Table 1.

PESTL Analysis of the RWD Landscape in Europe

Area	Drivers	Enablers	Barriers	Alternatives
Policy	European Commission (EC)'s push for the development of eHealth infrastructures and use of EHR EC's drive for the creation of Pan- European datasets and improved interoperability National healthcare reforms aiming to greater efficiency in service management and provision.	EU funding instruments Regional and National data infrastructure.	EC's data protection regulation Fragmentation of national approaches to health reform Disparities between national eHealth systems Governance issues regarding the design and implementation of RWD standards.	Reliance on data collected in countries with easiest rules for access Involvement in EU-funded research projects in partnership with relevant public and private stakeholders.
Economic	Resources constraints and need to develop efficient pathways to analysis Incentives for collaboration to pool resources Development of a market for data.	New synergies within the data value chain (e.g., with insurance companies) National authorities encouraging data input.	Fragmented markets presenting different characteristics Issues surrounding cost sharing for data access and use Conflicts of interest.	Routine collection of publicly available data Funding to academia for research in databases Participation in research-minded consortia to spread the cost of data access and analysis Engagement in disease specific research projects with direct access to self-reported patient data.
Social	Increased familiarity with sharing data Increased attention to the burden of a chronically ill and ageing society Enthusiasm for new cures for illnesses Willingness to access personalised health services.	Positive media coverage Interaction with stakeholders (e.g., rare disease groups) Practitioners care about improving outcomes for patients.	Increased suspicions about data use and potential breaches Privacy risks due to linking different datasets Regulation surrounding consent management Image problem of pharmaceutical companies or insurers.	Development of personalised and stratified health services offer Communication around the positive effects of RWD-based research.
Technological	Increased technological capabilities for data storage and analysis Increasing capacity to link distinct datasets Push towards standardisation of terminologies.	Machine learning, including natural language processing National/patient identifier systems Social media and apps for self-reported data collection.	Limits of analytical capabilities for the treatment of data Inconsistency of existing databases and limited development of data quality insurance standards.	Leveraging methods and tools developed in other sectors Exploration of the potential of apps/partnerships with device manufacturers.
Legal	EU level and national level debate on data protection, use and access.	Potential of using RWD to improve health services efficiency might influence existing regulation to facilitate data access Technological advances reduce the burden of work for consent documentation collection.	Privacy and data protection likely to be strengthened Ethical standards for research Fragmented standards for access to databases.	Efforts on transparency and ethical commitments Publication of RWD-based research results.