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Enhance Patient Outcomes with Advanced Insights and Targeted Interventions

Leverage Value-Based Care Insights for Timely and Effective Patient Interventions with HealthSphere™ 

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Data Ingestation & Normalization


Data Preparation


Training & Validation (AutoML)


Explainability & Reporting 


Data Ingestation & Normalization

HealthSphere optimizes the deployment of data science in the complex and diverse data environments of healthcare organizations by simplifying data ingestion and normalization, leading to faster and more effective data science operations.

  • Secure Data Practices: Ensures HIPAA compliance, HITRUST certification, and SOC 2 Type II certification for safe data transfer and storage.

  • Versatile Data Ingestion: Capable of processing and standardizing a wide range of raw healthcare data.

  • Extensive Terminology Mapping: Automatically maps data to over 20 healthcare terminologies, including CCSR, CPT, and LOINC.

  • Automated Data Cleanup: Features automatic cleaning of medical data to maintain quality and accuracy.


Data Preparation

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Training & Validation (AutoML)

HealthSphere unlocks the full potential of data science by continuously refining models to provide precise and transparent health insights tailored specifically for healthcare.

  • Iterative Model Refinement: Continuously enhances models to ensure the delivery of accurate and comprehensible health insights.

  • Elastic Scaling Compute: Capably manages models with extensive feature sets, scaling resources as needed.

  • Automated Cross-Validation: Streamlines the validation process to confirm model reliability and accuracy.

  • Hyperparameter Optimization: Automatically tunes model parameters to optimize performance.

  • Algorithm Selection Control: Provides flexibility in choosing from leading algorithms such as XGBoost, random forest, elastic net, and other robust open-source options.

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HealthSphere provides specialized tools that transform raw data into complex variables specifically for healthcare, eliminating the need to construct additional infrastructure.

  • Advanced Processing: Transforms raw data into complex variables tailored for healthcare use, enabling precise and actionable insights.

  • Flexible Analysis Tools: Provides dynamic index dates, look-back periods, and prediction windows, allowing for tailored analytical approaches to suit specific needs.

  • Core Data Management: Ensures robust data integrity through ML feature versioning, change logs, rollback capabilities, and archiving.

  • Data Ingestion:  Streamlines the ingestion and standardization of data, establishing a solid foundation for subsequent analytical processes.


Explainability & Reporting

Clinicians and other key stakeholders are unlikely to trust and act on predictions they don't fully understand. HealthSphere's award-winning explainability features enhance the clarity and credibility of AI/ML-driven insights, fostering their adoption due to their accuracy, comprehensibility, and reliability.

  • Individual- and Population-Level Contributing Factors: Identifies and explains factors affecting health outcomes at both individual and community scales.

  • Fully Configurable Report Generation: Offers customizable reporting capabilities to meet diverse clinical and administrative needs.

  • Longitudinal Risk Tracking: Tracks risk metrics over time, providing a clear view of progression or improvement.

  • Patented Factor Evidence: Delivers detailed explanations of risk predictions at the individual level, utilizing Shapley value significance testing for precision.

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