Payers are only convinced by evidence. So before we think about how we are going to communicate, we need to understand what we have to say. Our team of experienced evidence-based scientists will assess your existing evidence, identify gaps, and develop fresh clinical and economic insights to support your access strategy.

'Calculating added value needs method, data and creativity'

Health economic evaluation

As the cost of healthcare increases, society’s ability and willingness to pay decreases, and the need to demonstrate the value of new interventions in order to gain adoption is as important as it has ever been. Indeed, evaluating the economic case for a product is at the heart of reimbursement and health technology assessment processes worldwide – so developing a robust and appropriate economic argument is often the key to commercial success.

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Data analytics

Healthcare data is complex and increasingly ubiquitous – and this presents a challenge for stakeholders needing ready-to-go insights to inform their prescribing and reimbursement decisions. Our in-house data analytics team are experienced and skilled at evaluating patient-level and real world data, and transforming them into actionable insights.

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'Unearthing insights means understanding data'

'Evidence needs to found before you can be enlightened'

Systematic literature review

Before engaging with payers and reimbursement bodies, it is critical to have a full picture of the evidence supporting your product’s proposition. Systematic literature review is the gold standard method for identifying and synthesising published evidence. Moreover, it has become an essential element of “launch preparedness”, as many health technology assessment bodies around the world now require evidence to be identified via systematic methods.

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Meta-analysis has become a key technique in evaluating comparative evidence and informing payer decisions worldwide, and is increasingly a core evidence pillar supporting product value propositions. Our in-house literature review analysts and medical statisticians work side-by-side to enable a seamless transition between the systematic review and the meta-analysis feasibility assessment and full statistical analysis.

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'Connected data can drive powerful insights'