Monitoring and Assessment Framework for the EIP on Active and Healthy Ageing


Welcome to the analysis tool of the Monitoring and Assessment Framework for the European Innovation Partnership on Active and Healthy Ageing (MAFEIP). You can use this generic decision analytic model to assess the impact of your innovation in terms of health outcomes (health related quality of life) and resource use. Based on data you have available yourself, which may be (preliminary) data from clinical studies, expert opinions and your own views, this model compares the costs and health effects of the intervention versus current care (control group).

The analysis

The tool performs an incremental analysis of the impact of your innovation. This means that it estimates the changes in healthcare resource use, societal resource use and health related quality of life that result from using your innovation instead of current care. As a result you need data on both the current care situation for your target population, as well as the situation in which your intervention is used.

The model

The outcomes for the intervention and the control group are calculated by simulating the health status of the target population. This is done by simulating the transition of the target population between three health states, namely baseline health, deteriorated health, and dead. The baseline health state represents the general health status of the target population. The deteriorated health state reflects the health status of people who experience the condition of interest (the condition that the intervention aims to prevent, relieve or cure). Each health state is defined by an amount of resource use and quality of life (utility). This represents the average resource use and quality of life of a patient in that health state. A transition from the baseline health to the deteriorated health state represents a patient becoming ill. It is also possible for patients to move from the deteriorated health state to the baseline health state, when their illness is cured. At any time in the simulation patients can die. This is represented by a transition to the dead state.

Each age-gender combination in the target population is entered into the model separately (that is, individuals are modeled one at a time). The model results for each age-gender combination can be shown either for males or females, or as a weighted average for the age and gender distribution in the target population.

The impact of your intervention

The impact of your intervention on the quality of life and resource use can be represented though multiple parameters in the model. It can be through a difference in the resource use and health related quality of life values that define the states in the model. It can also be via the probabilities that a person transitions between the health states. A combination of both is of course also possible. For each of the parameters in the model, you will be asked to provide a value for the current care setting and the setting with your intervention. By simulating the transition of patients though the various health states over time, and calculating the resource use and health related quality of life accumulated over that period, the impact of your intervention on these outcomes can be estimated.

Data provided by the tool

The tool contains information on the baseline all-cause mortality and population size of each of the EU member states, except Croatia (Austria, Belgium, Bulgaria, Cyprus, Czech Republic, Denmark, Estonia, Finland, France, Germany, Greece, Hungary, Ireland, Italy, Latvia, Lithuania, Luxembourg, Malta, the Netherlands, Poland, Portugal, Romania, Slovak Republic, Slovenia, Spain, Sweden and the United Kingdom). This data which was retrieved from the Human Mortality Database for the year 2005 is used for all mortalities in the model (transitions to the death state). It can be adjusted to suit the target population, deteriorated health population and intervention effects using relative risks. The population size data can be used to calculate a weighted average for age and gender in the selected country and for the target population specified by the user.

The outcome generated

The tool allows estimating health outcomes and impact on health and care utilisation, and calculating the cost-effectiveness of an innovation versus its respective standard care alternative. The European Commission is only interested in estimating the overall impact of the EIP on AHA on its main objectives (Quality of Life and sustainability of health and care systems). The tool does not allow comparing the innovations delivered in the Partnership on the basis of their cost-effectiveness as standard care scenarios will differ for each user and each innovation. Further the outcomes generated by the tool will not be made publicly available.

Getting started

You can proceed to the tool by clicking the button below.

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