We work in close collaboration with stakeholders to establish what needs to be done, which resources are available, and what the timeline is.
In a landscape where resources are finite, but the demand for new and improved health care interventions is high, the efficient allocation of resources is essential. Health economic modelling serves as an important tool for the evaluation of health and cost outcomes associated with healthcare interventions.
Communicating the value of an intervention through robust economic evaluation empowers stakeholders to make well-informed decisions: payers can compare a new treatment with the standard of care and decide whether it is eligible for reimbursement.
We specialize in developing tailored, precise, and flexible health economic models. Our approach is multifaceted, involving several key phases dedicated to ensuring the model aligns with its intended purpose and meets the specific needs of our clients. Depending on the model and available sources, our process includes comprehensive steps to identify important outcomes, risk factors and model inputs.
Although approaches may vary across models, our general approach to developing a health economic model stems from international guidelines and the conceptual modelling framework by Squires et al. (2016)¹.
1 Squires H, Chilcott J, Akehurst R, Burr J, Kelly MP. A Framework for Developing the Structure of Public Health Economic Models. Value in Health. 2016;19(5):588-601. doi:10.1016/J.JVAL.2016.02.011
We work in close collaboration with stakeholders to establish what needs to be done, which resources are available, and what the timeline is.
We ensure that all relevant stakeholders are included, and all angles are covered. This will enhance the relevance of the model later on.
Defining the problem is essential to solving it. This is done by formulating a clear research question and may involve mapping out the problem and hypothesized causal relationships in a conceptual mode.
Our protocol development phase is a key step in our model development. The design phase involves several key steps:
In this phase, model inputs are gathered from a variety of sources, using the following steps.
The model will be designed to acknowledge and explore possible limitations in evidence and modelling uncertainty. This might include alternative data sources, modification of key assumptions or the inclusion/exclusion of variables. The overall aim is to capture the joint parameter uncertainty and structural uncertainty present in the model and understand the implications for decision-makers.
In this phase, the model is communicated to the shareholders, who are able to give feedback and suggestions for revision. The goal is to ensure that the final model is of the highest standards and meets final client requirements.
Finally, the model may be published via abstracts and posters for scientific conferences, manuscripts for peer-reviewed journals, or via other channels.