Published on 01 January 2025

Supplementary material: Real-world evidence: state-of-the-art and future perspectives

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Fitzke, Heather;Fayzan, Tamanah;Watkins, Jonathan;Galimov, Evgeny;F Pierce, Benjamin

Description

These are peer-reviewed supplementary materials for the article 'Real-world evidence: state-of-the-art and future perspectives' published in the Journal of Comparative Effectiveness Research.BackgroundAimMethodsStep 1: Selection of TAsStep 2a: Cross-validation of definition of ‘use of routine data in non-experimental settings’ Figure 3: Refinement of the criteria used to define 'use of routine data in non-experimental settings’ for the full assessment of published NICE TAsStep 2b: Full review of 12 Cancer and 67 Non-Cancer TAs published 2022-24ResultsFigure 4: Selection of TAs for reviewFigure 5: Distribution of Cancer (blue) and Non-Cancer (green) TAs submitted to NICE since 2000 (A). Non-Cancer TAs are broken down by specialty (B)Table 1: Results of the cross-validation of the criteria applied to randomly selected Cancer TAsTable 2: Results of the cross-validation of the criteria applied to randomly selected Non-Cancer TAsRecent developments in digital infrastructure, advanced analytical approaches, and regulatory settings have facilitated the broadened use of real-world evidence (RWE) in population health management and evaluation of novel health technologies. RWE has uniquely contributed to improving human health by addressing unmet clinical needs, from assessing the external validity of clinical trial data to discovery of new disease phenotypes. In this perspective, we present exemplars across various health areas that have been impacted by real-world data and RWE, and we provide insights into further opportunities afforded by RWE. By deploying robust methodologies and transparently reporting caveats and limitations, realworld data accessed via secure data environments can support proactive healthcare management and accelerate access to novel interventions in England.

Citations (1)

Mentions (0)

Metrics

Dataset Index

0.7

FAIR Score

13%

Citations

1

Mentions

0

Metrics Over Time

Publication Details

DOI

Publisher

Becaris

Assigned Domain

Subfield

Infectious Diseases

Field

Medicine

Domain

Health Sciences

Confidence Score

29%

Source

Scholar Data Model

Keywords

Digital health

Normalization Factors

FT

13.46

CTw

1.00

MTw

1.00