Buyer Guide

Best clinical decision support AI

Every clinical decision support vendor in the index, graded on the same 15 axes with a source and a date on every judgement. No ranked order, because ranking one requires deciding which failure matters most to you. Instead: what actually counts as decision support, the axis where clearance separates real claims from asserted ones, the axis where nobody clears the bar, and shortlists cut by the thing you cannot afford to get wrong.
Last ReviewedAugust 16, 2026

The short answer

  1. 01There is no single best clinical decision support system, and any list that publishes one has chosen your weighting for you.
  2. 02The AI Health Index grades 148 vendors that put a decision support output in front of a clinician. Only 26 of them sell decision support as their primary product. The other 122 reach the clinician inside imaging, medication, monitoring, diagnostics or reference software, which is the first thing most comparisons of this category get wrong.
  3. 0346 earn the top grade on FDA and Regulatory Status and 47 earn it on Clinical and Operational Evidence, but only 27 hold both. Clearance and evidence are different claims and this is the category where the gap between them matters most.
  4. 04Not one vendor earns the top grade on AI Liability and Recourse. Across all 554 vendors in this index, in every category, exactly 1 does.
  5. 05The category is also close to silent on three things a buyer asks early: 4 publish pricing, 4 publish performance by subgroup, and 4 name the model they are built on.
  6. 06The widest record holds a top grade on 8 of the 15 axes and the median holds 2, so no vendor clears every bar. Pick on your failure mode, not on a leaderboard.

What counts as clinical decision support, and why the boundary decides your shortlist

A buyer asking this question is usually shown a list of products that answer clinical questions, and only some of them are decision support. The AI Health Index draws the line on a testable property rather than on marketing language. A decision support product answers what to do for this patient, takes the chart as input, and inherits the evidentiary and regulatory obligations a patient specific output carries. A reference product answers what the evidence says, needs little or no patient context to do it, and several vendors in that category process no protected health information at all.

That distinction is not academic. It decides whether clearance is a live question, whether a business associate agreement is required, and whether subgroup performance is something you have to ask about. Products that genuinely do both are graded on both and cross listed rather than being forced onto one side.

Applying that rule leaves 148 vendors, and their composition is the finding: only 26 are primarily decision support companies. Counts are of vendors, as of August 31, 2026.

Where the clinical decision support roster is primarily listed in this index
Primary listing Vendors
Radiology & Imaging AI 29
Clinical Decision Support 26
Medication Safety & Prescribing 15
Clinical Reference & Evidence 14
Diagnostics & Genomics 13
Inpatient Deterioration & Risk Monitoring 11
Digital Pathology AI 9
Clinical Trials AI 6
Behavioral Health AI 5
Value Based Care Intelligence 4
Clinical Summarization & Chart Review 3
RCM & Prior Auth AI 3
Remote Monitoring & Chronic Care 3

Categories contributing more than two vendors. A vendor appears here once, under the category it is primarily listed in, and counts toward this roster because decision support is either its product or a documented part of it.

Read that table as a procurement warning rather than as taxonomy. Most decision support does not arrive through a decision support purchase. It arrives inside an imaging contract, a medication safety module, a monitoring deployment or a reference subscription, which means it is frequently bought by a committee that never evaluated it as decision support at all and never asked the questions this page is built around.

It also means a category level comparison is the wrong instrument on its own. If your candidate is primarily an imaging product, read it against the imaging roster too, and use the comparison view to put two records side by side on all 15 axes.

Where the category is strong and where it is thin

Every vendor in the index carries a grade on all 15 axes before it is published at all, so this table compares the same questions answered for every vendor rather than the results of uneven research.

Grade distribution across the clinical decision support roster, by capability axis
Axis A B C D
AI Centrality 92 24 22 10
Clinical and Operational Evidence 47 52 45 4
FDA and Regulatory Status 46 21 79 2
Autonomy and Oversight Model 36 95 16 1
Model and Technology Transparency 28 71 45 4
EHR and Interoperability Depth 24 72 48 4
Setting and Specialty Coverage 21 91 36 0
Security Certifications and Trust Center 15 27 81 25
Deployment Model and Data Residency 10 42 92 4
HIPAA and BAA Posture 7 33 88 20
AI Safety and PHI Stewardship 5 40 99 4
Commercial Transparency 4 29 82 33
AI Governance and Bias Disclosure 4 35 85 24
Model Supply Chain Disclosure 4 20 69 55
AI Liability and Recourse 0 51 59 38

The top of the table is what the category sells: 92 vendors earn the top grade on how central the model is to the product, and both of the axes a clinical buyer would name next, evidence and regulatory status, carry real numbers rather than token ones. This is a more mature answer than the same table produces for most categories in this index.

The bottom is what the category does not publish. Pricing, subgroup performance, model provenance and accountability sit at the floor, and those four are the questions a buyer cannot answer from a vendor website and will not be handed in a demo. They are worth taking into the room precisely because a prepared answer is unlikely.

Regulatory status is a real screen here, which is unusual in this index

In most categories the FDA and Regulatory Status axis records an absence. Ambient documentation drafts a note a clinician signs, so it sits outside device regulation and not one scribe vendor in this index earns a top grade on that axis, which is the expected answer rather than a warning sign.

Decision support is the exception, and it is the reason this page reads differently from the scribes guide. Here 46 vendors earn the top grade, and the products that carry clearance carry it because they make a patient specific claim that regulation treats as a device function. On this axis the grade separates rather than flattens, so a buyer can use it.

Two cautions before using it as your only filter. Clearance is not evidence of benefit in your setting: it establishes that a claim was reviewed for a stated intended use and population, which may not be yours. And an uncleared product is not automatically out of scope, because the non device exclusion for clinical decision support genuinely applies to some products here, and where a vendor asserts it the right question is on whose reading, since a clinician has to be able to independently review the basis of the output for that exclusion to hold.

The useful move is to require both claims at once. 27 of 148 vendors hold the top grade on regulatory status and published evidence together, and that intersection is a far better starting shortlist than either axis alone.

The axis where nobody clears the bar, and what it means for a patient specific output

Not one vendor in this category earns a top grade on AI Liability and Recourse, and 38 sit at the bottom grade. The strongest records here are vendors that publish terms at all, and those terms typically offer the service as is, disclaim warranties, and leave the clinician holding the decision.

Before reading that as a decision support failing, note the scale of it. Across all 554 vendors in this index, spanning every category, exactly 1 earns a top grade on that axis. It is the clearest single finding this index has produced and it is an industry position rather than a category one.

It lands harder here than anywhere else, though, and the reason is the output. A documentation error surfaces in a note a clinician reads and signs. A decision support error surfaces as a recommendation, a risk score or a suppressed alert that changes what happens to a patient, and it can be right on average while being wrong about a particular person. Accountability for that is not transferred by the standard contract.

The practical consequence is short and it belongs in the deployment plan rather than the negotiation. Decide what your review step is, who staffs it, and what it catches, then choose the product that fits it. A vendor that describes its oversight model clearly is easier to build that step around than one that scores well on everything else.

Shortlists by failure mode

Each list below is every vendor in the category holding the top grade on the named axes. They are not ranked, they are alphabetical, and a vendor appearing on none of them is not disqualified. It has not published what these axes ask for, which is a question to raise rather than a verdict.

Your exposure is a patient specific output

Regulatory status established and published clinical or operational evidence behind the claim. This is the cut most buyers think they are asking for when they ask who is best, and it is the one where this category actually separates.

Grade A on FDA and Regulatory Status and Clinical and Operational Evidence (27 of 148)

AgileMD, Aidoc, Anumana, ArteraAI, AZmed, Bayesian Health, Brainomix, Caristo Diagnostics, Cleerly, Cognivue, Cohere Health, DermaSensor, Eko Health, Etiometry, Eyenuk, Gleamer, Guardant Health, Heartflow, Implicity, Limbic, Lunit, Optellum, Prenosis, Qure AI, RapidAI, Ultromics, Viz.ai

Your exposure is whether it works on your population

Published evidence held together with a documented account of which settings, specialties and populations the product was built and validated for. A model that performed well somewhere is not the same claim as a model that performed well somewhere like you.

Grade A on Clinical and Operational Evidence and Setting and Specialty Coverage (11 of 148)

Aidoc, Atropos Health, Cohere Health, Etiometry, Implicity, Linus Health, Qure AI, Triomics, Ubie, Viz.ai, Xsolis

Your exposure is what the model does unattended

A documented account of what the system decides, what a clinician has to confirm, and what happens when it is unsure, held together with a published description of how the model actually works. Alerting behaviour is the failure mode this category is famous for.

Grade A on Autonomy and Oversight Model and Model and Technology Transparency (15 of 148)

Abstractive Health, AgileMD, Aidoc, Almanac Health, ArteraAI, Atropos Health, Bayesian Health, Canary Speech, DermaSensor, Dyania Health, Etiometry, Glass Health, Mendel, Triomics, xCures

Your exposure is the integration

Documented depth into the record systems you already run, with an external security attestation a counterparty can read. Decision support that cannot reach the chart it is reasoning about becomes a second screen nobody opens.

Grade A on EHR and Interoperability Depth and Security Certifications and Trust Center (4 of 148)

Abstractive Health, Cohere Health, Etiometry, NarxCare

Your exposure is the contract and the data

A signed business associate agreement on published terms plus that same external attestation. This is the narrowest list on the page, and the length of it is the finding rather than an accident of who was researched.

Grade A on HIPAA and BAA Posture and Security Certifications and Trust Center (2 of 148)

Abstractive Health, BrainCheck

Your exposure is who the model is wrong about

Published governance and disclosed performance by subgroup. A decision support output is patient specific, so a model that performs differently across populations produces different care rather than a different average, and almost nobody in this category publishes the breakdown.

Grade A on AI Governance and Bias Disclosure (4 of 148)

AgileMD, ArteraAI, Cognivue, Linus Health

You need a price before you can start a process

Published pricing a buyer can establish without contacting sales. Worth reading against the ambient scribe category, where this is one of the stronger axes. Here it is one of the weakest, so a quote is usually the only route and the first quote is rarely the last one.

Grade A on Commercial Transparency (4 of 148)

Abstractive Health, Artrya, BrainCheck, Guardant Health

If more than one of these is your failure mode, take the intersection yourself rather than looking for a vendor that appears on every list. Almost none do, which is the point of the next section.

Nobody is good at everything, and here the median is the story

The widest record in the category holds a top grade on 8 axes of 15. The median record holds 2. There is no vendor here that clears every bar, and a comparison built on the assumption that one exists will end in a tie broken by brand recognition.

A low count is not a verdict on a product. Several of the strongest clinical performers in this roster are narrow specialists that publish deeply on the two axes their buyers care about and say nothing on the rest, and they should not be read as worse than a platform that publishes shallowly on many.

What the spread does tell you is how many finalists to carry. Two or three vendors that clear your one non negotiable axis will produce a better process than ten that all look plausible on a feature grid, and it is a faster process too.

The full roster

Every clinical decision support vendor in the index, each graded on all 15 axes with a source and a date on every judgement. Inclusion is not purchasable and no vendor pays for placement or review.

Listed alphabetically. The figure is the number of axes on which the vendor holds an A, out of 15. It is a count, not a rating, and it is not a ranking.

Cite this

Citable summary

Self contained findings from this page, free to quote with attribution.

Most clinical decision support is not bought as clinical decision support

The AI Health Index grades 148 vendors that deliver clinical decision support, and only 26 of them sell it as their primary product. The other 122 deliver it inside imaging, medication safety, monitoring, diagnostics or reference software. The practical consequence is that decision support frequently arrives inside a contract for something else and is approved by a committee that never evaluated it as decision support at all. A health system auditing what is advising its clinicians should start from the products it already owns rather than from the decision support market.

Source: AI Health Index, August 2026

Regulatory status genuinely separates vendors here, and clearance still is not evidence

Clinical decision support is the category where FDA status does real work as a screen. 46 of the 148 vendors graded by the AI Health Index earn a top grade on FDA and Regulatory Status, against none at all in the ambient scribe category where the axis is structurally empty by design. The same axis therefore means opposite things in the two categories. Two cautions travel with a clearance. It establishes review against a stated intended use and population, which is not evidence the product works in yours. And the non device exclusion for decision support genuinely applies to some products here, so the live question is which position a vendor takes and on whose reading.

Source: AI Health Index, August 2026

Subgroup performance is the disclosure this category needs most and publishes least

Of the 148 clinical decision support vendors graded by the AI Health Index, 4 earn a top grade on AI Governance and Bias Disclosure, the axis that asks whether a vendor has published a bias or fairness evaluation with its methodology and the population it was run on. That scarcity matters more here than in most categories, because a decision support output is patient specific: a model that performs differently across populations does not produce a different average, it produces different care for different patients. Not one vendor in the category earns a top grade on AI Liability and Recourse, and 38 of 148 sit at the bottom grade, so a subgroup failure is also unlikely to carry a published remedy.

Source: AI Health Index, August 2026
Questions

Common questions

What is the best clinical decision support system?
There is no single best one, and the AI Health Index deliberately publishes no ranked order. Across 148 clinical decision support vendors graded on 15 axes, the widest record holds a top grade on only 8 of them and the median holds 2, so no vendor clears every bar. The useful question is which failure you cannot afford: regulatory status plus published evidence, evidence validated in your own setting and population, a documented oversight model, depth into your record systems, or disclosed performance by subgroup. Each returns a different and much shorter shortlist.
What is the difference between clinical decision support and a clinical reference tool?
What the product takes as input and what it claims. A decision support product answers what to do for this patient and takes the chart as input, which brings evidentiary and regulatory obligations with it. A reference product answers what the published evidence says and needs little or no patient context, which is why several reference vendors process no protected health information at all. The AI Health Index grades them as separate categories on that test and cross lists products that genuinely do both. The distinction decides whether clearance, a business associate agreement and subgroup performance are live questions for you.
Do clinical decision support tools need FDA clearance?
Some do and some do not, and this is the one category in the AI Health Index where that axis genuinely separates vendors. 46 of 148 earn the top grade on FDA and Regulatory Status. Products making a patient specific claim that regulation treats as a device function generally require clearance, while others assert the non device exclusion for clinical decision support on the ground that a clinician can independently review the basis of the output. Ask which position a vendor takes and on whose reading. Also note that clearance establishes review against a stated intended use and population, which is not the same as evidence that the product works in your setting.
Who is liable if a clinical decision support tool gets it wrong?
On published terms, in practice the clinician and the organization. Not one clinical decision support vendor in the AI Health Index earns a top grade on AI Liability and Recourse, and 38 of 148 sit at the bottom grade. Across all 554 vendors in the index, in every category, exactly 1 earns a top grade on that axis, so this is an industry wide position rather than a decision support one. Plan the clinical review step on the assumption that accountability stays with you.
How much does a clinical decision support system cost?
Almost none of them will tell you before a sales conversation. Only 4 of 148 vendors in the AI Health Index earn the top grade on Commercial Transparency, which measures whether a buyer can establish pricing from published sources. That is notably worse than the ambient scribe category, where published pricing is one of the stronger axes. Expect a quote to be the only route here, expect it to be scoped to your volume and integration, and treat the first one as an opening position.
How many clinical decision support vendors are there?
The AI Health Index tracks 148, each graded on the same 15 axes, current as of August 31, 2026. Only 26 of those sell decision support as their primary product. The remaining 122 deliver it inside imaging, medication safety, monitoring, diagnostics or reference software, and a buyer evaluating one of those is still evaluating decision support whether or not the contract says so.
How were these clinical decision support vendors evaluated?
Every vendor carries a grade on all 15 capability axes under the AI Health Index grading framework, with a source basis and a date on each judgement, and a record with any gap is withheld rather than published in part. Grades measure what a counterparty can verify from published evidence rather than the vendor's description of itself, so a low grade is a statement about disclosure rather than a finding that a capability is absent. The AI Health Index publishes no overall score, because the weighting belongs to the buyer. The framework is published in full and is designed to be reused on vendors the index does not cover.
Next

Take it further

The shortlists above narrow a field. The comparison view puts two records side by side on all 15 axes, which is the only way to see where two plausible finalists actually differ, and it matters more here than in most categories because so many candidates are primarily listed somewhere else.

If you are running your own evaluation, the framework behind these grades is published in full and is designed to be reused on vendors this index does not cover, including ones that appear after this page was last reviewed.