The Institute for People and Technology (IPaT) is deeply engaged in advancing pediatric research and clinical innovation through a partnership with the Children’s Healthcare of Atlanta Pediatric Technology Center at Georgia Tech (PTC). The center brings clinical experts from Children’s together with Georgia Tech scientists and engineers to develop technological solutions to problems in the health and care of children. The PTC provides opportunities for interdisciplinary collaboration to create breakthrough discoveries that enhance the lives of children and young adults in Georgia and beyond.

IPaT is supporting research within two of PTC’s three core research pillars: data science, machine learning, and artificial intelligence; and patient‑centered care delivery. PTC’s third research pillar is focused on technologies and devices. With the expertise of IPaT’s research scientists, these joint efforts combine scientific expertise, clinical insight, and shared funding that are helping to transform research innovations into operational tools that directly support pediatric patient care at Children’s.

“IPaT is bringing two core competencies to both of these research pillars,” said Maribeth Gandy Coleman, IPaT’s director of research. “First, we’re advocating for and supporting the use of people-centered techniques to inform the research and co-designing the resulting system with all the stakeholders. Second, we’re also making sure we can translate this research into a real return on investment for Children’s. We are ensuring that what we design can be deployed in the hospital, and that it can be integrated with their existing systems and merge as seamlessly as possible with their existing workflows.”

Supporting Data Science, Machine Learning, and Artificial Intelligence (Pillar 1)
Pillar 1 focuses on harnessing artificial intelligence to enable more personalized and predictive pediatric care. The work aims to improve data collection infrastructure, support equitable AI practices, and build a Children’s-Georgia Tech pediatric AI collaboration that integrates advanced AI tools into clinical workflows.

Clinical Deterioration Prediction
One of the flagship projects within Pillar 1 involves developing machine learning models that can detect clinical deterioration in hospitalized children. The goal is to identify when a patient needs urgent escalation to the intensive care unit — faster and more accurately than traditional monitoring.

To achieve this, IPaT research scientists are:

• Extracting and securely transferring electronic health record (EHR) data from Children’s clinical systems.
• Training predictive models using that real‑world data.
• Building the software infrastructure required to deploy these models inside Children’s.
• Integrating model outputs directly into the EHR using Fast Healthcare Interoperability Resources communication protocols. (FHIR is an international standard for the electronic exchange of healthcare information.)

This infrastructure is intentionally designed not just for this single project but as a repeatable, scalable framework for future AI‑enabled clinical tools developed through the Children’s-Georgia Tech partnership.

AI-Enhanced Decision-Making for Hospital Operations
A second emerging project under Pillar 1 aims to address one of healthcare’s most persistent operational challenges: ICU capacity management. Seasonal fluctuations, such as surges in flu or Covid‑19 cases, can create sudden ICU demand surges and staff illnesses, which can make scheduling and staffing decisions challenging.

IPaT is building models that incorporate historical hospital activity, seasonal variation, and real‑time census and staffing levels to predict scheduling needs and help Children’s optimize resource allocation. This research is just beginning, but holds the potential for improving both care delivery and staff well‑being. More importantly, IPaT is applying user-centered design and research techniques along with the engineering work to engage with Children’s people and processes to ensure that these prediction and resource allocation models actually work, and that they will actually be used and useful in the Children’s clinical environment. 

 

Supporting Patient‑Centered Care Delivery (Pillar 2)
Pillar 2 seeks to improve pediatric outcomes by focusing on the “whole child” — physical, psychological, social, and emotional well‑being — while accounting for the needs of families, caregivers, and community environments. Particular emphasis is placed on behavioral health, rural healthcare access, and chronic illness in underserved populations.

IPaT contributes to this work on two fronts:

User Experience and Workflow Research
IPaT’s user experience (UX) researchers conduct interviews, workflow studies, and design evaluations with Children’s clinicians and staff. This human‑centered research helps shape the interfaces, processes, and technologies needed to deliver patient‑centered care in practical, usable ways. These contributions ensure that tools created through the partnership align with the realities of clinical practice.

Data Integration for Behavioral and Social Insights
For Pillar 2 research, IPaT’s secure data enclave enables Children’s EHR data to be transferred, stored, and analyzed in a HIPAA‑compliant environment. Researchers are using this infrastructure to combine clinical data with voluntarily contributed social media information from consenting participants. The aim is to explore indicators of psychological well‑being, behavioral health trends, and early warnings related to self‑harm.

A Secure, Scalable Data Infrastructure to Support Both Pillars
The IPaT secure data enclave provides a protected, secure environment for storing and analyzing sensitive patient information. It serves as the backbone connecting Georgia Tech researchers with Children’s clinical systems. Both Pillar 1 and Pillar 2 research initiatives rely on this Georgia Tech IPaT-managed secure infrastructure to safely enable:

• EHR data transfer and storage.
• Machine learning model development.
• Testing and validation workflows.
• Eventual operational deployment back into Children’s systems.

This secure, scalable architecture is central to the shared goal of translating research into actionable clinical tools.

Accelerating Pediatric Discovery 
Georgia Tech’s partnership with Children’s represents a powerful model for cross‑institutional innovation. By aligning IPaT’s strengths in human‑centered design, machine learning, and secure data systems with Children’s clinical expertise, IPaT is helping to build solutions that move quickly from concept to bedside.

As these projects grow, especially with the ongoing expansion of the clinical deterioration system and the launch of the AI-enhanced operations initiative, IPaT research scientists anticipate even greater opportunities to support Children’s mission and improve pediatric health outcomes