z-logo
open-access-imgOpen Access
A review of stakeholder recommendations for defining fit-for-purpose real-world evidence algorithms
Author(s) -
Julie Beyrer,
Hamed Abedtash,
Kenneth Hornbuckle,
James F. Murray
Publication year - 2022
Publication title -
journal of comparative effectiveness research
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.567
H-Index - 23
eISSN - 2042-6313
pISSN - 2042-6305
DOI - 10.2217/cer-2022-0006
Subject(s) - stakeholder , credibility , real world evidence , medicine , transparency (behavior) , reliability (semiconductor) , relevance (law) , quality (philosophy) , real world data , stakeholder engagement , process management , risk analysis (engineering) , computer science , data science , public relations , business , political science , physics , epistemology , philosophy , power (physics) , quantum mechanics , computer security , law
Aim: The credibility and value of real-world evidence (RWE) are either supported or undermined by the algorithms (i.e., operational definitions) used. Methods: We conducted a targeted evidence review of key RWE decision makers' published recommendations on RWE algorithms through April 2021. Stakeholders were regulatory bodies, other governmental agencies and payer organizations. Results: Our review identified recommended criteria: relevance, validity, reliability, responsiveness, transparency and replicability, safety, feasibility and quality process. Stakeholders routinely recommended accuracy measures, subgroups evaluation and specific considerations for assessing exposures and covariates and the underlying real-world data (RWD) quality. Conclusion: The importance of stakeholder guidance on fit-for-purpose RWE algorithms is growing. We highlight gaps that future guidance and stakeholder recommendations could address.

The content you want is available to Zendy users.

Already have an account? Click here to sign in.
Having issues? You can contact us here
Accelerating Research

Address

John Eccles House
Robert Robinson Avenue,
Oxford Science Park, Oxford
OX4 4GP, United Kingdom