Exploring the reuse of health data by the European pharmaceutical industry

Medical health care science innovation concept, illustration by Panuwat/Adobe Stock

Photo by Panuwat/Adobe Stock

An exploration into current practices related to the reuse of health data by the European pharmaceutical industry found a number of important factors that can support or hinder the reuse of data. These include aspects such as the availability, interoperability and quality of data; data analytic skills and experience; and the presence of clear and uniform regulations.

Researchers identified a number of topics for further discussion that might help create a sustainable ecosystem in which health data are reused effectively. These included the need for continued research and development of analytic tools, promoting the adoption of standards and interoperability across datasets, building public confidence and trust in the pharmaceutical industry to reuse health data, and greater collaboration between industry and other key stakeholders.


The health data landscape is rapidly evolving, with a growing recognition of the potential benefits of reusing health data for secondary analysis by the pharmaceutical industry. At the same time, numerous technological, regulatory, economic and social challenges need to be addressed in order for stakeholders to capture value from health data, and support the creation of enabling health data ecosystems.


The European Federation of Pharmaceutical Industries and Associations (EFPIA) commissioned RAND Europe to undertake a study to explore current practices related to the reuse of health data by the European pharmaceutical industry. The reuse or secondary use of health data (by industry) refers to the use of data initially collected for some other primary purpose.

Specifically, the study aimed to develop an understanding of:

  1. How different types of health data are reused by the pharmaceutical industry and the reasons for this
  2. The key enablers and barriers to effective reuse of data
  3. Considerations for future action by different stakeholders, including industry and policy makers


The study involved a mixed-methods approach, including: a targeted literature review; the development of 12 case vignettes exemplifying the reuse of health data by industry; a series of interviews with stakeholders across the health data ecosystem; and a synthesis workshop to reflect on the findings and articulate potential implications for future action by stakeholders.


Electronic health records, health registry data and clinical trial data are reused most frequently

These three are the most frequently mentioned types of health data being reused by the European pharmaceutical industry. Other types of health data being used include biobank data, prescribing and dispensing data, and claims data. More recently, social media data and data from wearable devices have also been used.

The pharmaceutical industry reuses health data for a variety of reasons

  • To enable better insights into the real world than an artificial setting allows.

  • To help increase efficiency and reduce costs for both industry and health systems.

  • A growing availability of health data is contributing to its increasing use.

Health data is reused across the R&D pathway

The data is used for numerous purposes, such as:

At the discovery and drug development stage

  • To identify and better understand diseases;
  • To develop targeted and personalised therapies and drugs;
  • To develop new analytical methods.

At the clinical research stage

  • To inform clinical trial design;
  • To create new approaches to patient stratification;
  • In feasibility studies;
  • Alongside or instead of control groups for trials, to reduce the need to enrol patients as controls

At the marketing authorisation and market access stage

  • For medicine authorisation and regulatory purposes;
  • To support market access discussions;
  • To conduct cost-effectiveness analyses.

At the post-authorisation stage

  • To support pharmacovigilance and pharmacoepidemiology;
  • To enhance the medical evidence base, and inform practice guidelines and drug repurposing;
  • To support effectiveness comparison between drugs.

There are a number of enablers and barriers to reusing health data


  • Effective collaborations with a range of stakeholders
  • Easily accessible and inexpensive data
  • Regulators and policy makers that recognise the value of health data
  • Continual development of tools, and access to staff with adequate skills


  • Poor quality, restricted-access, biased and/or non-interoperable data
  • Challenging administrative factors
  • Lack of clear and uniform regulations
  • Lack of effective skills and experience
  • Lack of public and healthcare provider trust in the pharmaceutical industry

Priority topics for further discussion

The following seven suggestions might help create a sustainable ecosystem in which health data is reused effectively.

  • The pharmaceutical industry should actively continue to explore the reuse of new and different types of health data beyond those that have been traditionally used in secondary analysis.

  • As the field of health data grows, continued research and development is needed on analytical tools and techniques (including the ability to link different datasets).

  • A greater degree of collaboration between the pharmaceutical industry and other key stakeholders (such as regulators and healthcare system actors) is needed to improve accessibility to health data.

  • Promoting standards and interoperability across datasets could enable health data to be used effectively and efficiently as the health data ecosystem evolves.

  • There is a need for clearer and more uniform regulations (including for data protection) and guidelines related to secondary data analysis.

  • Improving data and analytical skills within the pharmaceutical industry is key to enabling effective secondary analyses of health data.

  • Building public confidence could help facilitate buy-in and trust and promote the further reuse of health data by the pharmaceutical industry.