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Predicting Hospital Readmissions

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Product Description: ClosedLoop's Predicting Hospital Readmissions solution leverages advanced artificial intelligence to identify patients at high risk of 30-day readmission. By analyzing diverse healthcare data sources, it provides actionable insights to healthcare providers, enabling proactive interventions that enhance patient outcomes and reduce unnecessary costs. Key Features and Functionality: - Comprehensive Data Integration: Aggregates and normalizes data from multiple sources, including electronic health records, clinical notes, e-prescribing data, vital signs, remote monitoring data, medical and prescription claims, ADT records, lab results, social needs assessments, and social determinants of health. - Explainable AI Predictions: Generates transparent predictions with detailed contributing factors, allowing clinicians to understand and trust the risk assessments. - Actionable Risk Factors: Identifies specific factors contributing to readmission risk, such as previous admissions for congestive heart failure, medication adherence levels, changes in medication regimen at discharge, and caregiver support levels. - Proactive Intervention Support: Enables healthcare providers to enhance pre-discharge evaluations, promote continuity of care, and educate patients on chronic disease management to prevent readmissions. Primary Value and Problem Solved: Hospital readmissions are a significant challenge, with approximately 4.2 million adult readmissions annually, costing CMS $26 billion each year. ClosedLoop's solution addresses this issue by providing healthcare organizations with the tools to predict and mitigate unplanned readmissions. By pinpointing high-risk individuals and surfacing actionable risk factors, it empowers providers to implement targeted interventions, improve patient care transitions, and reduce financial penalties associated with excessive readmissions.

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