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DTSTAMP:20240325T185834Z
LOCATION:Salon A-1
DTSTART;TZID=America/Chicago:20240325T141000
DTEND;TZID=America/Chicago:20240325T143000
UID:HFESHCS_2024 International Symposium on Human Factors and Ergonomics i
 n Health Care_sess116_INDLEC135@linklings.com
SUMMARY:System Engineering Approach to Understand Sepsis Care Workflow dur
 ing Emergency Department Admissions
DESCRIPTION:Oral Presentations\n\nJackie Cha, Dechristian Franca Barbieri,
  and Shyam Ranganathan (Clemson University); Justin Ulrich and Catherine C
 hang (Prisma Health-Upstate); and Divya Srinivasan (Clemson University)\n\
 nSepsis is characterized by organ dysfunction resulting from infection, wi
 th no reliable single objective test and presenting difficulty in diagnosi
 s. There is a national challenge of sepsis detection and treatment; sepsis
  affects more than 1.7 million Americans annually, is a leading cause of d
 eath in US hospitals, and is the most expensive ailment treated in US hosp
 itals, costing more than $20 billion a year. Most of these cases (>80%) ar
 e diagnosed on admission and receive initial care in emergency departments
 . Furthermore, every hour of delayed diagnosis (and treatment) critically 
 increases mortality rates. National strategies for early identification ha
 ve been ongoing for over a decade, and some data-based screening tools are
  now available for early detection.\nThe use of well-designed AI-based pre
 dictive analytics tools to support point-of-care clinical decision making 
 (AI-CDSS technology) is a potential solution to help address sepsis treatm
 ent and care. Although various AI-based CDSS have been developed, a critic
 al bottleneck, however, is in intuitive design and integration of such dec
 ision-support systems with clinical workflows. Poor integration with clini
 cal workflows has led to limited improvements in outcomes because of ineff
 ective work design and resistance from care-provider teams to trust/adhere
  to such predictive diagnostics tools, thereby increasing their mental wor
 kload. \nClinicians and administrators at Prisma Health have developed and
  implemented best practice strategies to improve sepsis care by developing
  standardized care modules and CDSS in their electronic health record (EHR
 ) system. However, the utilization of this sepsis tool has been limited du
 e to friction of incorporating the tools into the current clinical workflo
 ws of both physicians and nurses. We will take a systems-approach to under
 stand the impacts of the technology with the current clinician workflow, p
 atient care, and hospital infrastructure. The Systems Engineering Initiati
 ve for Patient Safety (SEIPS) model is leveraged to complete a novel mappi
 ng of the clinical work system components of sepsis treatment and care in 
 the emergency department, as it relates to people (physicians, nurses, and
  patients); tools and technology (AI-CDSS and EHR system); care tasks; int
 ernal and external environments (physical environments and regulation/ pol
 icies); and organization (hospital leadership). The system component mappi
 ng is translated into visualizations to clearly identify the interdependen
 cies among the work. \nOur multidisciplinary team of clinicians, engineers
 , and data scientists will use the SEIPS model applied to sepsis on emerge
 ncy department admissions to understand and evaluate the quantifiable effe
 cts and workflow integration of the current AI-CDSS technology to improve 
 patient safety.\n\nTrack: Hospital Environments\n\nSession Chair: Kristen 
 Webster (Cincinnati Children's Hospital Medical Center)
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