AI Health Index: Health System AI Platforms changes https://aihealthindex.io/categories/health-system-ai-platforms Material product changes at Health System AI Platforms vendors, tracked by AI Health Index. Every entry is dated and cited to a public source. en-us Free to reuse with a visible link to aihealthindex.io. Terms: https://aihealthindex.io/use-this-data Wed, 23 Sep 2026 12:00:00 GMT 720 https://aihealthindex.io/icon-192.png AI Health Index: Health System AI Platforms changes https://aihealthindex.io/categories/health-system-ai-platforms Aidoc received FDA Breakthrough Device Designation for CARE Chest X-Ray Triage, built on its CARE foundation model, covering triage of… https://aihealthindex.io/changelog/aidoc aihealthindex.io:change:6ab85e9bd92e5616ac6dc814 Wed, 23 Sep 2026 12:00:00 GMT Regulatory / FDA Radiology & Imaging AI Clinical Decision Support Health System AI Platforms Aidoc received FDA Breakthrough Device Designation for CARE Chest X-Ray Triage, built on its CARE foundation model, covering triage of pneumomediastinum and lobar or lung collapse. It is Aidoc's third breakthrough designation in just over a year, after CARE Multi-Triage Body CT and CARE First Read for Chest X-Ray. The 510(k) is under FDA review and the product is not yet available for sale in the United States.

Why it matters: A breakthrough designation can speed FDA review but does not clear the product. Radiology groups interested in foundation model triage for chest films should treat this as a roadmap signal and ask Aidoc for expected clearance timing.

Impact: Medium. Verification: Verified. Type: Regulatory / FDA.

Evidence: Vendor announcement

Source: AI Health Index change log. Free to reuse with a link back. Terms.

]]> Alcidion: Miya Precision 7.11.0 introduces a three tier restricted access model for patient records: full access, break glass access that requires… https://aihealthindex.io/changelog/alcidion aihealthindex.io:change:6ab90c10ee3c2977980e6539 Mon, 21 Sep 2026 12:00:00 GMT Security / compliance Hospital & Unit Operations Clinical Decision Support Health System AI Platforms Miya Precision 7.11.0 introduces a three tier restricted access model for patient records: full access, break glass access that requires justification via an individual PIN with audit tracking, and no access. Alcidion states the design supports NHS safeguarding principles.

Why it matters: Privacy and information governance teams get record level access control with an audited break glass path, which matters for restricted and safeguarding sensitive patients.

Impact: Low. Verification: Verified. Type: Security / compliance.

Evidence: Vendor documentation

Source: AI Health Index change log. Free to reuse with a link back. Terms.

]]> Alcidion's Miya Precision 7.11.0 adds a native inpatient admissions workflow, completing its admission, transfer, leave and discharge set… https://aihealthindex.io/changelog/alcidion aihealthindex.io:change:6ab90c10ee3c2977980e6538 Mon, 21 Sep 2026 12:00:00 GMT EHR / interoperability Hospital & Unit Operations Clinical Decision Support Health System AI Platforms Alcidion's Miya Precision 7.11.0 adds a native inpatient admissions workflow, completing its admission, transfer, leave and discharge set, with one way or two way integration to the Patient Administration System so clinicians no longer need to open the PAS. The release also adds Miya Vitals, for capturing observations on charts defined per care area such as ICU, ED and general wards with validation checks and warning thresholds, and Dynamic Fluid Balance Management, which calculates fluid restriction limits from patient weight.

Why it matters: Trusts running a separate PAS can manage the full inpatient encounter in Miya Precision while keeping the PAS in sync, which cuts double entry. Vitals capture is manual entry only in this release; Alcidion states capture from bedside monitors is planned for a future release.

Impact: Medium. Verification: Verified. Type: EHR / interoperability.

Evidence: Vendor documentation

Source: AI Health Index change log. Free to reuse with a link back. Terms.

]]> DeepHealth received FDA 510(k) clearance for Chest XRay, a computer aided detection tool built on a foundation model that detects and… https://aihealthindex.io/changelog/deephealth aihealthindex.io:change:6aaeaddaaaa02078636c9caa Fri, 18 Sep 2026 12:00:00 GMT Regulatory / FDA Radiology & Imaging AI Health System AI Platforms Hospital & Unit Operations DeepHealth received FDA 510(k) clearance for Chest XRay, a computer aided detection tool built on a foundation model that detects and localizes abnormalities on chest radiographs. It is the next version of the technology DeepHealth acquired with Gleamer, it is commercially available in the US now, and existing customers are eligible for the update.

Why it matters: A foundation model clearance matters because one model covers many findings, rather than one narrow algorithm per finding. Radiology groups should ask exactly which findings the 510(k) covers, since marketing for foundation models tends to run ahead of the cleared indications.

Impact: High. Verification: Partially Verified. Type: Regulatory / FDA.

Evidence: Trade press

Source: AI Health Index change log. Free to reuse with a link back. Terms.

]]> CMS approved a New Technology Add-on Payment for Bayesian Health's FDA cleared continuous AI sepsis monitor, creating Medicare payment… https://aihealthindex.io/changelog/bayesian-health aihealthindex.io:change:6a9c312c04c538181acf1b3d Wed, 02 Sep 2026 12:00:00 GMT Regulatory / FDA Inpatient Deterioration & Risk Monitoring Clinical Decision Support Health System AI Platforms CMS approved a New Technology Add-on Payment for Bayesian Health's FDA cleared continuous AI sepsis monitor, creating Medicare payment support for health systems running the platform.

Why it matters: This is the rarest event in this index, which is an AI tool acquiring a reimbursement pathway rather than only a clearance. Clearance establishes that a product may be used and says nothing about who pays for it, and the absence of a payment mechanism is the reason most cleared clinical AI stalls after the pilot. An NTAP moves the conversation from the innovation budget to the operating one.

Impact: High. Verification: Verified. Type: Regulatory / FDA.

Evidence: Vendor announcement

Source: AI Health Index change log. Free to reuse with a link back. Terms.

]]> LeanTaaS acquired Aidin and is folding discharge readiness intelligence and post acute placement into iQueue for Inpatient Flow, extending… https://aihealthindex.io/changelog/leantaas aihealthindex.io:change:6a9c312c04c538181acf1b3b Tue, 01 Sep 2026 12:00:00 GMT Acquisition / corporate Hospital & Unit Operations Health System AI Platforms LeanTaaS acquired Aidin and is folding discharge readiness intelligence and post acute placement into iQueue for Inpatient Flow, extending the platform from admission through transition out.

Why it matters: LeanTaaS has sold capacity optimization inside the hospital walls for a decade, and the constraint it kept hitting was a bed that cannot be freed because a post acute placement has not been arranged. Buying the placement workflow rather than integrating with one is a statement about where it thinks the remaining length of stay savings are.

Impact: High. Verification: Verified. Type: Acquisition / corporate.

Evidence: Vendor announcement

Source: AI Health Index change log. Free to reuse with a link back. Terms.

]]> Mercy and Aidoc released a white paper, commissioned by AVIA, reporting on five months of AI deployment across the Mercy health system. https://aihealthindex.io/changelog/aidoc aihealthindex.io:change:6a92e5ef75bbcbbe469c6fee Tue, 25 Aug 2026 12:00:00 GMT Clinical evidence Radiology & Imaging AI Clinical Decision Support Health System AI Platforms Mercy and Aidoc released a white paper, commissioned by AVIA, reporting on five months of AI deployment across the Mercy health system. The review documents more than 50,000 new clinical findings surfaced in that window and tracks the associated changes in speed of diagnosis and time to treatment. The scale is the notable part: this is a multi hospital deployment reporting aggregate output rather than a single site pilot.

Why it matters: A five month figure from a named health system gives buyers something to model against, which vendor accuracy claims do not. The number to interrogate is what counts as a new clinical finding, since that definition determines whether 50,000 represents meaningful catches or a high volume of flags a radiologist would have reached anyway. AVIA commissioning the work makes it more independent than a vendor case study and less independent than peer review, which is roughly where its evidentiary weight should sit.

Impact: Medium. Verification: Partially Verified. Type: Clinical evidence.

Evidence: Trade press

Source: AI Health Index change log. Free to reuse with a link back. Terms.

]]> Bunkerhill Health: CMS established a national billing code and associated payment under the Hospital Outpatient Prospective Payment System for algorithmic… https://aihealthindex.io/changelog/bunkerhill-health aihealthindex.io:change:6a5d3fdd0b03892a4bc1369a Wed, 15 Apr 2026 12:00:00 GMT Regulatory / FDA Health System AI Platforms Clinical Decision Support RCM & Prior Auth AI CMS established a national billing code and associated payment under the Hospital Outpatient Prospective Payment System for algorithmic analysis of coronary artery calcium and aortic valve calcium on chest CT, effective April 1, 2026. The company separately received FDA clearance for Bunkerhill Contrast CAC and Bunkerhill Contrast AVC, which it states are the first AI algorithms cleared to detect and quantify coronary artery calcium and aortic valve calcium on contrast enhanced, routine non gated chest CT, extending prior clearances that covered non contrast chest CT.

Why it matters: Two things changed here and the second matters more. FDA clearance on contrast enhanced non gated chest CT means the algorithm can run opportunistically on scans a health system is already acquiring for other reasons, rather than requiring a dedicated gated cardiac study. That converts an existing imaging volume into a screening surface without new acquisition cost. The CMS billing code is the rarer event: most healthcare AI carries no reimbursement pathway at all and must be justified purely on internal ROI, so a national OPPS payment moves this from a cost center argument to a billable service line. Buyers evaluating this platform should separate the two economic questions, since the reimbursement applies to specific algorithmic analysis and not to the cost of licensing the platform itself.

Impact: High. Verification: Verified. Type: Regulatory / FDA.

Evidence: Vendor announcement

Source: AI Health Index change log. Free to reuse with a link back. Terms.

]]> The FDA cleared Aidoc's comprehensive abdomen CT triage solution, powered by its self developed CARE foundation model, bringing 11 newly… https://aihealthindex.io/changelog/aidoc aihealthindex.io:change:6a5d4a29fdd2ff3590934a75 Wed, 21 Jan 2026 12:00:00 GMT Regulatory / FDA Radiology & Imaging AI Clinical Decision Support Health System AI Platforms The FDA cleared Aidoc's comprehensive abdomen CT triage solution, powered by its self developed CARE foundation model, bringing 11 newly cleared indications together with three previously cleared into a single 14 indication workflow. The company states this is the first FDA clearance of a double digit set of acute indications powered by one foundation model. In the FDA reviewed pivotal study the new indications reported a mean sensitivity of 97 percent and mean specificity of 98 percent, and the company reports roughly an order of magnitude reduction in false alerts compared with leading single condition tools.

Why it matters: The operationally decisive number here is not the sensitivity, it is the false alert rate. Triage AI fails in practice when radiologists learn to ignore it, and single condition tools deployed side by side compound that problem because each one alerts independently. A reported order of magnitude reduction in false alerts, if it holds in a buyer's own case mix, is what determines whether the tool survives past month three. Two things to establish in evaluation: that the cleared indications match the acute findings actually driving delays in your emergency department, and how the platform governs models it did not build, since aiOS also hosts third party AI and the governance layer is doing work across all of them.

Impact: High. Verification: Verified. Type: Regulatory / FDA.

Evidence: Vendor announcement

Source: AI Health Index change log. Free to reuse with a link back. Terms.

]]>