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    Smart on FHIR: AI-Powered Length of Stay Predictor

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    Sold by: Global Tech Teams 
    AI-driven FHIR app predicting discharge timelines for efficient bed management and optimized throughput.

    Overview

    Smart on FHIR: AI-Powered Length of Stay Predictor by Mindbowser is a professional services offering designed to help hospitals forecast patient discharge timelines and optimize bed utilization. Built using FHIR standards and deployed on AWS services such as Amazon SageMaker, Amazon HealthLake, Amazon QuickSight, and Amazon Comprehend Medical, it enables accurate, secure, and scalable LOS (Length of Stay) prediction.

    Key AWS-Enabled Benefits

    1. AI-Backed Forecasting: Leverages Amazon SageMaker and HealthLake to apply predictive ML models on real-time clinical indicators for accurate LOS prediction.
    2. Customizable Workflows: Uses AWS Lambda and CloudFormation for discharge workflows tailored to each hospital’s protocols.
    3. Seamless EHR Integration: Securely integrates via Amazon API Gateway, EKS, and Cognito to connect with Epic, Cerner, and Athenahealth.
    4. Real-Time Dashboards & Alerts: Visualizations powered by Amazon QuickSight, alerts via Amazon SNS, and automation via EventBridge.
    5. Enterprise-Grade Compliance: Designed with AWS KMS, IAM, CloudTrail, and Config to support HIPAA, HITRUST, and GDPR.
    6. Accelerated Deployment: Faster go-live with pre-built AWS frameworks, CI/CD on CodePipeline, and procurement via AWS Marketplace Private Offers.

    Use Cases

    1. Hospital Operations Optimization: Improve discharge planning and bed turnover efficiency.
    2. Administrative Efficiency: Reduce manual effort in inpatient, ED, and surgical wards.
    3. Care Coordination: Enable proactive planning for timely step-down or discharge.
    4. Strategic Planning: Use aggregated LOS data for staffing and capacity forecasting.

    By leveraging AWS-native services, Mindbowser delivers measurable impact: up to 25% reduction in average LOS, 40% drop in manual discharge planning time, and 3× faster readiness identification—helping hospitals achieve clinical and operational excellence on AWS.

    Highlights

    • AI-Driven Length of Stay Forecasting Predicts patient discharge timelines using machine learning models applied to real-time clinical data, helping hospitals proactively plan care transitions.
    • Seamless EHR & FHIR Integration SMART on FHIR-compliant and compatible with leading EHRs (Epic, Cerner, Athenahealth), embedding directly into clinician workflows without disruption.
    • Operational Efficiency & Cost Savings Improves bed utilization, reduces manual discharge planning, and achieves measurable reductions in unnecessary patient stays—optimizing resources and lowering costs.

    Details

    Sold by
    Global Tech Teams 
    Categories
    Healthcare & Life Sciences 
    Implementation 
    Assessments 
    Delivery method
    Deployed on AWS

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    Support

    Vendor support

    We are dedicated to ensuring your success with the Smart on FHIR: AI-Powered Length of Stay Predictor. Our support team is available to assist you with any questions, technical guidance, or implementation challenges you may encounter.

    Support Channels: 1. Email: aws-marketplace-support@mindbowser.com  2. Website: https://www.mindbowser.com/  3. Phone: +1 408 786 5974

    We provide comprehensive documentation, tutorials, and FAQs tailored to your deployment requirements. Our team is committed to providing timely and reliable support, ensuring you achieve a smooth and successful experience with our solution on AWS.

    Learning Resources – Optional Case Study – LOS Predictor in Action Optimizing Hospital Efficiency with AI-Powered LOS PredictionÂ