ClosedLoop.ai

by ClosedLoop.ai  · Based in United States →We predict the future so you can change it.
Family Medicine Hospital Medicine Internal Medicine

Not publicly available; requires contacting sales for a demo and quote.

Overview

ClosedLoop.ai offers a comprehensive, healthcare-specific AI platform designed to empower healthcare organizations to leverage predictive analytics for improved patient outcomes and reduced costs. Acquired by CVS Health, the platform specializes in transforming raw healthcare data into actionable insights through advanced machine learning models.

For physicians and healthcare systems, ClosedLoop.ai provides tools for end-to-end data science workflows. This includes robust capabilities for data ingestion, normalization, and preparation, ensuring that diverse healthcare datasets are ready for analysis. The platform then facilitates the development, validation, and deployment of predictive models tailored to specific clinical and operational challenges.

Key applications include risk stratification, identifying patients at high risk for adverse events or disease progression, and optimizing care management programs. It also supports initiatives in health equity by identifying disparities and improving value-based care models by predicting utilization and cost. By providing a powerful infrastructure for AI, ClosedLoop.ai enables data scientists and clinical teams to build and integrate predictive models directly into existing workflows, enhancing decision-making at various points of care.

Reviewed by Pouyan Golshani, MD — Interventional Radiologist

Key Features

  • Healthcare-specific data ingestion & normalization
  • Predictive model development & validation
  • Model deployment & monitoring
  • Risk stratification capabilities
  • Care management optimization
  • Health equity analytics
  • Value-based care support
  • Cost and utilization prediction
  • Integration with existing healthcare systems
  • Explainable AI (XAI) for model transparency

Use Cases

  • Identifying high-risk patients for proactive intervention
  • Optimizing care pathways for chronic disease management
  • Predicting hospital readmissions
  • Forecasting healthcare utilization and costs
  • Targeting interventions to reduce health disparities
  • Improving patient engagement and adherence

What Physicians Need to Know

Evidence Base
ClosedLoop.ai's platform leverages a comprehensive array of healthcare data types, including clinical, claims, pharmacy, and social determinants of health (SDoH) data, to build and train its predictive models. It can ingest raw EHR, claims, labs, SDoH, and other patient-linkable data streams, simplifying data handling without extensive normalization. The platform includes a comprehensive library of healthcare-specific features and model templates, with clients like Healthfirst developing thousands of custom and pre-built ML features.
Clinical Validation Studies
ClosedLoop.ai was the winner of the CMS AI Health Outcomes Challenge, recognizing its ability to predict unplanned hospital admissions and adverse events. It has been named Best in KLAS for Healthcare AI: Data Science Solutions in both 2022 and 2023. Case studies demonstrate significant improvements, such as CareATC enhancing predictive accuracy by 75% over rules-based risk stratification, identifying 30% of unplanned hospital admissions in the riskiest 5% of individuals. Oak Street Health also successfully implemented their tool, outperforming prior backward-looking approaches in identifying high-risk patients.
Alert Fatigue Management
The platform addresses alert fatigue through 'Explainable AI,' allowing clinicians and data scientists to understand the factors influencing each prediction. This transparency builds trust and confidence in the AI-driven insights. The system generates actionable lists, risk scores, and rankings, enabling care managers to prioritize interventions effectively and focus on the most urgent cases.
Guideline Update Frequency
ClosedLoop.ai supports continuous model improvement and automatic updates of predictions as new data arrives. The platform provides tools for data scientists to continuously refine and iterate on models, including automated accuracy reporting and performance monitoring over time, ensuring predictions remain relevant and accurate.
Clinical Workflow Integration
The platform is designed for seamless integration into clinical end-user workflows, delivering predictions via REST API or push notifications. Its closed-loop analytics approach aims to improve workflows and reduce non-value-added time clinicians spend in EMRs by providing timely, actionable data. Integration with leading Business Intelligence (BI) tools is also supported.
Decision Audit Trail
ClosedLoop.ai offers robust explainability features, allowing users to understand the 'why' behind each prediction. This includes auto-computed top factors for populations and weighted positive/negative factors for individual patients. The platform maintains version-controlled repositories with data provenance, linking predictions to the exact data and model used, which facilitates auditing and governance.
Physician Tip

ClosedLoop.ai excels in providing predictive insights for patient risk stratification and care management, rather than real-time diagnostic or treatment recommendations. Physicians should leverage its 'Explainable AI' features to understand the contributing factors behind risk scores, enhancing trust and informing personalized care plans. Focus on integrating these insights into existing care coordination and population health initiatives to proactively identify and intervene with high-risk patients, optimizing resource allocation and improving outcomes. Remember that this tool augments clinical judgment by highlighting probabilities and risk factors, not by replacing direct clinical assessment or traditional decision support for immediate diagnostic or drug interaction checks.

ClosedLoop.ai is built for integration with diverse healthcare data sources, including EHRs, claims, pharmacy data, and SDoH. It offers REST APIs and push notifications for deploying predictions into existing clinical workflows and supports integration with Business Intelligence tools. The platform is designed to work with an organization's existing data infrastructure, enabling rapid model deployment and continuous updates within the healthcare ecosystem.

Details

Category Clinical Decision Support & Reference, Developer Tools & APIs, Population Health Analytics
Pricing Not publicly available; requires contacting sales for a demo and quote.
  • Offers pricing tiers for organizations of all sizes, from small regional provider networks to large national health plans
  • One solution, ACO-Predict, is available for free to all Medicare ACOs
Free TrialUnknown
DeploymentCloud-based environment
TrainingUnknown
Target SizeOrganizations of all sizes, including small regional provider networks, large national health plans, digital health providers, ambulatory practices, hospitals/health systems, and life sciences.
Compliance
BAA AvailableUnknown AI-estimated
HIPAA CompliantUnknown AI-estimated
FDA Status Unknown AI-estimated — unknown
SOC 2Unknown AI-estimated
GDPRUnknown AI-estimated
Integrations
EHR Not specified
Specialties Family Medicine, Hospital Medicine, Internal Medicine

Social Proof

CustomersServes healthcare organizations impacting over 10 million lives, with one solution piloted by payers and providers managing over 2.7 million members.
Notable
CVS Health

Support & Reliability

Training ProvidedUnknown

Ratings & Reviews

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Clinical Value
Ease of Use
Integration
Support & Docs
Value for Money

Press & Coverage

PR Newswire (via ClosedLoop.ai)
ClosedLoop Wins Top Best in KLAS Healthcare AI Spot for Third Consecutive Year
ClosedLoop.ai has been named Best in KLAS for Healthcare Artificial Intelligence: Data Science Solutions for the third year in a row, achieving an overall performance score of 95.9 out of 100 in the 2024 Best in KLAS Awards: Software and Services report.
2024-02
Business Wire
Healthcare AI Leader ClosedLoop Launches Two First-of-Their-Kind Data Science Products for Value-Based Care
ClosedLoop launched two new data science products, ACO-Predict and Evaluate, designed to help healthcare organizations measure and guide the real-world impact of their programs, improve outcomes, and reduce costs.
2023-09
GlobeNewswire (via ClosedLoop.ai)
ClosedLoop Wins Best in KLAS for Healthcare AI for Second Consecutive Year
ClosedLoop was recognized as Best in KLAS for Healthcare Artificial Intelligence: Data Science Solutions for the second consecutive year in the 2023 Best in KLAS: Software and Services report.
2023-02
Business Wire
ClosedLoop.ai Raises $34M Series B to Usher in AI-Enabled Healthcare and Tackle Trillion-Dollar Healthcare Problem
ClosedLoop.ai announced a $34 million Series B financing round to further its mission of making healthcare decisions data-driven and AI-enabled, aiming to improve patient outcomes and reduce costs.
2021-08
Centers for Medicare & Medicaid Services (CMS)
CMS Selects Winner and Runner-Up in Artificial Intelligence Health Outcomes Challenge
CMS announced ClosedLoop.ai as the winner of its Artificial Intelligence (AI) Health Outcomes Challenge, a multi-stage competition aimed at accelerating the development of AI solutions for predicting patient health outcomes for Medicare beneficiaries.
2021-04
RamaOnHealthcare
ClosedLoop.ai Q&A: How AI is Changing the Healthcare Landscape - RamaOnHealthcare
Andrew Eye, CEO of ClosedLoop.ai, discusses how AI is transforming healthcare by leveraging predictive analytics to reduce disparities, prevent adverse events, and address costly problems in the industry.
2021-06
Journal of Medical Artificial Intelligence
Building a COVID-19 vulnerability index - Journal of Medical Artificial Intelligence
This article, co-authored by Dave DeCaprio of ClosedLoop.ai, presents models for predicting severe complications from COVID-19, including an open-source tool called the C-19 Index developed using the ClosedLoop platform.
2020-12
Medium (TDS Archive)
A New Metric for Quantifying Machine Learning Fairness in Healthcare u2014 ClosedLoop.ai | by Joseph Gartner | TDS Archive | Medium
This article, originally published on ClosedLoop.ai's blog, discusses the critical need to address bias in AI algorithms within healthcare and introduces a new metric developed by ClosedLoop to quantify machine learning fairness.
2020-03

Videos

Product demos, reviews, and walkthroughs for ClosedLoop.ai.

View all on YouTube

Frequently Asked Questions

ClosedLoop.ai analyzes vast amounts of patient data, including EHRs, claims, and social determinants of health, to provide predictive insights and recommendations. It helps identify high-risk patients, optimize treatment regimens, and personalize care by surfacing actionable risk factors.
While powerful, AI tools like ClosedLoop.ai can make mistakes and require critical review by clinicians to ensure accuracy and reduce liability risks. The platform aims for explainable AI, showing contributing factors to predictions, but human oversight remains crucial for final decisions.
ClosedLoop.ai is built for healthcare, emphasizing security and compliance, including HIPAA. It operates as a closed-loop system within an organization's environment, meaning data is not shared externally or used for public training models, ensuring data sovereignty and protection.
Yes, ClosedLoop.ai is designed to ingest, normalize, and blend data from various health data sources, including Electronic Health Records (EHRs), e-prescribing data, and lab results. It aims for seamless integration into existing clinical workflows and IT infrastructure.
While ClosedLoop.ai is recognized in healthcare AI, alternatives exist depending on specific needs. Some platforms mentioned in the broader healthcare analytics and patient engagement space include QGenda Advanced Scheduling for Providers, eClinicalWorks, Waystar, athenaOne, and InteliChart.
ClosedLoop.ai operates on a SaaS (Software as a Service) model, offering flexible pricing. As a privately held company, its specific pricing details are not publicly disclosed, but it may include performance-based or outcome-driven models in addition to standard subscriptions.
ClosedLoop AI Systems are designed to streamline clinical workflows by providing real-time insights and recommendations, which can reduce medication errors and optimize resource utilization. The goal is to empower clinicians with actionable intelligence for more informed decision-making.

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Suggest an Edit → | Last Verified: 2026-05-12 | First Added: 2026-05-12

Investors who backed ClosedLoop.ai

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