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MedAware

by MedAware · Based in Israel → — AI-based medication safety monitoring platform

Emergency Medicine Hospital Medicine Internal Medicine

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Overview

MedAware is an AI-powered medication safety monitoring platform designed to identify and prevent medication-related errors and adverse drug events (ADEs). Unlike traditional rule-based clinical decision support (CDS) systems that rely on pre-programmed logic, MedAware utilizes machine learning algorithms and statistical outlier detection to analyze patient data against historical prescribing patterns. This approach allows the platform to flag potential prescribing anomalies that do not align with the specific clinical profile of the patient, physician, or institution.

The platform is built for healthcare providers, clinical care teams, and acute care pharmacists operating in hospitals, health systems, and long-term care facilities. It integrates directly into existing electronic health record (EHR) systems, such as Epic, and operates continuously in the background. This native integration allows clinicians to receive real-time, patient-specific risk alerts directly within their established clinical workflows, minimizing alert fatigue by focusing on high-relevance clinical anomalies.

Notable capabilities of MedAware include:

Continuous Surveillance: Evaluates patient data 24/7 to identify evolving risks during a hospital stay as a patient’s clinical status changes.
Outlier Detection: Uses machine learning to identify off-pattern prescriptions, dosing errors, and contraindications that standard rule-based systems may miss.
Targeted Risk Identification: Features specialized models to screen for specific medication-related risks, such as opioid dependency risk and high-alert medication errors.

Reviewed by Pouyan Golshani, MD — Interventional Radiologist

Key Features

AI-based medication safety monitoring
Real-time detection of medication errors
Identification of adverse drug events (ADEs)
Opioid dependency risk identification
Machine learning algorithms for outlier detection
Integration with existing EHRs and technology systems
Reduction of alert fatigue with highly relevant alerts
Continuous monitoring throughout the patient journey
Personalized patient-specific risk analysis
Support for pharmacy workflows

Use Cases

Preventing prescription errors at the point of care
Identifying and mitigating evolving adverse drug events
Detecting patient-specific risk of opioid use disorder (OUD)
Improving patient safety in hospitals and health systems
Optimizing pharmacy workflows and operational efficiency
Providing clinical decision support for prescribers and care teams

What Physicians Need to Know

Evidence Base

MedAware utilizes AI and machine learning algorithms to analyze large-scale Electronic Medical Records (EMRs) and identify 'outliers' in prescribing patterns. This approach differs from traditional rule-based systems. It learns from real-life physician treatment scenarios and patient data to detect potential errors and risks, including those related to adverse drug events, opioid dependency, and medication appropriateness based on lab results.

Clinical Validation Studies

MedAware's platform has undergone clinical validation. A study at Sheba Medical Center showed that MedAware's machine learning platform significantly minimized medication-related risks, with 89% of alerts considered accurate and 80% clinically useful. Another study published in the Journal of American Medical Informatics Association found that MedAware's system generated clinically valid medication error alerts that traditional CDS systems might miss, with 76.2% of alerts found to be valid and 75% of those clinically useful. A Harvard Medical School study validated MedAware's algorithm for identifying patients at risk of Opioid Use Disorder (OUD) with over 93% accuracy.

Alert Fatigue Management

MedAware's AI-driven approach aims to significantly reduce alert fatigue by providing highly personalized and clinically relevant alerts. Studies indicate that MedAware can reduce the number of alerts by over 90% compared to conventional systems, which often have high false-positive rates (up to 90%). This increased accuracy leads to greater clinician confidence and attention to alerts.

Override Rate Data

While conventional systems often see only about 5% of medication alerts accepted, MedAware's alerts result in clinicians adjusting their behavior in 43% of cases. This high rate of behavioral change indicates a strong clinical relevance and acceptance of MedAware's alerts.

Drug Interaction Checking

MedAware's AI-powered system goes beyond traditional drug-drug interaction knowledge bases by analyzing patient-specific and provider-specific context to identify dangerous drug combinations and other medication-related risks. It can identify 80% more high-risk prescriptions compared to traditional rule-based systems.

Differential Diagnosis Support

While MedAware primarily focuses on medication safety and error detection, its AI analyzes patient data to identify outlier prescribing behaviors and inconsistencies, which can indirectly support differential diagnosis by flagging medications inappropriate for a patient's profile or condition.

Clinical Workflow Integration

MedAware is designed to integrate seamlessly as a safety and workflow optimization layer within existing Electronic Health Record (EHR) systems, such as Epic and athenahealth, without requiring significant overhauls. It embeds clinically relevant, patient-specific insights directly into the existing ordering/prescribing, order review and verification, dispensing, and clinical monitoring workflows.

Decision Audit Trail

MedAware's system monitors in real-time and is aware of a patient's past medical history, capable of pointing to future potential risks. This continuous monitoring and alerting within the workflow inherently creates a record of detected risks and interventions, supporting an audit trail for medication-related decisions.

Physician Tip

MedAware's AI acts as a personalized safety net, identifying medication errors and risks that traditional systems often miss. Pay close attention to MedAware's alerts, as they are highly relevant and patient-specific, leading to a significant change in prescribing behavior in many cases. The system continuously monitors patient data, including changes in clinical status, to provide timely interventions. Leverage this tool to enhance patient safety, particularly in complex cases or when prescribing high-alert medications, and to reduce your cognitive load from irrelevant alerts.

MedAware integrates as a supplementary layer within existing EHR systems like Epic and athenahealth, enhancing their medication safety capabilities without requiring a complete system overhaul. It also collaborates with medical device companies, such as Baxter International, to embed its AI algorithms into devices like smart infusion pumps for improved programming safety.

At a glance

Pricing Contact for pricing

Deployment On Premise (integrated With EHRs)

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Details

Category	Clinical Decision Support & Reference, Pharmacology & Dosing AI
Pricing	Contact for pricing
Deployment	On-premise (integrated with EHRs)
Compliance
BAA Available	Yes AI-estimated
HIPAA Compliant	Yes AI-estimated
FDA Status	Unknown
Integrations
EHR	Not specified
Specialties	Emergency Medicine, Hospital Medicine, Internal Medicine

What the Web Says

MedAware is an AI-powered platform designed to prevent medication errors and improve patient safety by analyzing electronic medical records in real-time. It identifies outliers in prescription behavior, flags potential errors, and can detect patients at risk of opioid use disorder. The system aims to reduce alert fatigue among healthcare professionals by providing more accurate and actionable alerts compared to traditional rule-based systems.

Overall: Positive

Strengths

Reduces medication errors and improves patient safety.
Significantly reduces false alerts, leading to less 'alert fatigue' for physicians.
Identifies patients at risk of Opioid Use Disorder (OUD) with high accuracy.
Monitors patient conditions in real-time, considering past medical history and potential future risks.
Integrates with existing Electronic Medical Record (EMR) systems.
Can be used as a population health tool to screen large populations for at-risk individuals.

Limitations

Integration with existing EMR systems can be challenging, and EMR systems may view MedAware as a competitor.
Faces the risk of older prescription patterns and practices becoming outdated as medical science evolves.
Requires continuous investment in research studies to validate its alerting system and prove causation.
Technology was patent-pending, potentially facing copycat solutions.
Hospital management must be willing to experiment with new products and train staff for behavior change.

Based on reviews from: Forbes, MedStartr AI, Digital Innovation and Transformation, MD+DI, Sheba Medical Center, YouTube

Last updated: 2026-10-01

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Press & Coverage

PR Newswire

MedAware Partners with Ballad Health's pharmacy team to bring personalized medication risk monitoring to rural healthcare

MedAware has partnered with Ballad Health to implement its AI-powered medication safety monitoring platform, aiming to provide real-time personalized risk monitoring for acute care patients and improve patient safety in rural healthcare settings. Ballad Health's pharmacy teams are reportedly acting on over 70% of the patient risks identified by MedAware's platform, leading to thousands of patients being safer from adverse drug events.

2024-10

Forbes

Using AI To Personalize Healthcare And Improve Patient Safety - Forbes

This article highlights MedAware's AI-driven approach to patient safety, emphasizing its ability to personalize healthcare and reduce medication errors. A Harvard Medical School study confirmed MedAware's predictive capabilities in identifying patients at risk of Opioid Use Disorder (OUD) with over 93% accuracy.

2024-11

ACL Anthology

MedAware at MEDIQA-EVAL 2026: Vision-Language Model Fine-Tuning with Logprob-Based Score Calibration for Medical Response Evaluation - ACL Anthology

This paper presents MedAware's system for MEDIQA-EVAL 2026, focusing on predicting human ratings of medical QA responses using fine-tuned Qwen3-VL models and logprob-based continuous scoring with quantile calibration. The approach aims to address label skew and unstable correlation metrics in medical response evaluation.

2026-09

PR.com

Biomed Industries, Inc. to Acquire MedAware Systems, Inc. to Expand Its Artificial Intelligence Research for Drug Discovery in Alzheimer's Disease - PR.com

Biomed Industries, Inc. announced its acquisition of MedAware Systems, Inc. in an $18 million share exchange agreement. This acquisition aims to expand Biomed's artificial intelligence research for drug discovery, particularly in Alzheimer's disease and other neurodegenerative disorders.

2022-09

MedTech Innovator

MedAware Systems Launches AI Post Market Surveillance for Neuromodulation Devices

MedAware Systems' Science of Health Informatics (SOHInfo) launched an AI-powered surveillance service for neuromodulation devices, fulfilling FDA and MDR post-market vigilance requirements. This service provides current and detailed event information, including reported events, device and patient problems, and report sources.

2021-02

PR Newswire

MedAware Partners with athenahealth's Marketplace Program to Provide Clinicians with an Effective Medication Safety Monitoring System - PR Newswire

MedAware has partnered with athenahealth's Marketplace Program to offer clinicians an effective medication safety monitoring system. The AI-based technology leverages EHR and lab data to continuously monitor patient risk of medication-related adverse events, providing alerts that go beyond traditional systems.

2021-08

PR Newswire

Harvard Researchers Find Significant Clinical Impact and Cost Savings With MedAware's Patient Safety Platform - PR Newswire

A study published in The Joint Commission Journal on Quality and Patient Safety validated MedAware's AI-based patient safety platform, demonstrating significant clinical impact and anticipated ROI. The study estimated over $1.3 million in direct cost savings from avoidable adverse events if the system had been operational in outpatient clinics.

2019-12

PR Newswire

Sheba Medical Bolsters Patient Safety Practices With MedAwareu00ae's Medication Safety Platform - PR Newswire

Sheba Medical Center implemented MedAware's AI-based medication safety platform, which leverages big data analytics and machine learning to flag potentially dangerous medication outliers with high accuracy and low alert fatigue. Initial results showed 80% accuracy of MedAware warnings, leading to a hospital-wide rollout.

2018-09

Videos

Product demos, reviews, and walkthroughs for MedAware.

Medical Alerts That Make Sense From MedAware

Healthcare IT Today

Interview with MedAware CEO Dr. Gidi Stein

HealthBiz Podcast with David E. Williams

Medaware a Platform to Help Prevent EHR Medication Erros

Neurosurgical TV

MedAware AI | Smart Medicine Scanner with AI Safety Detection

Tanya Garg

"MedAware" - Complete Walkthrough

Prithwiraj Mohanty

MedAware

Gidi Stein

View all on YouTube

Frequently Asked Questions

How does MedAware integrate into my existing clinical workflow and EHR system?

MedAware is designed to integrate seamlessly with most major EHR systems through standard interfaces like HL7. It works in the background, analyzing orders in real-time and providing alerts directly within your existing workflow, aiming to minimize disruption to your current processes.

What is the evidence for MedAware's effectiveness in preventing medication errors and improving patient safety?

MedAware utilizes a unique anomaly detection engine that identifies deviations from typical prescribing patterns, which can indicate potential errors. Studies and case reports have demonstrated its ability to detect a range of medication errors, including incorrect dosages, drug-drug interactions, and drug-allergy contraindications, leading to improved patient safety outcomes.

How does MedAware address alert fatigue, and what is its false positive rate?

MedAware employs advanced algorithms and machine learning to reduce alert fatigue by prioritizing high-risk alerts and learning from physician interactions. While no system can eliminate false positives entirely, MedAware continuously refines its algorithms to minimize irrelevant alerts, aiming for a low false positive rate to ensure clinicians only receive actionable information.

What are the typical costs associated with implementing and maintaining MedAware, and how is pricing structured?

Pricing for MedAware typically depends on the size of the healthcare institution, the number of users, and the specific modules implemented. It often involves a subscription-based model, with costs covering implementation, licensing, ongoing maintenance, and support. Specific pricing details would require a direct consultation with MedAware representatives.

What are the limitations of MedAware, and are there situations where it might not be effective?

While highly effective, MedAware's primary focus is on detecting medication-related anomalies based on historical data and real-time order analysis. It may have limitations in identifying errors related to rare diseases with limited data, or in situations where a highly unusual but clinically appropriate prescription falls outside typical patterns. It's a decision support tool, not a replacement for clinical judgment.

How does MedAware compare to other clinical decision support systems (CDSS) or pharmacy-based review processes?

MedAware differentiates itself through its anomaly detection engine, which goes beyond traditional rule-based CDSS by identifying errors that may not be explicitly coded in existing drug interaction databases. While complementing pharmacy review, MedAware provides real-time, pre-prescription alerts, offering an additional layer of safety earlier in the medication ordering process.

What kind of training and support is provided for physicians and staff using MedAware?

MedAware typically offers comprehensive training programs for physicians, pharmacists, and IT staff to ensure effective implementation and utilization. This often includes on-site training, webinars, user guides, and ongoing technical support to address any questions or issues that may arise.