Real-world evidence and its importance in medicine development

What is real-world evidence (RWE)?

Real-world evidence (RWE) is the evidence derived from the analysis and/or synthesis of real-world data (RWD). RWD is an overarching term for data on the effects of health interventions (such as benefits, risks or resource use) that are not collected in the context of conventional randomised controlled trials (RCTs). Instead, RWD is collected both prospectively and retrospectively from observations of routine clinical practice. It may include clinical and economic outcomes, patient-reported outcomes and health-related quality of life.

RWD can be obtained from many sources including patient registries, electronic medical records, and observational studies.

For more information on existing RWD sources, see Sources of Real World Data.

For more information about study designs used in generating RWD, see Generating Real World Evidence.

For more information about the terms used on this website, see the GetReal glossary.

How can RWE be used in medicine development?

RWE has an important role in decision-making related to authorisation and reimbursement and access of new medicines. It can be used for:

  • understanding ‘real-world’ settings, such as treatment populations, patterns of care and the burden of disease
  • assessing the effectiveness of current therapies using existing data
  • refining or supplementing evidence from conventional trials of new medicines
  • providing new evidence of relative effectiveness of new medicines.

RWD has conventionally been used to understand and characterise treatment populations, patterns of care and burden of disease. It has also been used to describe the natural history of disease, extrapolate long-term outcomes, and to define and validate new measures of outcome of relevance to patients.

RWE of the effectiveness of existing therapies will usually be available to help plan studies of new medicines. In some circumstances it may be possible to generate new RWE (‘early’ estimates) of the effectiveness of a new medicine, in time to inform reimbursement decision-making. In most circumstances it will be possible to generate new RWE of the effectiveness of new medicines after marketing authorisation, to inform (local) decisions on access to and optimisation of the use of the new medicine, and potentially to inform delayed reimbursement decisions (coverage with evidence development). RWE of safety outcomes is frequently required by regulatory agencies after marketing authorisation.

Why is RWE important in medicine development?

In most European healthcare systems, decision-making related to reimbursement and access to medicines by national and local healthcare payers and providers has become more prominent. RWE can be used to support these decisions.

Decision making for marketing authorisation of new medicines is traditionally supported by randomised controlled trials (RCTs), recognised as the ‘gold standard’ for establishing safety and efficacy. However, RCTs are undertaken in an idealised care environment and they may only measure efficacy in restricted populations, defined by trial eligibility criteria.

Healthcare payers, including reimbursement decision makers, wish to know the relative effectiveness of a new medicine compared with the current standard treatment in patients eligible for the new medicine in their population (the ‘treatable population’). They will ask questions such as:

  • Where will this medicine be used in the ‘care pathway’ for the treatable population?
  • Is the treatable population similar to the trial population, both in terms of socio-demography and in treatment history?
  • Is the treatable population currently receiving similar care to the comparator group in the trial?
  • Do the measures of health outcome (safety and efficacy) reported in the trial form a sufficient evidence base on which to make a decision? Do they capture relevant patient and clinician experience?

RCTs alone may not provide sufficient evidence of relative effectiveness. To support decision-making:

  • Data from RCTs may be combined in new types of meta-analyses to enable a wider range of comparisons with alternative therapies to be performed.
  • Statistical analyses may be applied to RCT data to estimate the efficacy in specific sub-populations or populations with different characteristics.
  • Studies (randomised or non-randomised) of the effectiveness of new medicines in less restricted populations may be carried out in usual care ‘real-world’ settings.
  • Statistical analyses may be used in advance of trials to help refine the trial design and make the results more useful for decision-making.

Both for authorisation and for reimbursement of new medicines RWD / RWE can be used to refine or supplement the evidence available from conventional trials.

GetReal and RWE

The focus of GetReal was on the use of RWE in medicine development, before and around the time of marketing authorisation and reimbursement. The project was primarily focused on the potential use of RWE to provide evidence on relative effectiveness of new medicines.

For more about GetReal, see What was the IMI GetReal Project?