Amr Makady

What Is Real-World Data? A Review of Definitions Based on Literature and Stakeholder Interviews

BACKGROUND Despite increasing recognition of the value of real-world data (RWD), consensus on the definition of RWD is lacking. OBJECTIVES To review definitions publicly available for RWD to shed light on similarities and differences between them. METHODS A literature review and stakeholder interviews were used to compile data from eight groups of stakeholders. Data from documents and interviews were subjected to coding analysis. Definitions identified were classified into four categories: 1) data collected in a non-randomized controlled trial setting, 2) data collected in a non-interventional/non-controlled setting, 3) data collected in a non-experimental setting, and 4) others (i.e., data that do not fit into the other three categories). The frequency of definitions identified per category was recorded. RESULTS Fifty-three documents and 20 interviews were assessed. Thirty-eight definitions were identified: 20 out of 38 definitions (53%) were category 1 definitions, 9 (24%) were category 2 definitions, 5 (13%) were category 3 definitions, and 4 (11%) were category 4 definitions. Differences were identified between, and within, definition categories. For example, opinions differed on the aspects of intervention with which non-interventional/non-controlled settings should abide. No definitions were provided in two interviews or identified in 33 documents. CONCLUSIONS Most of the definitions defined RWD as data collected in a non-randomized controlled trial setting. A considerable number of definitions, however, diverged from this concept. Moreover, a significant number of authors and stakeholders did not have an official, institutional definition for RWD. Persisting variability in stakeholder definitions of RWD may lead to disparities among different stakeholders when discussing RWD use in decision making.

Practical implications of using real-world evidence (RWE) in comparative effectiveness research : learnings from IMI-GetReal

In light of increasing attention towards the use of real-world evidence (RWE) in decision making in recent years, this commentary aims to reflect on the experiences gained in accessing and using RWE for comparative effectiveness research as a part of the Innovative Medicines Initiative GetReal Consortium and discuss their implications for RWE use in decision-making.

Using Real-World Data in Health Technology Assessment (HTA) Practice: A Comparative Study of Five HTA Agencies

BackgroundReimbursement decisions are conventionally based on evidence from randomised controlled trials (RCTs), which often have high internal validity but low external validity. Real-world data (RWD) may provide complimentary evidence for relative effectiveness assessments (REAs) and cost-effectiveness assessments (CEAs). This study examines whether RWD is incorporated in health technology assessment (HTA) of melanoma drugs by European HTA agencies, as well as differences in RWD use between agencies and across time.MethodsHTA reports published between 1 January 2011 and 31 December 2016 were retrieved from websites of agencies representing five jurisdictions: England [National Institute for Health and Care Excellence (NICE)], Scotland [Scottish Medicines Consortium (SMC)], France [Haute Autorité de santé (HAS)], Germany [Institute for Quality and Efficacy in Healthcare (IQWiG)] and The Netherlands [Zorginstituut Nederland (ZIN)]. A standardized data extraction form was used to extract information on RWD inclusion for both REAs and CEAs.ResultsOverall, 52 reports were retrieved, all of which contained REAs; CEAs were present in 25 of the reports. RWD was included in 28 of the 52 REAs (54%), mainly to estimate melanoma prevalence, and in 22 of the 25 (88%) CEAs, mainly to extrapolate long-term effectiveness and/or identify drug-related costs. Differences emerged between agencies regarding RWD use in REAs; the ZIN and IQWiG cited RWD for evidence on prevalence, whereas the NICE, SMC and HAS additionally cited RWD use for drug effectiveness. No visible trend for RWD use in REAs and CEAs over time was observed.ConclusionIn general, RWD inclusion was higher in CEAs than REAs, and was mostly used to estimate melanoma prevalence in REAs or to predict long-term effectiveness in CEAs. Differences emerged between agencies’ use of RWD; however, no visible trends for RWD use over time were observed.