit of benefit when comparing one treatment, technology or programme against another [15]

Cost-effectiveness: Return On Investment

When an acceptable amount of headroom is present for the project, continuation of de- velopment and investment would appear to be justified. When looking from a (purely) business perspective, a viable company must have adequate volumes to repay the Return on Investment (RoI) [15].

Development costs will play a part in the decision to continue or abandon projects. These factors will be largely based on internals of the organisation rather than the technology itself [15]. As these fall outside the scope of this research, they are not discussed here. Using the introduced Equation 4.3, the amount of revenue that, given the estimates, can be generated can be calculated with Equation 4.5 [15]. Note that revenue refers to business income in general and is not the same as profit [15].

R= (∆Costsmax−C0)∗V[15] (4.5)

with

Unit Name Description

R Revenue Income from normal business activities

C0 Expected costs of production Annual production costs

V Amount of cases per year Effective sales market indication

Using Equation 4.5 the neededQoLpresent in Equation 4.2 can be reversely calculated by changing from

to

QoL_needed =QoL_SotA+ (−

(R_V+C0₎

W T P

n + 1) (4.7)

giving the needed QoL of the MT as a result. With this Equations 4.5 and 4.6 venture into the Threshold analysis described below and in Equation 4.8.

Cost-effectiveness: Threshold Analysis

The estimated amount of revenue, in combination with the calculated headroom, shows whether the MT could be profitable with the stated amount of funding.

Alternatively, a more formal value of investment analysis testing might be needed. This involves testing a more realistic, effectively speaking this will result is a less optimistic, estimate of the increased effectiveness ∆QoL [15].

The analysis gives an effectiveness threshold as to where further investment of capital and time must stop.

The threshold analysis is an iterating variant upon the headroom analysis presented in Section 4.2.9 and Equation 4.3 where single value of ∆QoL will be replaced by a range of possible effectiveness. This determines at what point the new technology will no longer be cost-effective from a development perspective. This being the case when Equation 4.8 does not hold true.

M arginP rof it <((((1−∆QoL)∗n)∗W T P)−C0)∗V (4.8)

With all this information a Value dossier can be created. This will set clear goals for the designers as where to aim for when taking the next iteration in the design process. The next step is the construction of the actual Incremental Cost Effectiveness Ratio.

4.2. The Decision Making Model