Respecto del argumento de defensa del acusado, está claro que en la presente causa está en juego su libertad que es un bien jurídico de mayor

With the creation of an ICER, the assessment of the increased quality of the new MT in comparison with the SotA is possible to use as a sales pitch instrument rather than an analysis tool.

To convince buyers to buy the new MT being developed or, in earlier stages of devel- opment, peak their interests, a method of comparison is needed. An ICER shows the increase in (cost) effectiveness of the project in comparison with the SotA and is one of the most commonly used methods in doing so.

A CEA describes an intervention in terms of the ratio of incremental costs per unit of incremental health effect, using the QALY as the standard unit within CEA [24]. In some instances, this changes the name from CEA into a cost-utility analysis. These calculations can also be seen in Equation 4.4 and are explained in Section 4.2.9. As mentioned, the calculation of an ICER is often a next step in the process. Whilst the previous equations show whether the project should continue or not, this ICER is an excellent tool to show the ”quality“ of the MT in comparison the other (competing) devices.

Typically the results of an ICER analysis are represented as points in one of the four quad- rants of the cost effectiveness plane shown in Figure 4.5. Most new technologies lay within quadrant b., being more effective but also costing more than their comparator. Here the WTP line comes into play. The WTP, which is country and sometimes even disease spe- cific, is the amount society is willing to pay for an increase of 1 QALY for one individual. This is, in most cases, the line to which governments and insurance companies abide when deciding on reimbursement questions. Meaning that a product estimated to be below and to the right of the blue line will be reimbursed. This is normally used for medication and medical technology that is eventually paid by society itself. However, it can be connected to the later distribution to the Dutch market of technologies of which the purchase will fall on the shoulders of hospital or medical institutions. Because this effect is an in depth effect of insurance systems, this will not be discussed further. In Table 4.4 the new newly adopted WTP values, based on the experienced burden of disease, for the Netherlands are shown. When presenting this in the cost-effectiveness plane from Figure 4.5, not one, but three lines are present [29].

Because RaM deals with the more peripheral types of MT, the insurance company al- lowance of the MT is less important, see Section 4.1. In most cases, the hospital itself will be responsible for the purchase and no insurance plan type of funding is present for them. Meaning that the ICER will primarily be used as a sales pitch instrument within RaM.

Table 4.4.: Dutch WTPs based on burden of disease per 2015 [49]

Burden of disease (disutilities) WTP

0.10 to 0.40 e20.000/QALY 0.41 to 0.70 e50.000/QALY 0.71 to 1.00 e80.000/QALY

Figure 4.5.:Cost-effectiveness plane used in CEA to compare different medical technologies with eachother. With in dotted red the WTP and in blue the reimbursment line.

Still several problems remain present within CEAs, of which three are listed below [24].

Indirect costs

Indirect costs typically consist of lost wages due to being taken out of the general work force. There is no uniformly accepted standard practice of incorporating such costs [24]. If im- plemented by calculation of actual monetary value, the ADMM would become extremely more complicated. Alternatively, a simpler variable, the difference in indirect costs (∆IC) between comparators, can fulfil the same function [24].

When ∆IC<0, patients are back to work faster than when using the comparing technol- ogy. When implementing, this reasoning has to be reversed by showing that patients will need/are estimated to need less recovery time, leading to ∆IC<0 [24].

4.2. The Decision Making Model

is a logical consequence of improving medical technology [24]. This is being complemented by a longer living population [24].

Age bias

When describing the benefit of new technologies in terms of QALY or life years saved, a question arises. Are these methods intrinsically bias against the elderly?

The answer to this question, in most cases, is ”yes“ [24]. But in most cases the out- come is again weighted based on age categories. This bias is also less relevant in the field diagnostics where new technology is purchased for a multitude of patients in comparison to single patient purchases in the case of medication, meaning lower relative costs for hos- pitals [24].

To fill in the cost effectiveness plane for the new MT a selection of items that are to be compared is needed. For this the possible items are divided into the Diagnostic qual-

ities, Treatment qualities and User comfort of the product and will be selected in the

Item adjudication phase of the model, see Section 4.2.11. With the items selected a

more thorough SotA investigation will allow for a ICER to be created. This can be done by either comparing the new MT with the golden standard. This will also determine the market position of the product. In the early stage of the project it is perhaps more useful to compare it with the equipment used by the hospital of with the specialist expressed need originates persuading a specific hospital in purchasing the MT [29].

Flawed units

Diagnosis/Treament interaction Item adjudication (practice examples)

QALY QoL 5-year survival rate Number of follow ups

Recovery time Sensitivity Specificity Time efficiency QoL Survival rate Dummy proof MT Ease of use Ease of repair Ease of maintenance Trail-ability Presence of learning curve

Trail-ability Not too technical in appearnce

Not too simple in apperance

Less discomfort Not too technical in apperance

Not too simple in apperance Users

Patients GG

HH

Positive effect on treatment RR

Yes/Neutral

Positve effect on diagnosis No Yes Chart items for ICER Chart items for ICER Chart items for ICER RR Users Patients Interviews Experimental data RCT's Own experiments No Technical staff Medical staff Specialists

Device operating staff

If possible Questionnaires Users state to accept MT Patients state to accept MT Yes RR Yes Patient acceptance RR Yes No

User prefrences dossier

Elicit user prefrence for selected items

A A II ICER preperation No Neutral

4.2. The Decision Making Model