Healthplus.ai

The models are the product and are regulated as such. PERISCOPE is certified as software as a medical device in its own right, the company is effectively single product, and removing the prediction leaves nothing saleable. No platform layer, no data aggregation business and no services wrapper dilutes the claim. This is one of the cleanest centrality A cases in the category.

Adjunctive by design and by certification. The output is a risk probability rendered as one of three traffic light categories inside the existing EHR workflow, and clinicians decide what follows. Hospitals build their own pathways around the categories, which puts the action threshold with the institution rather than the vendor, the property that earned Affineon and Haystack credit. THE EXPOSURE IS THE LOW RISK CATEGORY, and it is the same structure flagged on CLEW's low risk model. A clinician quoted in the company's own material describes low risk as meaning more confidence when discharging, and the company markets safer discharge directly. A false low risk label does not generate a visible error, it quietly accelerates a discharge, and nobody is positioned to notice the patient who returns to another hospital. Held at B rather than A because no false negative rate at the discharge relevant threshold is surfaced in customer facing material, even though the underlying paper reports the analysis that would support one.

Among the strongest in the index, and the reason is calibration. The model class is named plainly as XGBoost rather than described as proprietary AI, the input space is stated at roughly 50 preoperative and intraoperative clinical parameters drawn from existing record data, and the two prediction horizons of seven and 30 days are explicit. DECISIVELY, THE PEER REVIEWED PAPER REPORTS CALIBRATION SLOPE, INTERCEPT AND PLOTS ALONGSIDE DISCRIMINATION. Almost nothing in this index publishes calibration at all, and without it a risk percentage cannot be interpreted as a probability, which is exactly what a traffic light category asks a clinician to do. The development, validation and local updating methodology is fully described and reproducible in outline. Held short of perfection only by the absence of a published feature list and a model card, though the parameter count and data sources are given.

THE BEST EVIDENCE IN THIS CATEGORY. van der Meijden SL, van Boekel AM, Schinkelshoek LJ et al., The Lancet Regional Health Europe, published 5 December 2024, doi 10.1016/j.lanepe.2024.101163. 253,010 surgical procedures, data from 2014 to 2023, multiple surgical specialties, models developed at one hospital and validated and updated at two further hospitals across the Netherlands and Belgium, with the two most recent years held out for temporal validation. WHAT SEPARATES IT FROM EVERYTHING ELSE ASSESSED HERE IS THE OUTCOME MEASURE SET: discrimination, calibration, AND CLINICAL UTILITY THROUGH DECISION CURVE ANALYSIS WITH NET BENEFIT. Decision curve analysis answers the question AUROC cannot, namely whether acting on the model at a given threshold is better than not acting, weighing the relative harm of false positives against false negatives. That is the analysis this category most needs and this is the only vendor assessed that has published one. FUNDING IS NOT FROM THE VENDOR: the study was supported by a REACT EU grant from the European Regional Development Fund. Conflicts are disclosed, with the chief executive a major shareholder and two authors employees, alongside a substantial independent academic author list. ONE CAUTION RECORDED: partner and marketing material reduces all of this to accuracy above 90 percent, which for an outcome the company itself puts at roughly one in five patients is close to what predicting no infection every time would achieve. The paper is the evidence; the accuracy figure is not.

No privacy policy, data processing agreement, retention statement or training use disclosure was located. Not Rated means no public evidence was found rather than evidence of weakness, and the bar is different here: as an EU medical device the product operates under GDPR, which imposes obligations that do not depend on vendor publication. One design property is worth noting because it reduces exposure directly: PERISCOPE reuses data already present in the record and requires no new measurements or additional data collection. Open questions for a buyer: where processing occurs, whether hospital data is used in the local model updating the company describes, and whether any data leaves the institution for that purpose.

GRADED NOT RATED BECAUSE THE AXIS DOES NOT MAP, not because the vendor failed a test. This is an EU product operating in the Netherlands, Belgium and Germany, where the governing framework is the GDPR and the EU Medical Device Regulation, and a business associate agreement is not the relevant instrument. Same handling as the WELL AI Inbox Admin record, where PIPEDA and provincial Canadian legislation applied instead. Say so rather than grading a vendor down for failing a test that does not apply. Recorded separately: no US deployment was identified, and the company has stated it is pursuing FDA authorisation, at which point this axis would become live and should be reassessed.

No SOC 2, ISO 27001, trust centre or report request path was located. Not Rated means no public evidence was found. THE DISTINCTION MATTERS HERE MORE THAN USUAL because the company does publish ISO 13485, and ISO 13485 IS A MEDICAL DEVICE QUALITY MANAGEMENT STANDARD, NOT AN INFORMATION SECURITY ATTESTATION. This index recorded that confusion in the surgical lane and applies the same reading here. CE certification under the Medical Device Regulation likewise addresses safety and performance rather than information security, the same way a 510(k) does. A buyer should ask for ISO 27001 or an equivalent separately.

No FDA clearance; the company states it is pursuing US authorisation. What it holds instead deserves precise handling, because a naive prestige ranking of regulators gets this backwards. PERISCOPE is CE certified as CLASS IIa SOFTWARE AS A MEDICAL DEVICE UNDER THE EU MEDICAL DEVICE REGULATION, with ISO 13485. THE MDR ROUTE REQUIRES A CLINICAL EVALUATION SUPPORTED BY CLINICAL EVIDENCE. Compare the US 510(k) pathway, where substantial equivalence to a predicate can be established with no clinical data at all, as happened with another vendor in this same category whose filing states in terms that the device did not require clinical data. So on the specific dimension of clinical evidence demanded, this vendor has cleared a higher bar than some FDA cleared competitors, in a different jurisdiction. REUSABLE RULE: ask which regulatory route was taken and what evidence that route actually required, rather than ranking regulators by reputation. Graded B rather than A because the authorisation is regional, covers no US market, and MDR Class IIa is not the highest EU risk class.

THE THIRD DISTINCT ANSWER IN THIS CATEGORY TO THE INSTITUTIONAL VARIABILITY PROBLEM, and the only one that is an empirical research finding rather than a company commitment. CLEW binds retraining through a regulator reviewed change control plan; Etiometry claims continuous production drift monitoring; Healthplus.ai calibrates to each hospital's own data, and its published study was DESIGNED to test that, developing at one site then validating and updating at two others and measuring performance before and after updating. The paper's stated conclusion is that local updating is necessary to account for domain shifts in patient populations and data distributions across settings. That is the Epic Sepsis Model institutional variability finding turned into a method. Held below A on two counts. No subgroup performance is published by sex, age, ethnicity or socioeconomic status. And the prediction target is defined as the probability of REQUIRING CLINICAL ACTION related to postoperative infection, which is a label learned from what clinicians actually did rather than from biological ground truth, so it can encode differential recognition and response patterns exactly as the Birth Model record describes for obstetric risk. Nothing published addresses that.

Integration is the delivery model rather than an add on: predictions render inside the existing EHR workflow rather than in a separate dashboard, which the company quantifies as saving around ten clicks per patient per shift by consolidating infection relevant information in one place. Distribution runs partly through Founda Health, a Dutch healthcare interoperability platform, which is a real third party integration route. The product also requires no new data capture, drawing only on what the record already holds, which materially lowers the integration burden compared with vendors in this lane that need live device feeds. Held at B because no EHR vendor is named anywhere, there is no marketplace listing or partner certification, and no FHIR or SMART on FHIR capability is described.

Named clinical sites include Amsterdam UMC and Deventer Ziekenhuis, with the published study drawing on three hospitals across the Netherlands and Belgium. Market scope is stated: licensed to operate in the EU with initial focus on Benelux and Germany, which is a clearer geographic statement than most vendors offer. LOCAL CALIBRATION IS A NAMED IMPLEMENTATION STEP RATHER THAN A MARKETING PHRASE, since the company states models are calibrated to each hospital's data and the published work demonstrates the updating procedure, so a buyer knows a site specific step exists. Held at B because no implementation timeline, resourcing requirement, hosting architecture or data residency commitment is published, and it is not stated whether local calibration is included in the licence or charged separately.

No pricing published at any level: no rate card, no unit of pricing, no band and no implementation or calibration fee. THE ASYMMETRY IS THE SAME ONE RECORDED AGAINST DROXI, and it is worth naming because it recurs: the company publishes the customer's upside in detail, citing avoided costs of more than four million euro per hospital per year in one place and a bottom line improvement above two million euro in another, while gating its own price entirely. A buyer modelling return on investment has one side of the equation and not the other. The two savings figures are also inconsistent across sources with no stated basis or derivation for either.

Narrow on condition and broad on specialty, with the limits published. The target is postoperative bacterial infection defined inclusively, covering surgical site infection, pneumonia, urinary tract infection and other bacterial infections rather than surgical site infection alone, which is a wider and more clinically honest target than most competitors in the surgical risk space attempt. Coverage spans a wide range of surgical procedures and multiple specialties, evidenced by a development and validation cohort drawn across specialties rather than a single service line. Adults only. THE 30 DAY HORIZON IS AN UNUSUAL PROPERTY IN THIS CATEGORY AND WORTH NOTING: it extends past discharge, so the product straddles inpatient monitoring and post discharge risk in a way nothing else in this lane does, which raises a question the vendor does not address about who is watching, and who is accountable, once the patient has gone home. Geographic coverage is EU only.