Developing the role of electronic health records in economic evaluation

Excerpt

Cost-effectiveness analysis (CEA) is increasingly used to inform health decision-making with a consequence that the methods and assumptions are exposed to critical review [1]. Criticism may be hard to avoid because cost-effectiveness models generally represent a simplification of the real world in which health interventions are delivered and patients are treated. George Box’s aphorism that ‘all models are wrong but some are useful’ is highly relevant in this field [2]; some simplification is essential because the real-world is too complex to be completely represented in a tractable model. Researchers generally adopt a rigorous approach to identifying estimates of intervention effectiveness, which are usually drawn from well-designed and well-conducted randomized controlled trials, or from systematic reviews and meta-analyses. There is less consistency of approach to the collection of epidemiological data to populate a CEA model, including the costs associated with model health states and the probabilities of transitioning between states. Modelling studies often rely on data inputs assembled from multiple secondary sources, often identified through literature or ‘scoping’ reviews and incorporating additional assumptions. In studies of population sub-groups, estimates may be derived from small non-probability samples. These processes could compromise both the precision and external validity of model-based estimates of cost-effectiveness. …