Building and running network decision analysis models for complex health interventions.
Understanding the market size for health technology or new therapeutics requires accurate and up-to-date burden of illness estimation.
What we do
We conduct detailed burden of morbidity and mortality analyses using custom sourced data from administrative, insurance and research datasets.
Clients can confidently plan their corporate activities and conduct risk assessments based on a sound evidence base.
Business decisions in the health space are often made without full consideration of all contributing factors and risks. The key supporting information may be incomplete, or the decision path complex and affected by numerous technical and commercial factors that interact. The impact of poor decisions may not be known or appreciated. Poor decisions cost individuals and entire organizations money and time.
What we do
We apply a structured approach to decision analysis that combines statistics, value measurement and logic maps into a coherent framework.
This includes a rational evidence-based framing of the problem/decision tree network and all relevant uncertainty points.
Clients receive clear measurable results in the face of complexity. Having traceable decision analysis models that are flexible, and allow for continuous improvement evolution, provides clients the confidence to make critical program decisions.