Hospital Readmission Prediction Model for Leading EHR & HealthTech Vendor

Published: April 10, 2024

Discover how Reveal used predictive modeling to reduce patient readmissions, determining whether a patient was likely to need skilled nursing care or home care after hospital discharge.

Minimizing Patient Readmissions

Reducing patient readmissions after hospital discharge is critical. Readmissions introduce costs & challenges for patients as well as providers. Our client wanted to leverage predictive modeling to determine the relative risk of readmission for individual patients.

Crafting the Solution

Reveal built a tailor-made machine learning model to forecast patients’ need for post-discharge care and readmission risk. The model analyzed over 10TBs of hospital discharge and referral data that was gathered over several years. A HIPAA-compliant, AWS-based data science platform was built that ensured the confidentiality and integrity of patient data while enabling seamless data processing & analysis.

Streamlined Healthcare Efficiency

The implementation of Reveal’s solution demonstrated how predictive modeling could generate impactful insights. By proactively addressing patient needs, the readmission risks were reduced. This model also optimized resource allocation and workflows leading to improved patient outcomes.

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