Sepsis, the systemic response to infection, is a diagnostic challenge and a leading cause of death worldwide. There are more deaths attributable to sepsis than acute myocardial infarction, stroke, or cancer. Failure to recognize the early signs and symptoms of sepsis and institute aggressive management is associated with significant increases in mortality for children and adults. The early signs of sepsis are subtle and extensive clinical experience has traditionally been required to recognize and interpret these cues reliably. At a time when the incidence of sepsis is rising, resident work hour restrictions have limited the novice clinician's exposure and opportunities to gain experience with these patients. This proposal represents one of the first efforts to understand the differences in the ways that novice and expert clinicians recognize the septic patient and the first time that the expert's approach will be leveraged as a means to accelerate the development of expertise in novice clinicians. The overall objective of this project is to identify the behaviors that distinguish the expert's approach to the early recognition of sepsis and to use that data to accelerate the acquisition of expertise from the novice to expert level. Our central hypothesis is that simulation-based training can accelerate the development of expertise needed by novice clinicians to quickly and accurately recognize sepsis. The rationale for the proposed research is that, by identifying the unique elements of the expert's approach to sepsis, simulation-based training to accelerate the acquisition of these skills for the novice provider becomes possible. The proposed research is relevant to the mission of the Agency for Healthcare Research and Quality because it addresses the missions of the patient safety and innovations/emerging issues portfolios concurrently. We will test our central hypothesis by pursuing the following two specific aims: 1) Determine the behaviors that characterize and differentiate the expert from the novice in the recognition of sepsis at the bedside and 2) Develop and implement simulation-based learning interventions that accelerate the development of expertise in relation to sepsis recognition. The proposed research is significant because it is the first step in the development of an approach to accelerate the acquisition of expertise in the recognition of sepsis-a condition in which only early goal directed therapy has been shown to improve survival. This project is innovative because we will use cognitive task analysis to identify the behaviors that distinguish expert clinicians and use this information to develop and implement simulation-based training that will provide novice clinicians with the tools that will enable them to rapidly attain clinical expertise. We will also employ methods that have not previously been used in healthcare, including training based on recognition primed decision making. The use of cognitive task analysis and simulation-based training within a naturalistic decision making framework will create opportunities to accelerate the development of expertise for novice clinicians not only in pediatrics, but across multiple critical healthcare domains.

Public Health Relevance

Sepsis is a leading cause of death worldwide and a diagnostic challenge for novice clinicians. The current proposal is one of the first efforts to use cognitive task analysis to identify the distinguishing elements of the expert's approach to the early recognition of sepsis. It is also the first effort to use simulation based training and recognition primed decision making to accelerate the development of expertise in the recognition of sepsis by the novice clinician.

Agency
National Institute of Health (NIH)
Institute
Agency for Healthcare Research and Quality (AHRQ)
Type
Research Demonstration and Dissemination Projects (R18)
Project #
5R18HS020455-02
Application #
8247662
Study Section
Special Emphasis Panel (ZHS1-HSR-Y (02))
Program Officer
Henriksen, Kerm
Project Start
2011-04-01
Project End
2014-03-31
Budget Start
2012-04-01
Budget End
2013-03-31
Support Year
2
Fiscal Year
2012
Total Cost
Indirect Cost
Name
Cincinnati Children's Hospital Medical Center
Department
Type
DUNS #
071284913
City
Cincinnati
State
OH
Country
United States
Zip Code
45229