Clew Predicts Patient Deterioration Before It Happens: The Future of Critical Care
What is Clew? CLEW Medical provides an AI-driven clinical surveillance platform that analyses real-time physiologic, device, and EHR data to predict patient deterioration (notably respiratory failure and hemodynamic instability) hours before events occur. Its FDA-cleared predictive models produce unit- and patient-level risk indices (e.g., CLEWRF, CLEWHI), customisable alerts, and dashboards for ICU and tele-ICU teams […]
Feature Categories
What is Clew?
CLEW Medical provides an AI-driven clinical surveillance platform that analyses real-time physiologic, device, and EHR data to predict patient deterioration (notably respiratory failure and hemodynamic instability) hours before events occur. Its FDA-cleared predictive models produce unit- and patient-level risk indices (e.g., CLEWRF, CLEWHI), customisable alerts, and dashboards for ICU and tele-ICU teams to prioritise interventions, reduce false alarms, and improve outcomes.
CLEW’s cloud-native architecture supports enterprise deployments, integrates with monitoring and EMR systems, and has peer-reviewed validation and multi-centre deployment evidence demonstrating improved prediction accuracy and operational benefits.
Why Leading Healthcare Teams Trust Clew
- FDA 510(k) clearance secured for second-generation AI/machine learning models for predicting patient deterioration
- Built-for-cloud technology offering scalability, interoperability, robustness, security, privacy and full regulatory compliance
- FDA-cleared predictive analytics with proprietary critical care models for hospitals and healthcare systems
- Strategic partnership with AvaSure (market leader in acute virtual care) for early detection of critical care patient deterioration
- Investment backing from notable healthcare investors including Relyens, Agate Medical Investments, 8200 EISP, MedTech Innovator, and Healthbox
- Global presence with representatives and partners in over five different countries
- Specialises in high-accuracy predictive clinical analytics for healthcare providers and administrators
- No acquisitions or mergers to date, maintaining independent operations
- Fulfilled all standard FDA prerequisites applicable to medical devices for regulatory clearance
- Focus on intensive care units and high-acuity healthcare transformation
Top 3 Pain Points Crew Fixes in Healthcare
| Problem | How Clew Solves It |
|---|---|
| 1. Delayed Detection of Patient Deterioration | Uses FDA-cleared AI models to predict risks like respiratory failure and hemodynamic instability hours in advance. |
| 2. Alarm Fatigue in ICUs | Prioritises clinically significant alerts and reduces false alarms, helping staff focus on high-risk patients. |
| 3. Resource Strain in Critical Care | Provides unit- and patient-level risk dashboards, enabling better triage, workflow management, and ICU resource allocation. |
Feature Category Summary: Clew
| Feature Category | Summary | Association (YES, NO, NA) |
|---|---|---|
| Regulatory-Ready | CLEWICU is explicitly described as a class II medical device that has received FDA 510(k) clearance to predict hemodynamic instability in adult ICU patients and subsequent clearance for second‑generation deterioration models, following earlier EUA for respiratory deterioration; the system is also CE‑marked and registered with the Israeli AMAR authority. CLEW states that it operates under an ISO 13485–certified QMS, provides HIPAA‑compliant cloud deployment, and maintains audit‑ready documentation, demonstrating full regulatory‑grade device development and validation for its intended ICU use. | YES |
| Clinical Trial Support | CLEW’s products and published materials focus on real‑time ICU surveillance and deterioration prediction in routine critical care, not on clinical‑trial protocol design, recruitment, between‑visit monitoring for study endpoints, or regulatory trial reporting; no CTMS/EDC features are described. No public documentation found that CLEW is used as a clinical‑trial support platform. | NA |
| Supply Chain & Quality | The platform ingests physiologic and clinical data from EHRs and bedside devices to monitor ICU patients; there is no mention of GMP manufacturing, batch‑release QA, serialization, or counterfeit‑medicine detection capabilities. No public documentation found for pharmaceutical supply‑chain or manufacturing‑quality functionality. | NA |
| Efficiency & Cost-Saving | CLEWICU continuously categorizes patient risk and identifies low‑risk patients unlikely to deteriorate, which can support ICU resource optimization and reduce alarm fatigue, but public sources summarise mainly accuracy and alert‑burden metrics (e.g., 50× fewer alarms vs a leading tele‑ICU system) rather than quantified cost or staffing savings. No explicit, quantified evidence (e.g., reduced LOS, cost per case, or FTE time saved) is provided in publicly accessible materials, so cost‑saving and efficiency gains, while plausible, are not formally documented to your required standard. | NA |
| Scalable / Enterprise-Grade | CLEW is marketed as a “system‑agnostic” platform that processes data from HL7 v2, FHIR, bedside monitors, and custom interfaces, and is deployed across multiple ICUs with remote/virtual care models and high‑resolution audio‑video for tele‑ICU teams. It supports unit‑level and enterprise‑wide deployment, but public sources do not name specific large pharma/biotech customers (appropriate here, since it is a hospital product) or quantify number of hospitals; nonetheless, the multi‑site ICU deployments and integration stack provide explicit evidence of hospital‑enterprise scalability. | YES |
| HIPAA Compliant | CLEW states that its cyber‑security practices “allow CLEW to offer a HIPAA‑compliant cloud environment” and that “CLEW and its products meet the requirements for protection of sensitive patient data and are fully HIPAA compliant,” and also notes ISO 27001 and ISO 27799 certifications plus GDPR compliance. These attestations explicitly confirm alignment with HIPAA and related security standards. | YES |
| Clinically Validated | A peer‑reviewed, multi‑center ICU study (UMass Memorial and WakeMed) reported that CLEW’s AI‑driven predictions for hemodynamic instability and respiratory failure were five times more accurate than alerts from the leading telemedicine system and generated 50 times fewer alarms, demonstrating clinically relevant performance and reduced alarm burden. FDA 510(k) summaries and clearance announcements further indicate that CLEW’s models were evaluated against clinical endpoints of hemodynamic and respiratory deterioration, providing formal clinical validation for their intended ICU‑surveillance use. | YES |
| EHR Integration | CLEW documentation and the FDA device summary state that the CLEWICU system integrates with existing EHR systems and medical devices, receiving data via HL7 v2.x, FHIR, streaming channels, or SQL databases, and providing “One Click” access that deep‑links clinicians from CLEW into the corresponding EHR patient record for order entry and documentation. This is explicit evidence of bi‑directional EHR integration and workflow embedding. | YES |
| Explainable AI | CLEW describes combining ML‑derived prediction models with “rules‑based best practices,” built‑in clinical protocols, and tools that allow hospitals to customize and display protocol‑driven alerts and criteria, providing clinical context around AI risk scores. However, there is no detailed description of model‑level explanations (e.g., feature‑importance, causal contributions, or per‑prediction rationales) being exposed to clinicians; explanations are primarily via protocol overlays and risk categories, not explicit XAI tooling. | NA |
| Real-Time Analytics | CLEWICU “continuously monitors and categorizes patient risk levels,” receiving data from EHRs and bedside devices and analyzing it in near real‑time to provide unit‑wide displays of patient status and predictive alerts up to 8 hours in advance of hemodynamic instability. The technology page explicitly notes real‑time/online data quality validation and continuous streaming, clearly meeting the requirement for real‑time analytics. | YES |
| Bias Detection | Available materials focus on ICU deterioration prediction performance, interoperability, and alarm burden; there is no reference to structured bias‑detection, subgroup performance dashboards, or fairness metrics across demographic or clinical sub‑cohorts for CLEW’s models. No public documentation found for algorithmic bias‑detection or fairness‑monitoring features. | NA |
| Ethical Safeguards | CLEW emphasizes regulatory compliance (FDA, CE, HIPAA, GDPR, ISO‑certified QMS) and provides tools for clinical leadership to configure protocols and criteria, but there is no description of explicit ethical‑governance modules such as consent management, configurable use‑case restrictions, or enforced human‑in‑the‑loop override controls beyond standard clinical judgment. No public documentation found that frames specific product features as ethical‑safeguard controls for AI use. | NA |
Risks & Limitations: Clew
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Alert fatigue / PPV management: high sensitivity settings increase false positives—threshold tuning and integrated workflows are essential to avoid clinician overload.
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Generalisability & drift: models trained on one population or device set can underperform elsewhere—local calibration and prospective validation are required.
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Causal attribution: observed outcome improvements are typically tied to the broader implementation (alerts + response protocol + staffing) rather than the model alone. Procurement pilots should include implementation science metrics.
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Operational readiness: hospitals with limited rapid-response capacity or constrained staffing may struggle to convert earlier detection into improved outcomes.
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Stephen
Founder of HealthyData.Science · 20+ years in life sciences compliance & software validation · MSc in Data Science & Artificial Intelligence.