Early Detection of Hospitalized Patients at Risk for Developing Sepsis

Author: Stephen Jones, MD

Primary Advisor: Dean Sittig, PhD (co-author)

Committee Members: Jiajie Zhang, PhD (co-author); Laura J. Moore, MD (co-author); Fred A. Moore, MD (co-author); Todd R. Johnson, PhD (co-author)

Masters thesis, The University of Texas School of Biomedical Informatics at Houston.

Abstract:

Sepsis is as an overwhelming inflammatory reaction in response to an infection. The end result is often fatal. Sepsis is a continuum, with escalating mortality rates the further along the continuum the patient proceeds. Despite tremendous research efforts, death rates from septic shock remains unchanged at > 50%. The best way to prevent death from sepsis is to identify sepsis early in its onset and timely initiation of appropriate goal directed therapy. The early clinical signs of sepsis are non-specific and often not detected in a timely manner. This is a serious health care quality problem. Using a human centered methodology, UFuRT, we developed a functioning prototype of a web based systemic inflammatory response syndrome screening tool. The UFuRT methodology is a useful framework with which to guide efforts to devise web-based screening forms intended for use by busy healthcare professionals in the complex and dynamic environment found in modern tertiary care surgical intensive care units and general inpatient surgical wards at major academic referral centers. The online implementation of a sepsis screening tool is a valid predictor of sepsis for general surgical patients, more cost effective, less cumbersome, and less error prone than a paper based instrument and shows promise as a tool to help reduce mortality and morbidity from sepsis in the inpatient setting at major academic referral centers.