Editorial brief · Methodology

How we evaluate AI tools for clinical practice

Healthcare AI Hub is an aggregation-and-curation reference. We do not run every tool in our own clinical practice. Here is what we do instead, what we weight, and what we explicitly do not claim.

Last updated May 18, 2026

01 / Sources

The six source-tiers we aggregate from

Each review draws from a stack of public sources. Weights below reflect how much each source contributes to a tool’s position in our comparisons.

Source 01 Vendor documentation Weight 30%: Pricing, feature lists, EHR-integration disclosures, compliance attestations (HIPAA, SOC 2, HITRUST, FDA-510(k) status).
Source 02 Public review aggregators Weight 20%: G2, Capterra, Software Advice, TrustRadius profile pages. Aggregated star-ratings + recent qualitative reviews.
Source 03 Clinician community sentiment Weight 20%: Reddit (r/medicine, r/familymedicine, r/medstudent, r/Residency, r/EmergencyMedicine), Doximity forums, and clinician YouTube reviews. Scraped via our research crawler, sentiment-analyzed, and quote-attributed.
Source 04 Peer-reviewed literature Weight 15%: PubMed-indexed studies that evaluate the tool in clinical settings. When available, primary literature carries the highest weight in our scoring.
Source 05 Vendor stability signals Weight 10%: Crunchbase funding rounds, leadership changes, EHR-marketplace certifications (Epic App Orchard, Cerner CodeFuture).
Source 06 Specialty society guidance Weight 5%: AAFP, AAP, ACP, AMA recommendations or endorsements when published.

02 / Principles

Six editorial principles that govern every review

Principle 01

Aggregation over self-testing

We do not run AI tools in our own clinical practice for the purpose of these reviews. Sites that claim hands-on testing of every tool in their index typically rely on the same public sources we do, with less transparency about it. We name our sources and link to them.

Principle 02

MD editorial sign-off

Every published review is reviewed by at least one board-certified physician on our editorial team before publication. The MD-verified badge appears only on tools whose reviews have completed sign-off within the past six months.

Principle 03

Affiliate transparency

Some outbound links are affiliate links. We disclose this inline at the point-of-occurrence (a sponsored badge next to each link) and at the bottom of every page. Rankings are editorial and never sold. We decline sponsorships from tools that fail our published evaluation criteria.

Principle 04

Source attribution per claim

Quantitative claims (pricing, integration counts, certification status) link to the source. Qualitative quotes from clinician reviews carry the source forum, subreddit, or platform with a date. We do not republish entire reviews; we quote with attribution under fair-use commentary.

Principle 05

Living documents, not frozen reports

Every review carries a last-verified timestamp per data category. Our scrapers re-run vendor documentation and community sentiment on a monthly cadence. Reviews older than 180 days carry a stale-data warning until refreshed.

Principle 06

Transparent uncertainty

Every tool page includes a What we have not verified block: data points the public sources do not let us validate (private SLA terms, enterprise pricing tiers below NDA, real-world latency in specific EHRs). We name what we do not know.

03 / Transparency

What we do not claim

01We do not claim "hands-on testing" of every tool in our index. When a tool review includes first-hand observations from an MD on our editorial team, the review is marked with that note.
02We do not claim our scoring is objective. Weights are editorial judgments published openly. Reasonable clinicians can disagree.
03We do not claim our reviews replace formal evaluation by your IT, compliance, or legal teams. Use this site to narrow a shortlist, not to make a final purchasing decision.
04We do not claim AI-tool reviews are medical advice. Reviews are about commercial software, not clinical guidance.
05We do not claim independence from commercial relationships. Affiliate links exist and we disclose them. We claim that our rankings are not for sale.

04 / Affiliate disclosure

Where money may change hands

Some outbound links to AI-tool vendors are affiliate links. If you sign up through one of these links, we may receive a referral commission. The price you pay is identical. The following commercial relationships exist:

Direct affiliate or referral agreements with selected vendors. These links carry a sponsored badge.
Sponsorship slots on category landing pages (clearly marked, category-exclusive maximum 1 per quarter).
Newsletter sponsorships in our forthcoming clinician newsletter (subject to the same editorial firewall).

Editorial rankings are not affected by these commercial relationships. We decline sponsorships from tools that fail our evaluation criteria. If you spot a vendor relationship we have not disclosed, please email editorial@healthcareai-tools.com.

05 / Corrections

Corrections policy

Pricing, integration, and certification data change rapidly. If you are a vendor, clinician, or reader and you spot an inaccuracy, we correct it within seven business days of verification. Corrections are logged at the bottom of each affected review with the original wording struck through.

Material errors that affect a tool’s ranking position trigger a re-publication notice, not a silent edit.

06 / Contact

Reach the editorial team

Editorial: editorial@healthcareai-tools.com
Corrections: corrections@healthcareai-tools.com
Vendor relations: partnerships@healthcareai-tools.com
Press: press@healthcareai-tools.com