OpenEvidence vs UpToDate vs a decision-support API: which does what

Clinicians ask "OpenEvidence or UpToDate?" because both now answer questions in natural language, and the question of which to open first is real. A third kind of tool, a decision-support API, gets lumped into the same comparison. It does a different job, and it is worth separating the three before choosing.

UpToDate: the expert-authored reference

UpToDate is a library of topic reviews written and reviewed by over 7,600 expert clinicians, editors and reviewers, with treatment and screening recommendations graded using the GRADE system.^[1][2] Users can earn CME while researching clinical topics.^[1]

It has changed in two ways that matter for this comparison. UpToDate Expert AI is generative AI built on UpToDate content, and Wolters Kluwer states it is now included in all UpToDate subscriptions in the US.^[3] And UpToDate Connect is an API-driven product that lets digital health companies integrate UpToDate content, including an Expert AI API for conversational, AI-generated responses grounded in UpToDate.^[4]

Best at: reading and citing a synthesized, graded recommendation on a topic you need to understand in depth.

OpenEvidence: the cited answer engine

OpenEvidence answers clinical questions with cited responses. It is free for verified US healthcare professionals, and it has signed content agreements with NEJM, JAMA, Nature, NCCN, Cochrane and others, plus partnerships with societies including ACC, AAFP, ACOG and ACEP.^[5]

Two facts are often misstated. First, OpenEvidence says it complies with HIPAA and that covered entities may transmit PHI under its standard business associate agreement.^[6] Second, its separate API terms say developers may not use the API to process protected health information.^[7] So "OpenEvidence cannot be used with PHI" is wrong for its clinician app, and "the OpenEvidence API takes PHI" is wrong for the API as its terms read today.

Best at: a fast, cited, natural-language answer to a specific question, at no cost to US clinicians.

A decision-support API: structured next steps

A decision-support API does not answer a question you type. It takes the clinical context (a note, or structured findings) and returns structured items another system can act on. That is what Pogosh is: labs with LOINC codes, imaging with RadLex codes, specialist routing adapted to setting, specialty, age and sex (including what happens after the emergency department), escalation criteria, a strict emergency check, relevant calculators offered but never auto-run, and a note draft that does not invent negatives. Its pricing is published: $149 per month for a clinic, $299 per month per location for a practice, and a $499 monthly minimum for EHR platforms.

Best at: putting an orderable, coded plan into a chart or product without a clinician retyping it.

Side by side

Where a cell says "not evaluated here", we did not find a statement on the vendor's own pages and would rather leave it blank than guess.

Questions to ask before relying on any AI answer

Both UpToDate Expert AI and OpenEvidence ground their answers in specific content, which is the right design. It still helps to read any AI-generated answer with a few questions in mind:

• What is it grounded in? An authored library, licensed journals, or the open web? The answer changes how much checking it needs.
• Can you open the source? A citation is only useful if you click it and the source says what the answer says.
• Is the answer about this patient? A question typed into a reference tool loses the context of the chart: prior results, medications, what was already done. The answer may be correct in general and wrong for the person in front of you.
• What happens next? Prose answers stop at the answer. Someone still has to turn it into orders, a referral and a follow-up plan, and that step is where omissions creep in.

That last question is the gap a decision-support API is designed for. It is not a better answer engine. It starts from the note, so the context is already there, and it ends with structured items rather than prose, so the plan does not have to be retyped.

Which to use

• You want to understand a topic and cite a graded recommendation: UpToDate.
• You want a quick, cited answer and cost matters: OpenEvidence. It is free for US clinicians, and that is hard to argue with.
• You want the next steps in the chart, coded, without retyping: a decision-support API such as Pogosh.
• You run an EHR or digital health product: compare UpToDate Connect, which delivers reference content and AI answers grounded in it, with an API that returns coded orders. They solve different integration problems.

Many clinicians will reasonably use two of the three. The reference tools help you think about the patient. The API helps the chart carry out what you decided. Pogosh's output, like the others', is advisory: a clinician reviews it and can override all of it.