NextGen Ambient Assist

Graded on the platform not algorithm precedent already applied to ModMed, Elation Health and Oracle Health in this category. Ambient Assist is a module of the NextGen EHR, activated through a NextGen account representative, and no practice selects NextGen because of it.

The grade describes the mechanism rather than the quality of the tool: the module itself is genuinely generative, but the moat is the ambulatory installed base and the 26 specialty template library, both of which predate the AI and would survive its removal.

The most conservative posture among the EHR native scribes in this index, and it earns the grade on a structural difference rather than a stated policy. The note is placed in the chart explicitly pending provider review, and codes, medications and orders arrive as SUGGESTIONS rather than pre filled order objects, which is a materially lower risk surface than the ambient order drafting shipped by Oracle Health and Sunoh.ai.

NextGen also states in its own materials that clinical validation and oversight are essential for reliability, which is a vendor conceding the limits of its own output. Held at B rather than A because no confidence threshold, acceptance rate or edit burden figure is published.

Publishes a headline accuracy figure of over 90 percent, which is more than several competitors offer, but never defines it. There is no statement of what was measured, against what reference standard, on how many encounters, or in which specialties, so the number cannot be compared with anything or falsified. Vendor sourced time saving claims are also internally inconsistent, appearing as 1.5 to 2 hours per day in some materials and 2.5 hours per day in others. An undefined accuracy percentage is a marketing figure rather than a benchmark.

Nothing published identifies any party in the chain. No foundation model provider, model class or version is named, no hosting or cloud arrangement is described for this product, and no sub processor list was located in two passes.

The product is delivered inside an enterprise electronic health record, and vertical delivery of that kind often means a short chain in practice, but a chain inferred from the delivery model is not a disclosed one and a buyer cannot confirm from anything public whether encounter content stays within the vendor's own systems. The stewardship disclosures are better than this axis and they point at the shape of the gap rather than filling it.

Transcripts are described as temporary and used only to generate the structured note, and documentation is stated to flow into the enterprise record rather than persisting on the device, which describes how content is handled without saying who handles it. Ask for a sub processor list scoped to the ambient capability, and for a written statement of whether any third party model provider is invoked in producing the note.

Vendor reported time savings and customer testimony only. No peer reviewed publication, no controlled comparison, no independent evaluation and no third party performance rating located in this pass. Graded C on the standing precedent that adoption and satisfaction claims do not substitute for evidence of benefit.

Better articulated than most in this category. NextGen states that conversations become temporary transcripts used only to generate the structured note, and that documentation flows into the Enterprise EHR rather than persisting on the mobile device, which is a purpose limitation and a data location statement rather than a generic assurance.

Its named control set also includes patient consent alongside encryption, secure storage, access controls and audit trails, and consent is a control very few scribes in this index mention at all. Held at B because a formal commitment that customer audio and transcripts are never used for model training is still not stated in those words.

Sold as HIPAA covered software within an existing NextGen enterprise agreement, with encryption, access controls and audit trails named. Terms are contracted through the account relationship rather than published for inspection.

One correction to the earlier assessment: a trust page does exist. What it publishes does not do what a trust centre normally does.

The page describes the security posture of the cloud provider hosting the platform, listing that provider's adherence to health privacy, HITRUST, SOC, ISO and payment card standards, alongside its physical data centre security, regional redundancy and encryption capabilities. Those certifications belong to the infrastructure supplier. They establish that the platform runs on well certified infrastructure. They do not establish that this vendor holds a report in its own name, covering its own systems, its own personnel, its own access controls, or this module specifically.

This index applies that distinction consistently and it matters here as much as anywhere. Certification demonstrably existing somewhere in the stack is not the vendor's attestation. A buyer inherits the cloud provider's controls over physical and virtual infrastructure and inherits nothing about how the vendor operates on top of it.

No named or dated attestation held by this vendor, and none specific to the ambient documentation module, was located. The company's own description elsewhere refers to supporting rigorous industry and regulatory standards without naming one, which is the same non attestation language this index tracks across the category.

A small tell belongs alongside: the standards list on that page separates the payment card industry standard and data security standard as though they were two different things. A compliance list assembled carelessly is weaker evidence than a short one assembled precisely.

Ask which report this vendor holds in its own name, of which type, covering which period, and whether the ambient module falls inside its scope.

No clearance claimed and none required for ambient documentation. The base position holds: the system drafts, the clinician reviews and signs.

The scope has moved since the earlier assessment, and the vendor's own framing is the clearest evidence of it. The company describes the product as offering decision support, and its president has described the capability as generating recommendations on diagnosis codes, lab orders and imaging orders by referencing coding datasets against the captured note. Trade coverage of the same announcement filed it under clinical decision support.

Two boundaries follow. Diagnosis code recommendation is the reimbursement boundary, since the codes proposed determine what gets billed. Lab and imaging order recommendation is a different and larger step, because an order is an action taken on a patient rather than a description of one, and a system proposing which tests to run is participating in the clinical decision rather than recording it. The vendor's material also describes the in visit workflow extending to prescribing.

One thing deserves crediting. The mechanism is stated rather than obscured: recommendations are described as derived by referencing established code sets against the captured note. Naming the source makes the output more inspectable than an unexplained suggestion, and the reasoning that keeps clinical decision support outside device regulation depends on a professional being able to review the basis of a recommendation. A vendor that says where its recommendations come from is closer to satisfying that than one that does not.

Ask which modules are enabled at the version being bought, and where the clinician's confirmation sits for orders specifically as distinct from for the note.

Markets appear to be United States only, with English and Spanish documentation.

Partial rather than absent, which is why this is C rather than Not Rated. NextGen does state openly that clinical validation and oversight are essential for reliability, and it names patient consent as part of its control set, both of which are more than several competitors offer.

What is missing is anything about performance variation: no fairness statement, no subgroup analysis, no accent or dialect disclosure, and no acknowledgement that speech models degrade unevenly across patient populations.

A number is published, which is the beginning of accountability and is more than several competitors offer, but it is published in a form that cannot be tested. The stated figure is accuracy of over 90 percent, with no statement of what was measured, against what reference standard, over how many encounters or in which specialties. Without a definition it is a marketing figure rather than a commitment, because there is no way for a customer to establish that it was not met.

A buyer should also read the number itself rather than the reassurance attached to it: better than 90 percent, undefined, is consistent with roughly one element in ten being wrong, and whether that means a word, a sentence or a whole section changes what the review burden actually is.

Vendor sourced time saving claims are internally inconsistent as well, appearing as 1.5 to 2 hours per day in some materials and 2.5 hours per day in others, which is a candour signal on the same set of published claims. Against that, one genuine credit belongs here rather than only on stewardship. Patient consent is named as part of the control set, and consent is the mechanism by which the recorded person is treated as a party with a say rather than as a data source. Very few vendors in this lane mention it at all. No warranty, indemnity or remediation commitment was located. Ask for the accuracy definition, the sample and the specialty breakdown.

Deep inside NextGen and unavailable outside it. Built into NextGen Mobile and writing directly into the NextGen Enterprise chart with no copy and paste step, which is the strongest possible fit for a NextGen site and irrelevant to anyone else.

Note that the interoperability asset usually credited to NextGen, the Mirth Connect integration engine supporting HL7v2, FHIR R4 and C-CDA, belongs to the parent platform rather than to this module, and third party scribes hold certified NextGen integrations of their own, so native does not automatically mean deepest here.

Better established than previously recorded, though the questions this axis asks first remain open.

The hosting provider is now named: the platform runs on a major public cloud, with the vendor citing that provider's multi region and availability zone architecture and its encryption of data at rest and in transit. Capture happens through the vendor's own mobile application, and integration into the record runs over a modern interoperability interface.

Naming the cloud is not the same as answering residency. No hosting region is stated for this module, no residency option is offered, and no subprocessor list was located. The cloud provider's regional footprint is described as a property of that provider rather than as a commitment about where a given customer's data sits.

More importantly for an ambient scribe, nothing establishes where inference runs. Whether encounter audio and transcript are processed by a third party model service, which provider that would be, and what it retains are all unanswered. The product now generates diagnosis code and order recommendations by referencing coding datasets, so the pipeline does considerably more than transcribe, and the question of which components run where is correspondingly larger than it was.

The multilingual capability adds a further reason to ask. Spanish language documentation is offered, and a vendor documenting encounters in more than one language is likely serving populations whose data protection expectations differ.

Ask for the hosting region, whether it can be pinned by contract, the subprocessor list, and specifically which model provider processes the encounter.

No published rate card for the module. Activation runs through a NextGen account representative and pricing is negotiated by practice size and contract, so the ambient line item is bundled inside an EHR relationship reported by third parties at roughly 150 to 500 US dollars per provider per month for the platform overall. That platform figure is not the price of this module and should not be read as one.

Ambulatory only, matched to the NextGen base of independent and specialty practices, with the parent platform carrying 26 specialty template sets. The open question a buyer should press is whether the AI is tuned per specialty or simply writes into specialty templates: third party reviews position specialty tuned scribes as the better fit for high complexity NextGen practices such as orthopaedics, cardiology and gastroenterology, which suggests the model is general purpose even where the templates are not. No inpatient or emergency coverage and no published language coverage.