Evidence map›Paper›PMID 37650031›Full record

ArticleInternational journal of population data science2022

Laying the foundation for Real-world evidence studies: a case study from Newfoundland and Labrador.

Winifred Badaiki, Evelyn Pyper, Kendra Lester, Janelle Skeard, Michelle Penney, Janey Shin, Brenda Fisher, Huong Hew, Susanne Gulliver, Wayne Gulliver and 1 more

Abstract read
In one paragraph

Article in International journal of population data science, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

11 authors.

Winifred BadaikiMemorial University of Newfoundland, Canada.
Evelyn PyperJanssen Inc., Toronto, Ontario, Canada.
Kendra LesterThe Newfoundland and Labrador Centre for Health Information, St. John's, Newfoundland and Labrador, Canada.
Janelle SkeardMemorial University of Newfoundland, Canada.
Michelle PenneyNewlab Clinical Research, St. John's, Newfoundland and Labrador, Canada.
Janey ShinJanssen Inc., Toronto, Ontario, Canada.
Brenda FisherJanssen Inc., Toronto, Ontario, Canada.
Huong HewJanssen Inc., Toronto, Ontario, Canada.
Susanne GulliverNewlab Clinical Research, St. John's, Newfoundland and Labrador, Canada.
Wayne GulliverNewlab Clinical Research, St. John's, Newfoundland and Labrador, Canada.
Proton RahmanMemorial University of Newfoundland, Canada.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The Janssen and Newfoundland and Labrador Health Innovation Partnership (JANL-HIP) was established to carry out Real-World Evidence (RWE) projects to generate evidence about disease pathways, healthcare delivery, the effects of clinical interventions. Doing so will support and influence clinical decision-making in Newfoundland and Labrador (NL). This case study describes the foundational elements necessary for a real-world evidence generation project in NL and may provide learning for the effective execution of real-world studies in other jurisdictions. It uses an ongoing project in psoriatic disease in NL to illustrate the partnership and the benefits of RWE studies. Ultimately, the JANL-HIP RWE project aims to inform decisions that will drive improvements in health outcomes, system delivery, and policy mutually beneficial to health ecosystem stakeholders.

Indexed as

Clinical Decision-MakingEcosystemHumansLearningNewfoundland and LabradorPolicyNewfoundland and LabradorpsoriasisReal world datareal world evidenceresearch partnership

Identifiers

PMID37650031
PMCPMC10464867

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.