Evidence map›Paper›PMID 41508412›Full record

ArticleInternational journal of technology assessment in health care2026

When should RWE studies be prioritized for reimbursement? Insights from the Canadian perspective.

Jennifer Boss, Laura Shulak, Trisha Rao, Candice Tam, Shannon M Sullivan

Abstract read
In one paragraph

Article in International journal of technology assessment in health care, 2026. 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. Review
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

5 authors.

Jennifer Bosshttps://ror.org/00gttkw41PPD Evidera Health Economics & Market Access, Thermo Fisher Scientific, UK.ORCID https://orcid.org/0009-0008-4214-8448
Laura Shulakhttps://ror.org/00gttkw41PPD Evidera Health Economics & Market Access, Thermo Fisher Scientific, Canada.
Trisha Raohttps://ror.org/00gttkw41PPD Evidera Health Economics & Market Access, Thermo Fisher Scientific, Canada.
Candice Tamhttps://ror.org/00gttkw41PPD Evidera Health Economics & Market Access, Thermo Fisher Scientific, UK.
Shannon M Sullivanhttps://ror.org/00gttkw41PPD Evidera Health Economics & Market Access, Thermo Fisher Scientific, France.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Given the increasing importance of real-world evidence (RWE) in health technology assessment (HTA) decision-making, we aimed to assess RWE use in Canadian HTA and collect stakeholder insights on when RWE generation should be prioritized in HTA.We found that RWE was included in one-third of Canadian Drug Agency-L'Agence des médicaments du Canada (CDA-AMC) reimbursement reviews (2017-2022). To further understand drivers of RWE generation for reimbursement, consultations were held with stakeholders (pharmaceutical industry representatives, payers, and patient advocates) to obtain insights in Canada and other global markets. Stakeholders highlighted the value of RWE to complement randomized controlled trials (RCT) data, as well as the need to consider feasibility and multiple stakeholder perspectives.Our findings indicate there is a need to further support the practical implementation of RWE in policy decision-making. A framework providing guidance on when to prioritize RWE studies for reimbursement would provide value and could be tailored by region.

Indexed as

Insurance, Health, ReimbursementReimbursement MechanismsTechnology Assessment, BiomedicalCanadaDecision MakingHealth PolicyHumansPolicy Makinghealth policyHTApharmaceuticalsreal-world evidencereimbursement

Identifiers

PMID41508412
PMCPMC12964149

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.