Evidence explorer

Every claim we hold, and how far we can stand behind it.

142 claims across 39 products. 30% are confirmed against the source text by the evidence gate; 39% come from a class with no vendor interest. Everything below is browsable, filterable, and available as JSON.

What this corpus is made of

Evidence class	Claims	Confirmed	What it can support
Peer-reviewed study	19	5	Independent review before publication. The only class that survives a sceptical committee unaided.
Regulatory filing	4	0	A statement made to a regulator, where being wrong has consequences.
Independent report	32	9	Analysis by someone with no stake in the sale.
Customer case	4	3	A real deployment, but selected and framed by someone with an interest.
Press release	63	23	The vendor's own announcement. Useful for dates and facts, not for outcomes.
Vendor page	20	2	Marketing copy. Establishes what is claimed, never that it is true.

Showing 5 of 5 matching claims (142 in the full corpus) · 0% of this selection is confirmed · clear filters

Peer-reviewed Nature Health study (SAFEMOM) of Ada integrated into South Africa's government-run MomConnect WhatsApp maternal health platform found safe health-seeking behavior rose nearly a third and appropriate care-seeking rose more than 40%; an independent physician panel rated Ada's recommendations safe in 98% of cases
Ada Health Assessment (AI symptom assessment & care navigation)Peer-reviewed studyUnverified2026-06-30Open source ↗
Provenance
Claim ID
clm_e424d6e33e196547ba29
Version
1
Workflow
Clinical Evidence & Decision Support
Dimension
evidence strength
Retrieved
2026-08-27
Reviewer
healthit-gate-v1
Source URL
https://doi.org/10.1038/s44360-026-00125-x
Mayo Clinic study in J Prim Care Community Health (2025 Apr 16;16:21501319251332215, doi 10.1177/21501319251332215) found OpenEvidence 'provided accurate, evidence-based recommendations in all cases, aligning with physician plans' across five common chronic conditions, with mean scores of clarity 3.55±0.60, relevance 3.75±0.44, support 3.35±0.49, and satisfaction 3.60±0.60.
OpenEvidencePeer-reviewed studyUnverified2025-04-16Open source ↗
Provenance
Claim ID
clm_565ce01a474e2b680115
Version
1
Workflow
Clinical Evidence & Decision Support
Dimension
evidence strength
Retrieved
2026-08-27
Reviewer
healthit-gate-v1
Source URL
https://pmc.ncbi.nlm.nih.gov/articles/PMC12033599/
Journal of Investigative Dermatology study (Dulmage et al., 2021;141:1230-1235, doi 10.1016/j.jid.2020.08.027) of VisualDx's point-of-care AI system found 'The AI system achieved an accuracy of 68% in determining the single most likely morphology from the test image bank', while primary care physicians scored 36% without aids and 68% with a visual guide (P < 0.001); on 222 images across Fitzpatrick skin types the AI achieved 70% accuracy in Fitzpatrick I-III and 68% in Fitzpatrick IV-VI (P = 0.79).
VisualDxPeer-reviewed studyUnverified2021-06-15Open source ↗
Provenance
Claim ID
clm_19dcf624d235238fa2b7
Version
1
Workflow
Clinical Evidence & Decision Support
Dimension
evidence strength
Retrieved
2026-08-27
Reviewer
healthit-gate-v1
Source URL
https://doi.org/10.1016/j.jid.2020.08.027
Independent BMJ Open peer-reviewed vignette study (Gilbert et al., 2020) compared digital symptom assessment apps, including Ada, against GPs for suggesting conditions and urgency advice
Ada Health Assessment (AI symptom assessment & care navigation)Peer-reviewed studyUnverified2020-12-31Open source ↗
Provenance
Claim ID
clm_796e5c36fb879e0a483b
Version
1
Workflow
Clinical Evidence & Decision Support
Dimension
evidence strength
Retrieved
2026-08-27
Reviewer
healthit-gate-v1
Source URL
https://pmc.ncbi.nlm.nih.gov/articles/PMC7745718/
Cluster-randomized controlled trial in J Med Libr Assoc (2019 Apr 1;107(2):151-162, doi 10.5195/jmla.2019.581) evaluated VisualDx as a clinical evidence technology for skin problems in primary care: 'Thirty-two PCPs and 433 patients participated', and time from index visit to skin problem resolution was similar in both groups (hazard ratio=0.92; 95% CI 0.70, 1.21; p=0.54).
VisualDxPeer-reviewed studyUnverified2019-04-01Open source ↗
Provenance
Claim ID
clm_fa1a96f540b206b3d969
Version
1
Workflow
Clinical Evidence & Decision Support
Dimension
evidence strength
Retrieved
2026-08-27
Reviewer
healthit-gate-v1
Source URL
https://pmc.ncbi.nlm.nih.gov/articles/PMC6466492/

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