This application addresses the broad challenge Area (10) Information Technology for Processing Health Care Data and specific challenge topic, 10-LM-102, Advanced decision support for complex clinical decisions. BACKGROUND: Sepsis is characterized by systemic inflammation secondary to infection. It is common and can affect individuals of any age, race, or sex. More than 750,000 cases are diagnosed in the United States annually, and among patients with associated organ dysfunction, mortality approaches 30%. Patients with severe disease often require intensive care unit management, endure prolonged hospital stays, and consume substantial healthcare resources. A growing body of evidence has emerged to guide sepsis management and improve outcomes. RATIONALE: Evidenced-based recommendations are widely used for sepsis management but are challenging to implement in the intensive care unit (ICU) setting. The ICU is an information-intensive environment where rotating teams of physicians manage critically ill patients by analyzing multiple, temporally discontinuous pieces of data. Adding a complex, time-sensitive protocol-as required in sepsis treatment-exacerbates the discrepancy between supply and demand for time and information-management capacity. For these reasons, we believe that the ICU setting in general, and sepsis management specifically, are ideally suited for a technology intervention that will streamline identification and information handling in septic patients providing just-in-time decision support. HYPOTHESIS: We hypothesize that automated identification and electronically-supported process management for sepsis will shorten the time to diagnosis and initiation of therapy, facilitate improved compliance with evidence-based management recommendations, and positively impact pertinent clinical outcomes, such as ICU and hospital length of stay and requirement for mechanical ventilation. METHODS: We have developed a novel suite of electronic applications that leverage Vanderbilt's advanced technology infrastructure, leadership in clinical trials related to sepsis, and robust medical informatics support. These applications will constantly monitor the electronic medical record and electronic orders of each patient for data suggestive of developing sepsis, or in patients diagnosed with sepsis, for evidence that recommended management guidelines are being satisfied. These automated applications will interact with physicians by way of real-time notifications to alert them to the possibility that sepsis has developed. Our software suite, to be deployed on the hospital's ubiquitous clinical work stations, will expedite identification of septic patients. Additional software will display patient-specific, evidence-based management recommendations to physicians providing the opportunity for greatly improved patient care and outcomes. We will design and deploy a novel suite of interactive electronic applications to facilitate early detection of septic patients and guide physicians toward guideline-driven management practices. We hypothesize that this suite of electronic applications will result in earlier identification of septic patients, improve physician adherence to recommended guidelines for management of sepsis, and improve clinical outcomes for patients.

Public Health Relevance

We will design and deploy a novel suite of interactive electronic applications to facilitate early detection of septic patients and guide physicians toward guideline-driven management practices. We hypothesize that this suite of electronic applications will result in earlier identification of septic patients, improve physician adherence to recommended guidelines for management of sepsis, and improve clinical outcomes for patients.

Agency
National Institute of Health (NIH)
Institute
National Library of Medicine (NLM)
Type
NIH Challenge Grants and Partnerships Program (RC1)
Project #
1RC1LM010310-01
Application #
7819433
Study Section
Special Emphasis Panel (ZRG1-HDM-G (58))
Program Officer
Florance, Valerie
Project Start
2009-09-30
Project End
2011-09-29
Budget Start
2009-09-30
Budget End
2010-09-29
Support Year
1
Fiscal Year
2009
Total Cost
$428,130
Indirect Cost
Name
Vanderbilt University Medical Center
Department
Internal Medicine/Medicine
Type
Schools of Medicine
DUNS #
004413456
City
Nashville
State
TN
Country
United States
Zip Code
37212
Semler, Matthew W; Weavind, Liza; Hooper, Michael H et al. (2015) An Electronic Tool for the Evaluation and Treatment of Sepsis in the ICU: A Randomized Controlled Trial. Crit Care Med 43:1595-602
Hooper, Michael H; Weavind, Lisa; Wheeler, Arthur P et al. (2012) Randomized trial of automated, electronic monitoring to facilitate early detection of sepsis in the intensive care unit*. Crit Care Med 40:2096-101