Team Research

The intensive care unit (ICU) is one of the most high-stakes environments in healthcare, characterized by complex patient acuity and constant, time-sensitive decision-making. These demands place high workloads on healthcare workers (HCWs), which directly impact HCW well-being and compromise patient safety. Burnout rates of the ICU team members are among the highest in healthcare, at nearly 70%, with compelling evidence linking excessive workload to the 1.5 million adverse drug events that occur annually in the U.S. Current staffing procedures rely on unvalidated metrics, such as doses dispensed, medications verified, or administrations completed, which capture only isolated tasks and fail to account for the complexities of team-based bedside care, the goal standard for safe and effective ICU practice. 

To address this gap, we propose the development of DRIVE (Data-dRiven ICU Volume intErvention), an evidence-based, real-time dashboard that integrates HCW staffing data with patient care needs to improve staffing decisions and optimize workloads. This interdisciplinary project brings together expertise from the College of Pharmacy, College of Education, College of Public Health, College of Veterinary Medicine, and School of Computing. 

The project has both practical and scholarly goals. From a practical perspective, DRIVE will provide the ICU team members and administrators with real-time, patient-level workload measures to guide staffing decisions that improve patient safety and quality of care. From a research perspective, DRIVE will serve as a platform for studying the impact of workload on HCW well-being and patient outcomes. 

Workload factors to be included in DRIVE will be identified using the TURF (Task, User, Representation, and Function) framework. We will ask ICU HCWs and administrators to participate in semi-structured interviews and collect perspectives on (1) safe care goals and tasks, (2) perceptions of AI-driven workload models, (3) design requirements for information presentation, and (4) existing workflows. 

These insights will guide the development of a prototype DRIVE dashboard, a wireframe of which can be seen in the accompanying figure. Usability testing will then be conducted, using simulated cases and think-aloud protocols to assess transparency (including predictability and observability), augment cognition, and trustworthiness. Robust statistical approaches will be applied, with iterative refinements based on feedback and observations. The final DRIVE design will be implemented in the ICU setting and formally evaluated in a workflow comparison study using validated measures, including (1) the Situational Awareness Global Assessment Technique (SAGAT) for situation awareness, (2) accuracy, (3) time on task, and (4) the System Usability Scale for usability metrics. 

Through interdisciplinary collaboration, DRIVE will enhance ICU staffing practices and workload allocation. This innovation will reduce HCW burnout while enhancing patient safety and quality of care. As a pre-seed effort, team development will be supported to establish a strong foundation for competitive applications to internal UGA seed grants and extramural funding opportunities. 

Team Lead

Smith, Susan
susan.smith@uga.edu
College: College of Pharmacy
Department: Clinical and Administrative Pharmacy

Team Members

Chin, XianYan
xchen@uga.edu
College: College of Public Health
Department: Epidemiology & Biostatistics

Hill, Janette
janette@uga.edu
College: Mary Frances Early College of Education
Department: Workforce Education and Instructional Technology

Keedy, Chelsea
chelsea.keedy@uga.edu
College: College of Pharmacy)
Department: Clinical & Administrative Pharmacy

Kim, Eunice
sj.eunicekim@uga.edu
College: College of Pharmacy / College of Veterinary Medicine
Department: Clinical & Administrative Pharmacy / Pathology

Sikora, Andrea
andrea.sikora@cuanschutz.edu
College: College of Pharmacy
Department: Clinical & Administrative Pharmacy 

Xiang, Zhen
zsiangaa@uga.edu
College: Franklin College of Arts and Science / College of Engineering
Department: School of Computing