Preventing Infection

How well do you understand data in your hospital?

Pariveda was engaged by a Texas-based pediatric healthcare system whose mission is to create a healthier future for children and women throughout the global community by leading in patient care, education, and research. It consistently ranks among the top children’s hospitals in the nation because of this commitment to quality care. Recently, this hospital system has been focused on digitally transforming the organization to increase their efficiency both clinically and operationally. 

Use Machine Learning to prevent further infection 

This organization is exploring the use of Predictive Analytics, specifically Machine Learning (ML), to reduce the instances of hospital-acquired infectious diseases. Currently, physicians rely on their own experience and intuition as well as vital sign changes as indicators that an infection may have already begun. However, the organization wanted to understand if an ML model could utilize patient history and other process-related data to predict the probability of a patient contracting an infectious disease before an infection even begins. Understanding which patients are at a greater risk of contracting an infectious disease, and the reasons why can help clinicians proactively address these risks and potentially stave off infection.

Understanding your patients for better health outcomes 

The pediatric healthcare system partnered with Pariveda to build an Infectious Disease Risk Prediction model. Through this model, they are able to identify the probability of a patient contracting an infectious disease sometime in the next 3 days for all patients in a specified population. The model is also able to inform clinicians on the factors that are highly correlated to that individual’s risk levels. For example, physicians can now know that patient A has an 83% chance of contracting an infectious disease sometime in the next 3 days because she has been administered a specific type of medication, has had more than 4 dressing changes in the past 24 hours and currently has significant dermatological issues. With this information, physicians can now practice targeted and personalized care with the hopes of proactively intervening before an infection begins. 

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