A network of organisations we support across healthcare

Global Data Support collaborates with different organisations across the healthcare landscape to generate insights to support better outcomes for patients with rare and complex diseases.

Who we support

Global Data Support supports organisations that share a common goal: improving how rare and complex diseases are recognised, diagnosed and treated in practice. Through evidence-based insights, our work supports a better understanding of the landscape and, ultimately, better patient outcomes.

Global Data Support collaborates with organisations across several segments.

Healthcare and Research Organisations

We work with healthcare organisations seeking a clearer understanding of how rare disease diagnose and care is organised. Our insights support stronger collaboration between centres, improved disease awareness, and better access to therapies.

Established (Bio)Pharmaceutical Companies

We support (bio)pharmaceutical companies with approved therapies in identifying centres of expertise and referral pathways, helping ensure patients are diagnosed and treated in the right settings.

Emerging Therapy Innovators

We also collaborate with (bio)pharmaceutical companies preparing to launch new therapies or enter new markets. Our insights into disease expertise, networks, and healthcare infrastructure help organisations navigate the journey to commercialisation, while increasing awareness and improving patient access to new innovative therapies.

Medical Technology Organisations

We work with medical technology organisations and support them by identifying where specialised procedures are performed and which centres and clinicians have expertise to adopt new technologies. These insights support responsible technology adoption and ensure that innovative solutions reach those who may benefit from them.

Challenges in rare disease care and how Global Data Support addresses them

Global Data Support supports organisations that share a common goal: improving how rare and complex diseases are recognised, diagnosed and treated in practice. Through evidence-based insights, our work supports a better understanding of the landscape and, ultimately, better patient outcomes.

Global Data Support collaborates with organisations across several segments.

Organisations working in rare and complex diseases often face significant challenges in understanding how care is organised in practice:

Rare diseases are often not captured in healthcare coding systems like ICD-10, making it difficult to identify clinical activity through datasets.

Rare disease patients often move through multiple centres and may initially receive alternative diagnoses before reaching the expert. Diagnosis and treatment may occur in different centres, making patient pathways challenging to trace.

Many rare disease network analyses rely primarily on scientific activity. As a result, clinicians are overlooked and connections are missed. In practice, collaboration extends beyond research activity and includes signals like shared care, referral pathways and multidisciplinary collaboration.

In rare diseases, small patient populations, off-label use, and missing clinical context mean prescription data alone rarely reveals how patients are diagnosed, referred, and treated in practice.

How Global Data Support creates value for all organisations:

Rare disease activity is captured by combining multiple verifiable healthcare data sources and signals to uncover clinical activity that may remain hidden if only using healthcare coding systems.

Our analyses examine real-world referral patterns, diagnostic activity, and treatment involvement to understand how patients move through healthcare systems in practice. We also analyse disease correlations to identify clinicians involved in related conditions.

Our network approach goes beyond scientific output by examining the broader clinical and professional context in which clinicians operate. This deeper analysis helps reveal connections that are not always visible through scientific activity alone, while also recognising that relationships within networks vary in strength and influence.

We look beyond prescription data by integrating multiple real-world signals to build a more complete picture of how patients are diagnosed and treated.

Since rare disease expertise is often reflected in fragmented or incomplete information, our analyses go beyond automated data collection by identifying missing information and uncovering contextual links that automated approaches alone overlook.

Together, these insights support disease awareness initiatives, educational programmes, and more informed engagement strategies, while providing a clearer understanding of how patients move through healthcare systems, where referral delays occur, and where specialist expertise is concentrated or underutilised.