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Predicting Hospital Readmissions

Preventing Readmissions and Saving Lives with AI


Patients with serious and chronic illnesses are treated in the hospital and then discharged. Unfortunately, according to multiple studies, up to 25% of these patients will be readmitted within 30 days to be treated again, often with less favorable outcomes. With a focus on value-based care, providers are trying to prevent unnecessary readmissions and improve patient care outcomes. Readmission can be significantly reduced by taking steps while the patient is still hospitalized, defining different actions during discharge, and taking steps post discharge to ensure compliance with home care regimens.


AI is ideally suited to tasks where the data inputs are complex and may elude clinicians. Readmissions risk prediction can require data about the specific patient’s recent care, their current condition, treatment, their home life and other risk factors from electronic medical records. AI models can use this information to provide a proactive assessment of their risk and notify clinicians while the patient is still hospitalized. AI can provide the reasons that will lead to readmission and also provide recommendations for the types of treatments that are most likely to be successful given the patient’s history. The reason codes are valuable to clinicians because they can pinpoint areas to focus on when developing a care plan for the patient and prevent unnecessary and costly tests.


The mission at is to democratize AI for all so that more people across industries can use the power of AI to solve business and social challenges. The healthcare industry is a key focus for the company with an initiative to help develop AI healthcare solutions including dedicated, experienced resources for customers, driving healthcare AI events and meetups for healthcare professionals, and membership in Health IT Now, the leading coalition of patient groups, provider organizations, employers, insurers, and other stakeholders. is already working with top healthcare companies including Change Healthcare, Armada Health, Kaiser Permanente, and HCA, and its products include industry leading features for machine learning interpretability required by the healthcare industry for compliance purposes.

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Adam Sullivan
Director, Change Healthcare

"H2O has been the driver for building models at scale. We are talking about billions of claims. You can't do this with standard off the shelf open source techniques. "

Allison Baker
Data Scientist, HCA

"With H2O we are building models to improve the patient experience in our hospitals and improve the nursing and doctor workflows as well."