Limbix (by BigHealth)
Evidence-based digital therapeutics for adolescent mental health and behavioral activation.
The AI platform for value-based care optimization and patient risk prediction.
ClosedLoop is an industry-leading healthcare data science platform engineered to accelerate the development and deployment of predictive models specifically for clinical and financial outcomes. By 2026, it has established itself as the dominant player in the Value-Based Care (VBC) ecosystem, offering a purpose-built AutoML engine that handles the nuances of longitudinal healthcare data, including EHR records, claims, and Social Determinants of Health (SDoH). The platform's technical architecture is centered around its Healthcare Data Model (HCDM), which automates the feature engineering process for thousands of clinical variables. This allows healthcare organizations to move beyond generic risk scores to high-performance, explainable models that identify rising-risk patients, predict hospital readmissions, and optimize resource allocation. ClosedLoop distinguishes itself through its focus on transparency and clinical validation, providing 'Acre'—an explainability toolkit that translates complex model outputs into actionable clinical insights for frontline providers. In the 2026 market, it is primarily utilized by large health systems, payers, and ACOs looking to reduce the Total Cost of Care (TCOC) while improving health equity through rigorous bias detection and mitigation tools.
Proprietary automated machine learning engine optimized for sparse, longitudinal healthcare data sets.
Evidence-based digital therapeutics for adolescent mental health and behavioral activation.
Predictive clinical and operational intelligence to fight death and waste in healthcare.
Predictive medical data and clinical insights for streamlined enterprise underwriting.
The professional medical network for clinicians, providing HIPAA-compliant AI and telehealth solutions.
Verified feedback from the global deployment network.
Post queries, share implementation strategies, and help other users.
A clinical-first explainability framework that identifies the specific factors driving an individual patient's risk score.
Integrated auditing tools to detect and mitigate algorithmic bias across demographic and socioeconomic lines.
Pre-built connectors for third-party social determinants data, including zip-code level economic indicators.
Direct support for HL7 FHIR standards for real-time data streaming and interoperability.
A library of 100+ pre-vetted clinical model templates for common conditions (CHF, COPD, Diabetes).
Bi-directional integration that pushes risk scores and clinical insights directly into Epic, Cerner, or Meditech.
Identifying which patients are most likely to return to the hospital after discharge.
Registry Updated:2/7/2026
Finding patients who are clinically stable now but likely to have an acute event in the next 6 months.
Predicting which patients will stop taking life-saving medications.