Patients.app

The models do the work. Retrieving records from outside organisations, scanning thousands of pages across EMRs, PDFs and scanned documents, screening them against a centre's own criteria, surfacing contraindications and generating intake, anaesthesia and review committee reports are all model tasks, and there is no platform, system of record or services organisation underneath them. The human elements described, nursing review and the trained transplant recipient support layer, sit downstream of the AI rather than substituting for it.

Genuine human structures sit downstream in both products, which is why this is not lower. Perioperative output speeds nursing review rather than replacing it, transplant output is packaged as reports FOR a review committee, a human body that makes the candidacy decision, clinical oversight is attributed to a named physician, and every result links to its source so a reviewer can check any assertion. Held at B for three reasons. No confidence signal, threshold or abstention behaviour is published anywhere. The system automatically FILLS UNOS AND TIEDI FORMS, meaning generated content enters national transplant registry systems, and nothing describes what a human verifies before submission or what happens if a field is wrong. And highlighting strong candidates shapes what a committee sees before it deliberates, which is influence exercised upstream of the gate rather than checked by it. Ask what is verified before a form is submitted and before a candidate list reaches committee.

One real property and no measurement. Every result links back to its source, which the company frames as making context and authenticity clear, and that is the right instinct for a product whose output feeds a committee decision. Beyond it nothing: no model or model family named, no accuracy figure for criteria screening or contraindication detection, no evaluation methodology and no model card. For a product that flags what is MISSING from a record, the number that matters is how often it misses something that was missing, and that is unpublished.

One efficiency claim and nothing else. The company reports 30 to 60 minutes saved per case on surgical readiness screening, with no baseline, method or reference organisation attached. No customer is named, no funding was located, no case study exists, and no independent evaluation was found. For the transplant product in particular, where the outputs feed a committee that decides candidacy, the absence of any published accuracy or concordance data is the gap that matters most.

No retention period, training use statement or de identification posture was located. Not Rated reflects absent retrieval. The surface is larger than the product's narrow use cases suggest: the company states it finds patient data across the country and taps into external systems to retrieve records from referring sites, so it assembles records from organisations that are not the customer and have no relationship with the vendor. Establish what is retained after a case is decided, since a declined transplant candidate's assembled record has no ongoing clinical purpose.

No HIPAA compliance statement and no business associate agreement terms were located. Not Rated reflects absent retrieval. The multi party question is sharper here than usual because records are retrieved from referring sites rather than only from the customer, so establish the legal basis for that retrieval and which agreements cover it.

No SOC 2, HITRUST, ISO 27001 or other attestation was located, and no trust centre or security page was found. Not Rated reflects absent retrieval.

No FDA clearance, device authorisation or regulatory analysis was located. Not Rated reflects absent retrieval, and the more relevant regulatory frame here is not FDA at all. Transplant centres operate under Organ Procurement and Transplantation Network policy and are audited on data submitted through UNOS and TIEDI, so a product that fills those forms sits inside a compliance regime with its own accuracy obligations and its own consequences for error. Ask what the vendor's position is on data accuracy attestation for registry submissions, and who is accountable if submitted data is wrong.

The grade describes disclosure, and this is the most consequential disclosure gap found anywhere in this lane. The product highlights strong transplant candidates against a centre's guidelines, surfaces contraindications and prioritises who reaches a review committee. Access to transplantation is one of the most extensively documented sites of inequity in American medicine, with well established disparities by race, insurance status, geography and referral pattern, and much of that inequity operates precisely through referral, evaluation and listing decisions rather than through allocation once listed. A model trained on historical listing decisions and applied to candidate prioritisation inherits whatever patterns those decisions contained, and a model reading records assembled from referring sites inherits whatever unevenness exists in what was documented about whom. None of this is an allegation about this product, which may perform evenly; the point is that NO SUBGROUP OR DEMOGRAPHIC PERFORMANCE DISCLOSURE OF ANY KIND WAS LOCATED, and this is the single application in this index where that absence carries the highest stakes. Published subgroup performance would be a genuinely significant disclosure and the first thing to ask for. Credit where due: source linking, a named clinical overseer and a peer support layer of trained transplant recipients all indicate a company thinking about the human side of the process.

Real capability described, nothing named. The platform plugs into the customer's EMR and separately retrieves records from external systems and referring sites nationally, and it ingests EMR data, PDFs and scanned documents, which is the right ingest breadth for a referral driven workflow where records arrive in whatever form the sending organisation used. It also writes into UNOS and TIEDI. Graded C because no EHR vendor, exchange network, integration standard or certification was located anywhere, so an organisation cannot establish what is supported or how retrieval actually works without asking.

No hosting model, cloud provider, region, residency commitment or customer hosted option was located. Not Rated reflects absent retrieval.

No price, tier or pricing mechanism was located. Not Rated is the house convention for absent pricing rather than a low grade. The commercial arguments offered are avoided case cancellations, staff time saved and, on the perioperative side, captured codes and reduced denials, all of which describe claimed value rather than cost.

Narrow by design and genuinely deep within the narrow parts, which is rarer than breadth in this category. Two settings are addressed and both with instrument level work rather than generic summarisation. Perioperative covers surgical readiness screening against centre specific criteria, intake and anaesthesia report generation, and clearance and laboratory gap detection. Transplant covers candidate identification and prioritisation, contraindication surfacing, review committee report generation and completion of UNOS and TIEDI registry forms. Filling national registry forms is instrument work of the same order as registry abstraction. Graded B rather than A because only two settings are covered and neither is evidenced at a named centre.