When Can We Trust Real-World Data To Evaluate New Medical Treatments?

Journal Article (Journal Article)

Concerns regarding both the limited generalizability and the slow pace of traditional randomized trials have led to calls for greater use of real-world evidence (RWE) in the evaluation of new treatments or products. RWE studies often rely on real-world data (RWD), including data extracted from healthcare records or data captured by mobile phones or other consumer devices. Global assessments of RWD sources are not helpful in assessing whether any specific RWD element is fit for any specific purpose. Instead, evidence generators and evidence consumers should clearly identify the specific health state or clinical phenomenon of interest and then consider each step between that clinical phenomenon and its representation in a research database. We propose specific questions regarding potential error or bias affecting each of those steps: Would a person experiencing this clinical phenomenon present for care in this setting or interact with this recording device? Would this clinical phenomenon be accurately recognized or assessed? How might the recording environment or tools affect accurate and consistent recording of this clinical phenomenon? Can data elements from different sources be harmonized, both technically (same format) and semantically (same meaning)? Can the original data elements be consistently reduced to a useful clinical phenotype? Addressing these questions requires a range of clinical, organizational, and technical expertise. Transparency regarding each step in the creation of RWD is essential if evidence consumers are to rely on RWE studies.

Full Text

Duke Authors

Cited Authors

  • Simon, GE; Bindman, AB; Dreyer, NA; Platt, R; Watanabe, JH; Horberg, M; Hernandez, A; Califf, RM

Published Date

  • January 2022

Published In

Volume / Issue

  • 111 / 1

Start / End Page

  • 24 - 29

PubMed ID

  • 33932030

Pubmed Central ID

  • PMC9292968

Electronic International Standard Serial Number (EISSN)

  • 1532-6535

Digital Object Identifier (DOI)

  • 10.1002/cpt.2252

Language

  • eng

Conference Location

  • United States