Welcome to our use cases

1. Rare Disease – Hereditary Angiodema (HAE)

Situation: 
The client’s product growth was slowing.  They were reaching the limit of the available patient population of around 500 patients.

Task: 
Understand if there were opportunities to find further patients – beyond the 500 – that were not currently being detected, diagnosed and treated by the UK healthcare system.

Action: 
Digital patient voice analysis revealed two key insights:
– There probably were many currently undiagnosed HAE patients.  These were likely to be concentrated in certain identified geographic hotspots across the UK.
– There was a big unmet need around anxiety and mental health support for HAE patients.

Results: 
– Using the 2 key insights, the sales team was able to have more valuable conversations with HCPs – especially in the geographic hotspots of unmet need that had been identified. 
– Within 3 months, a major hospital in one of those geographic hotspots had changed its prescribing policy and started to use the client’s product.  This generated significant additional client revenue and improved HAE management in the hospital’s catchment area.

2. Hormone Replacement Therapy (HRT)

Situation:
The client was launching a new product in the UK market.  They needed to decide whether to have different strategies for the NHS and Private markets.  They also wanted to understand how they could commercially benefit more than their competitors from the growing focus on regional inequality of care within the healthcare system.

Task:
Generate data-driven insight using digital patient voice data and other contextual data sources to provide insights that would inform and support the client’s decision-making, strategic planning, and targeted tactics per region.

Action:
Analysis was performed that revealed the following:
– There were clear localised relationships between menopause internet search, HRT prescribing, and levels of socio-economic deprivation across the UK.
– In wealthier areas, the digital patient voice data showed that search activity was often led by privately-paid-for alternative solutions to menopausal issues, such as Evening Primrose Oil and magnesium supplements.
– By contrast, in poorer areas with high levels of deprivation, search was predominantly around menopause symptoms and treatment – indicating a high level of unmet need in poorer communities.
– The data also showed high HRT prescribing rates from GPs in wealthier areas, and low HRT prescribing rates from GPs in poorer, more deprived areas.
– This data-driven insight strongly suggested that the menopause was being under-treated in the poor,  high-deprivation areas.  This represented an opportunity for the client to develop specific localised tactics and messages, and therefore to have value-added discussions with GPs in the areas of high deprivation.

Result:
Based on these data-driven insights:
– The client decided to pursue two distinct strategies – one for the NHS market and a different one for the Private market – supported by high quality data.
– They targeted and engaged with healthcare providers in the more deprived areas, grew those markets, and reduced the geographical inequalities in menopause management and HRT prescribing.

Client Data Privacy & Confidentiality

At r2-insight, we are committed to maintaining the highest standards of data privacy, confidentiality, and ethical practice in all client engagements.

All client data accessed and analysed by r2-insight is treated as strictly confidential. We do not share, repurpose, or disclose any identifiable client information without prior written consent. Data shared with us is used solely for the agreed project scope and in accordance with relevant data protection laws, including GDPR and applicable industry regulations.

Ethical Use of Insight

We ensure all insight derived from public or client data adheres to ethical standards. 

Use Case & Case Study Representation

Use cases, success stories, or case studies shared by r2-insight are anonymised to protect client identity and commercial interests.

• We do not disclose the names of companies, products, brands, or individuals involved in past or current projects unless we have received explicit permission to do so.
• Examples shared are generalised or aggregated in order to illustrate capability and to avoid revealing proprietary or strategic information.