MedAI Verdict
Decision support

Clinical Decision Support

PERISCOPE logo

PERISCOPE

by Healthplus.ai  ·  NL

Last verified

PERISCOPE predicts postoperative bacterial infection risk 7 and 30 days after surgery from EHR data.

At a glance

Pricing
No public price.
HIPAA
Not disclosed
SOC 2
Not disclosed
EHRs
—
Founded
—
HQ
NL
On this page

Independent score  ·  By our public rubric

15/100Tracked

Not rated: too little independent evidence yet.

How it’s computed →
  • Regulatory & Compliance
    0/22

    No FDA clearance listed

  • Clinical Integration
    0/11.6

    No EHR integrations listed

  • Evidence Strength
    8.4/30

    1 peer-reviewed paper

  • Vendor & Market
    3/18

    Seed-stage or unfunded

  • Sentiment & Transparency
    1.3/2.5

    Pricing on request, no public amounts

▸ Show all 11 dimensions

Regulatory & Compliance

  • FDA clearance0/12

    No FDA clearance listed

  • HIPAA / SOC2 / BAA0/10

    No public HIPAA/SOC2/BAA attestation

Clinical Integration

  • EHR integrations (count)0/6

    No EHR integrations listed

  • Top-3 EHR coverage (Epic / Oracle / Athena)0/5

    None of the top-3 EHRs covered

  • Bidirectional write-back0/1

    No bidirectional write-back documented

Evidence Strength

  • Peer-reviewed papers8/21

    1 peer-reviewed paper

  • RCT / meta-analysis / systematic review0/9

    No RCT, meta-analysis, or systematic review

Vendor & Market

  • Funding & adoption signal3/12

    Seed-stage or unfunded

  • Years in market0/6

    Founded year not recorded

Sentiment & Transparency

  • Pricing transparency1/3

    Pricing on request, no public amounts

Scored November 2, 2026 · Public scoring method v1.2.0

PERISCOPE predicts postoperative bacterial infection risk 7 and 30 days after surgery from EHR data.

No public price.

Evidence record

FDA decisions

No FDA decision cited in our research as of November 2, 2026.

Peer-reviewed

1 study on PubMed: 1 other, published 2025. Read the literature summary

Verification
  • Score computed November 2, 2026, method 1.2.0
  • Review written November 2, 2026
Cite this record

MedAI Verdict, PERISCOPE record, https://medaiverdict.com/tools/healthplus-ai, version November 2, 2026

Bottom line

PERISCOPE, from Amsterdam-based Healthplus.ai B.V., estimates a surgical patient's risk of a bacterial infection 7 and 30 days after the operation from data already in the EHR. The vendor states a CE mark as a Class IIa device under the EU MDR and makes no FDA claim. The published evidence is one retrospective multicentre paper that has two authors from the company. A surgical service in Europe is the target, and a US hospital has no FDA-cleared product to buy.

What does the score look like?

The homepage describes a clinical decision support system that returns a 7-day and a 30-day risk, a risk category and the top contributing factors, and adds "You decide what action to take." The models are XGBoost, trained per hospital on pre- and intra-operative EHR data. According to the vendor, each hospital's model is recalibrated locally and checked for accuracy across 16 subgroups such as sex and age.

Implementation takes "typically 8 to 12 weeks, depending on your EHR system," and the page says PERISCOPE "integrates directly into your electronic health record interface" without naming an EHR.

Which certificates and clearances does it hold?

Besides the CE mark, the homepage lists ISO 13485 and ISO 27001 and does not name the notified body. The FDA 510(k) database has no record under Healthplus.ai, and funding coverage presents FDA clearance as a goal for the money raised.

How strong is the one published study?

The one PubMed-indexed paper is van der Meijden and colleagues in the Lancet Regional Health Europe, 2025 (PMID 39720095). It covers 253,010 procedures with 23,903 infections within 30 days at three hospitals in the Netherlands and Belgium. After model updating, the 30-day AUROC was 0.82, 0.82 and 0.91 on the 2022 to 2023 temporal validation. The design was retrospective and it evaluates prediction accuracy without testing any change in infection outcomes. Two of the authors work at Healthplus.ai B.V.

The homepage carries testimonials from Deventer Ziekenhuis and Amsterdam UMC and describes the tool as "validated and implemented at leading medical centers of excellence," without a count.

Who funds it, and what does it cost?

Funding coverage lists an undisclosed round from LUMO Labs meant for CE certification and clinical trials, and a EUR 2.3 million late-seed round led by Elevating Capital with LUMO Labs, ROM InWest, PATHENA and Leistone, aimed at the European rollout, a US launch and FDA clearance. A news post on the vendor's site adds BVP and Noso Capital as investors in a seed extension, with no amount. The homepage gives no founding year or founders.

Healthplus.ai gives no price. The homepage links a "Calculate your ROI" tool instead.

The verdict

The published case for PERISCOPE is one retrospective study with 30-day AUROCs of 0.82, 0.82 and 0.91 at three hospitals in the Netherlands and Belgium, and no outcome trial. A surgical service in those countries has the closest match to that data. A US hospital has no FDA clearance to cite, since the vendor claims none.

Editorial review last generated November 2, 2026. Synthesized from clinician sentiment, peer-reviewed coverage, and our editorial silo picks. Refined by hand where vendor facts change.

What it costs

All tiers are custom-quoted. The vendor does not publish per-provider list pricing.

TierMonthlyAnnualNotes
EnterpriseNot statedNot statedNo public price.

Source: vendor pricing page. Last checked November 2, 2026.

What deploys cleanly

Carries CE, ISO 13485, ISO 27001 per vendor documentation. Independent attestation review is the buyer's responsibility before clinical deployment.

What the literature says

1 peer-reviewed study indexed on PubMed evaluate PERISCOPE in clinical contexts. The most relevant are shown below, ranked by editorial relevance score combining title match, study design, recency, and journal tier.

Development and validation of artificial intelligence models for early detection of postoperative infections (PERISCOPE): a multicentre study using electronic health record data. (opens in new tab)
van der Meijden SL, van Boekel AM, Schinkelshoek LJ, et al.· Lancet Reg Health Eur· 2025
Postoperative infections significantly impact patient outcomes and costs, exacerbated by late diagnoses, yet early reliable predictors are scarce. Existing artificial intelligence (AI) models for postoperative infection prediction often lack external validation or perform poorly in local settings when validated. We aimed to develop locally valid models as part of the PERISCOPE AI system to enable early detection, safer discharge, and more timely treatment of patients. We developed and validated XGBoost models to predict postoperative infections within 7 and 30 days of surgery. Using retrospec…

See all on PubMed (opens in new tab)