The data science, machine learning and artificial intelligence pillar focuses on:

• Acute deterioration prediction: Developing predictive models to help analyze electronic health records to better serve hospitalized patients at risk for sepsis or other critical deterioration.
• Precision population health: Developing data infrastructure, predictive models and care models to help improve outcomes for behavioral/mental health and asthma by collecting data, identifying at-risk individuals and implementing proactive interventions to prevent emergency department visits and hospitalizations.
• Clinician and health system efficiency: Developing HIPAA-compliant infrastructure; regulatory framework for AI models, notifications and education; and AI-based triaging based on patient/family communications to increase efficiency within hospitals and across care networks.

To achieve these objectives, we will:

• Create frameworks for ethical AI that promote transparency, equity and
• Build data infrastructure for internal and external
• Incorporate innovative engineering and science into designing new AI solutions for clinical and patient-facing settings.
• Demonstrate the capability of using AI in the short-term to improve outcomes for children in and out of the hospital with acute or chronic conditions, clinician and health system efficiency, and prevention and wellness
• Scale successful strategies across Children’s and beyond through academic and industry collaborations.

We will develop and implement AI models to better care for hospitalized patients at risk for severe illness and for outpatients who require acute care at home. Focusing on clinical and operational staff at Children’s, as well as patients and their families, we will build strong foundations that prioritize patient privacy, increase clinician efficiency through automation of time-intensive routine tasks, and improve health system efficiency by creating systems that will lead to better communication. These improvements will help increase patient/family satisfaction through faster response times, increase access to care and reduce clinician burnout and turnover.

The projects within this pillar will demonstrate how the clinical application of data science and AI can cause real-world impact, leading to commercialized products that will help make healthcare systems in Georgia and beyond more efficient and accessible. Through donor support of data science, AI and machine learning, the PTC will be able to ethically use AI to help improve and save lives by keeping children out of the emergency department and helping those who are in the hospital receive the best care possible.