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Predicting Hospital Acquired Infections (HAIs)

Challenges

 

Hospital or Healthcare acquired infections (HAIs), such as central-line associated bloodstream infections (CLABSIs) are a huge problem for patients and providers. An estimated 250,000 CLABSIs occur in the U.S. annually, according to the Centers for Disease Control and Prevention (CDC). Patient mortality rates associated with CLABSI are up to 25 percent and the cost of the infection is up to $36,000 per episode, according to the CDC.

Why Med.ai

The mission at Healthmed. AIis 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. Healthmed. AI 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.

Opportunity

Using AI driven models, providers can predict which patients are most likely to develop central-line infections by looking and a variety of data including patient information, treatment history and staff history. With this prediction, clinicians can monitor high-risk patients and intervene to reduce risk. AI driven models can also identify the reasons for increased risk and provide reason codes that point clinicians to recommended treatments and preventative measures for future patients.