Burden of Illness Research Studies

Payers, purchasers, and users of your technology require highly-targeted data and models that map to their patient populations. Highly aggregated estimates, or estimates that do not reflect their patient populations, will be insufficient.
Health economic models and value propositions rely on accurate estimates of the incidence and prevalence of outcomes. Using inaccurate measurements can be the difference between a strong or weak value proposition and market success or failure.
Having confidence in the burden of illness presents essential data. Confidence in the data presented helps persuade key decision makers to prioritize the right treatments for the right populations, while ensuring return on investment and overall cost savings.

The burden of many outcomes cannot be easily quantified through high-level coding, and as a result many burden of illness studies and health economic models are incomplete and under estimate the burden of disease.
Many estimates of burden of illness in peer-reviewed literature will be insufficient to convey confidence to market stakeholders due to deficiencies in methods, sample sizes, and generalizability of the populations being studied. A comprehensive, highly-customized and highly-focused burden of illness study is vital to communicating value to stakeholders.
BOI can vary significantly by important patient subpopulations; understanding who can benefit from your technology most is a critical part of a successful go-to-market strategy.

Utilizing real-world data sources such as disease-specific registries, administrative claims databases, hospital data sources, national longitudinal surveys, chart reviews, and relevant literature identified through systematic reviews, our experts can estimate burden of illness, including magnitude of an illness’ economic impact, public health impact, and patient-level impact (e.g., impact on quality of life).
Findings from our burden of illness studies can help to identify which disease would benefit most from an allocation of resources, determine which subpopulations would benefit most from your technology, provide decision-makers with critical information regarding healthcare obligations, gain insight into market size/share, inform forecasting functions, and support economic appraisals and decision making.
Using these findings, we can help develop your value messaging and bolster key value drivers.

Insights

Why Good Clinical Data Still Fails to Win Coverage One of the hardest [...]

Why Founders Underestimate Protocol Design One of the first questions I ask founders [...]

Your Stakeholders Have Changed. Has Your Evidence Strategy? I give a lecture at [...]