Ashish Gupta, School of Business, presented on a panel at Mayo Clinic Conference on Systems Engineering and Operations Research in Health Care August 9-11. The presentation focused on Simulation and Modeling Application in ICU System Operational Analysis: Case Study of Sepsis Resuscitation. Panelist were Yue Dong, MD (Mayo Clinic) and Ashish Gupta, PhD (Minnesota State University Moorhead), Fazi Amirahmadi, PhD  (Mayo Clinic) and Chris P. Schieffer (Mayo Clinic, Head for Clinical Practice and Quality Support).

Panel Objectives

The panel focused on improving ICU performance with the goal of:

  • Identifying challenges facing healthcare professionals to improve the healthcare delivery: Systems Thinking and Patient Safety
  • Summarizing simulation and modeling tools used for quality improvement and applications in healthcare
  • Using human factor framework for systematic analysis and optimization of complex system processes and interventions
  • Presenting a case study on applying modeling for Sepsis resuscitation


In 2005, Intensive Care Unit (ICU) costs represented 13.4% of hospital costs, 4.1% of national healthcare expenditures and 0.66% of the gross domestic product in the US. ICU, as multidisciplinary specialty practices, represent a major section of hospital operation, patient outcome impact, and resources (providers, instruments, medications, etc.)utilization. Due to the aging population and decrease in reimbursement, an important challenge for all hospitals now is to better manage ICU to provide improved patient outcome with less operating costs. Modern ICU practice is complex that not only includes life threatening patho-physiologic disturbances, but also a complex “system” dimension: health care providers’ performance, organizational factors, environmental factors, patient and family member preferences and interaction between each component. ICU’s unique service model (up-stream from floor/ER/OR, down-stream: floor/home/readmissions,) and connections with other units in the hospital (blood bank, radiology, labs, etc.) makes it very unique for modeling tasks. The uncertainties due to provider and patient variations imposes extra challenge to model the health care delivery process in ICU. How to deliver care in a timely and efficient manner is a challenge for both providers and ICU managers. For example, time to intervention (myocardial infarction bleeding, trauma, resuscitation, dialysis, etc.) have been shown to have direct impact on patient outcome Sepsis resuscitation model will be discussed as a sample to demonstrate the potential benefit to utilize the OR tools. Further investigation is needed to understand system organizational factors that contribute to poor patient outcomes beyond traditional perspective from patient risk factors, pharmaceutical interventions and provider education.