Abstracts by keywords: personalized medicine
The so-called multi-criteria decision analysis (MCEA) can be used to support complex technology assessments. Multi-criteria decision analysis procedures have their origins in decision theory or operations research and are used there to make decisions under uncertainty. They assist decision makers in evaluating a finite number of alternative health interventions using a finite number of performance criteria. In addition to conjoint analysis, the elimination and choice translating reality method (ELECTRE) and the multiattribute utility theory (MAUT) (Lootsma/Schujit 1997), the most widely used multi-criteria decision analysis tools include the Analytic Hierarchy Process (AHP).
24.01.2013
In Germany, medical care is largely financed by contributions from insured persons. This results in the normative and ethical obligation of statutory health insurance to provide the optimum level of health services with maximum benefit for the insured. It is important to reduce waste, use resources efficiently, and all results must be meaningful, especially for patients. The health insurance companies, together with the service providers and the patients, are responsible for achieving these goals and a primarily scientifically based approach (SGB V §§ 2, 12, 35b, 70). The question of what is useful is described, for example, in SGB V § 35b as “improving the state of health, shortening the duration of the illness, extending the lifespan, reducing side effects and improving the quality of life”. This maxim can be found in an identical form in the G-BA's Rules of Procedure, in the Drug Benefit Assessment Ordinance or in the IQWiG method paper for benefit assessment. The statement that the benefit assessment has to be based on “patient-relevant target values” is of particular importance. “In this context, “patient-relevant” should be understood as how a patient feels, can perceive their functions and activities or whether they survive.” (IQWiG 2011, p. 30f)