Clinical and administrative outputs
backed by evidence.
Text alternative for the silent product walkthrough. A clinician opens EvidenceMD on a phone and asks whether SGLT2 inhibitors reduce cardiovascular death or heart-failure hospitalisation in patients with HFpEF, independent of diabetic status. The app shows each reasoning step as it works: analysing the question, developing a search strategy, searching the knowledge base, and evaluating the evidence. It then returns a structured answer that compares trial endpoints in a table and cites each claim inline, with links through to the source publications. The recording continues into the AI scribe, where a new visit is started and a structured progress note is drafted automatically from the transcription.
How It Works
See how EvidenceMD delivers evidence-based clinical decision support in real time.
Watch the AI scribe capture and document patient encounters with clinical reasoning built in.
Presentations
NewEvidenceMD researches the literature first, then builds the slides around what it found. You get an evidence-based 10-slide deck for the audience and format you picked, and it downloads as a PDF.
Pick the audience — physician, nurse, PA, student, researcher, pharmacist.
Pick the arc — clinical review, case discussion, journal club, learning or research review.
Every claim is anchored to retrieved sources, and the deck stops where the evidence does.
01 / 10 · Cover
PDFEvidenceMD · Presentation
Clinical review · Physician · 10 slides · 6 sources
Example deck
One to three minutes end to end. Decks are saved to your workspace.
A clinical reasoning partner that enhances medical decision-making and streamlines documentation and operational workflows.
"What are the treatment options for CKD stage 4 in a patient with diabetes and eGFR 28?"
CDI + Utilization Review
Most documentation tools match keywords against a code list. EvidenceMD reads the chart the way a physician advisor does — building the clinical picture first, then showing you the exact words in the note that support every code, query and level-of-care decision. Revenue improves for an unglamorous reason: the work was already done and the documentation was not showing it.
Close a visit and run CDI/UR on the note the scribe just drafted. Accept the findings and they are written back into the note in one click — with one-click revert when you disagree. Chronic conditions from earlier visits are checked for recapture at the same time.
Paste or upload a note from whatever system you already use. You get the same CDI engine plus the standalone-only work: qualitative DRG impact, non-leading CC/MCC query drafts, inpatient-versus-observation review and the ED utilization pass.
What a review returns
A senior-CDI pass over the finished note: ICD-10 specificity, MEAT support, HCC recapture, E/M level and denial risk. If a code is not supported by text in the note, it does not appear.
MEAT · CMS-HCC V28 specificity · Excludes1 hygiene · 2-of-3 MDM
I50.9 → I50.23 — acute on chronic systolic heart failure
Unspecified heart failure drops the CC that the documentation already supports.
“SOB worse over 3 days, EF 30%, started on furosemide drip”
CKD stage 4 coded last visit, unaddressed today
Carried in the medication list but never assessed this encounter — no MEAT, no recapture.
“Continue sevelamer 800 mg TID”
Medical necessity not stated for the CT angiogram
The order is documented; the indication that justifies it is not.
Level 4 holds on Problems and Risk
Two of the three MDM elements clear the threshold and Data does not — scored, not assumed.
Illustrative output. Every finding in a real review is anchored to a verbatim phrase from your own note.
The engine builds the clinical picture before it goes looking for a code, which is how it catches the acuity a keyword scan reads straight past.
Every code, query and recommendation carries the exact phrase it came from. Unsupported findings are omitted rather than invented — which is what makes the output hold up under audit.
CC/MCC queries are drafted non-leading and multi-option, with the neutrality language reviewers look for, built only from the indicators charted.
EvidenceMD supports professional CDI, coding and utilization review — it does not replace the clinician or the certified coder signing off.
Closing the gap between bedside and back office.
Unified decision support for the care continuum.
Medical precision for administrative efficiency.
AI Clinical Decision Support
EvidenceMD is an AI clinical decision support platform designed to think the way clinicians do. Instead of returning a confident but unsourced paragraph, it works through a case step by step and shows the reasoning behind every recommendation — then backs that reasoning with peer-reviewed evidence from PubMed, clinical guidelines, and peer-reviewed journals indexed in PubMed. For physicians, residents, nurses and biomedical researchers, that means answers you can actually verify at the point of care.
The platform combines six capabilities that usually require separate tools: transparent clinical reasoning, an evidence-based AI medical scribe, CDI and utilization review, citation-backed literature search, evidence-based presentations, and a developer medical AI API. Together they cover the clinical and administrative work that fills a modern clinician's day.
Ask a differential, a workup, or a management question and EvidenceMD lays out its chain-of-thought with inline citations. Read more about how it works on the clinical reasoning page, or see why it's the best clinical decision support AI.
The evidence-based AI scribe drafts structured notes from the encounter and pairs documentation with clinical decision support, so the note and the reasoning stay connected.
DeepSearch does not just summarise papers. It retrieves from more than 40 million peer-reviewed papers and guidelines, then applies clinical reasoning to weigh what they mean for your question, with links back to the original studies so you can confirm the answer against the primary literature rather than a model's memory.
Teams can integrate the same clinical reasoning and citations into their own products through an OpenAI-compatible medical AI API, with a free tier to start.
Type a topic and get an evidence-based slide deck: more than 40 million peer-reviewed papers and clinical guidelines are retrieved first, the slides are built around what that pass found, and the finished 10-slide deck arrives with a linked Sources slide as a presenter view and a presentation-ready PDF for teaching, journal club or a case discussion. The AI medical presentation maker guide covers the workflow, the output contract and the design choices behind it, and the ranking of the six best AI medical presentation tools places it #1, ahead of PowerPoint with Copilot, Gamma, ChatSlide, Prezi and Beautiful.ai, as the only one of the six fine-tuned for healthcare.
The same reasoning engine reviews a finished note for clinical documentation integrity and utilization management — ICD-10 specificity, MEAT support, HCC recapture, E/M level, charge-capture gaps and denial risk, plus inpatient-versus-observation level-of-care and ED utilization review. Every finding is anchored to a verbatim phrase from the note. Run it on notes the AI scribe just wrote, or standalone on notes from any EHR.
Physicians and residents use EvidenceMD to pressure-test a differential, check drug interactions, and draft medical-necessity rationales with supporting citations. Nurses and advanced practice providers use it for guideline-concordant workups and clear documentation. Biomedical researchers use DeepSearch to move quickly across the literature. And healthcare engineering teams embed the API to bring evidence-based reasoning into their own clinical workflows. Learn more about the people building it on the team page.
Because it is built for medicine, EvidenceMD is careful about what it does and does not claim: it is a clinical decision support tool that surfaces evidence and reasoning to support a licensed clinician's judgment, not a replacement for it. Every answer is designed to be checked, with the sources one click away.
