​Using existing ePROM.
Start at 2,000 euro + 0.5 to 2 euro per respondent.
​
Depends − for instance on whether it is intended for commercial or academic use, or on the size of the study.
​Using existing ePROM.
Start at 2,000 euro + 0.5 to 2 euro per respondent.
​
Depends − for instance on whether it is intended for commercial or academic use, or on the size of the study.
​Using existing ePROM.
Start at 2,000 euro + 0.5 to 2 euro per respondent.
​
Depends − for instance on whether it is intended for commercial or academic use, or on the size of the study.
Fixed cost per month
20 euro.
Fixed cost per month
20 euro.
From values to utilities
For most research questions the results produced by our ePROMs and tools are very useful. In some cases (economic evaluation) an anchored scale in which dead=0.00 is required. We have proven methods available for normalizing and transforming values into utilities
Economic evaluation
Regulatory authorities and governmental organizations generally require studies to evaluate the value of health interventions. Many of these bodies recommend using a summary measure of health outcome, such as quality-adjusted life years (QALYs), as the unit of health benefit in economic evaluations. For QALYs we need that 'dead' has a metric value of zero.
Utilities
Preference-based methods stemming from economics, such as the standard gamble and time trade-off, are constructed such that they directly produce values on a scale, where 0.0 is equal to dead and 1.0 is full health, and these values can be applied in QALY computations, where they are called utilities.
Our preference-based methods require extensions or additional exercises to normalize values because dead does not appear on the scale.
Normalization
Values collected with our ePROMs are normalized. By normalizing we mean that the values are transformed or rescaled to produce a common utility scale (0–1). For this purpose, a separate survey performed by a sample of the general population will be performed and the collected data analyzed by a rank-ordered
logit model.
