TY - JOUR
T1 - How good is our diagnostic intuition? Clinician prediction of bacteremia in critically ill children
AU - Hoops, Katherine E.M.
AU - Fackler, James C.
AU - King, Anne
AU - Colantuoni, Elizabeth
AU - Milstone, Aaron M.
AU - Woods-Hill, Charlotte
N1 - Funding Information:
This study was conducted with funding support from the MITRE Corporation. The MITRE Corporation did not have a role in the collection, analysis, nor interpretation of data nor in the writing of this manuscript. Dr. Milstone is supported by an NIH K24 (K24AI141580).
Publisher Copyright:
© 2020 The Author(s).
PY - 2020/7/2
Y1 - 2020/7/2
N2 - Background: Clinical intuition and nonanalytic reasoning play a major role in clinical hypothesis generation; however, clinicians' intuition about whether a critically ill child is bacteremic has not been explored. We endeavored to assess pediatric critical care clinicians' ability to predict bacteremia and to evaluate what affected the accuracy of those predictions. Methods: We conducted a retrospective review of clinicians' responses to a sepsis screening tool ("Early Sepsis Detection Tool"or "ESDT") over 6 months. The ESDT was completed during the initial evaluation of a possible sepsis episode. If a culture was ordered, they were asked to predict if the culture would be positive or negative. Culture results were compared to predictions for each episode as well as vital signs and laboratory data from the preceding 24 h. Results: From January to July 2017, 266 ESDTs were completed. Of the 135 blood culture episodes, 15% of cultures were positive. Clinicians correctly predicted patients with bacteremia in 82% of cases, but the positive predictive value was just 28% as there was a tendency to overestimate the presence of bacteremia. The negative predictive value was 96%. The presence of bandemia, thrombocytopenia, and abnormal CRP were associated with increased likelihood of correct positive prediction. Conclusions: Clinicians are accurate in predicting critically ill children whose blood cultures, obtained for symptoms of sepsis, will be negative. Clinicians frequently overestimate the presence of bacteremia. The combination of evidence-based practice guidelines and bedside judgment should be leveraged to optimize diagnosis of bacteremia.
AB - Background: Clinical intuition and nonanalytic reasoning play a major role in clinical hypothesis generation; however, clinicians' intuition about whether a critically ill child is bacteremic has not been explored. We endeavored to assess pediatric critical care clinicians' ability to predict bacteremia and to evaluate what affected the accuracy of those predictions. Methods: We conducted a retrospective review of clinicians' responses to a sepsis screening tool ("Early Sepsis Detection Tool"or "ESDT") over 6 months. The ESDT was completed during the initial evaluation of a possible sepsis episode. If a culture was ordered, they were asked to predict if the culture would be positive or negative. Culture results were compared to predictions for each episode as well as vital signs and laboratory data from the preceding 24 h. Results: From January to July 2017, 266 ESDTs were completed. Of the 135 blood culture episodes, 15% of cultures were positive. Clinicians correctly predicted patients with bacteremia in 82% of cases, but the positive predictive value was just 28% as there was a tendency to overestimate the presence of bacteremia. The negative predictive value was 96%. The presence of bandemia, thrombocytopenia, and abnormal CRP were associated with increased likelihood of correct positive prediction. Conclusions: Clinicians are accurate in predicting critically ill children whose blood cultures, obtained for symptoms of sepsis, will be negative. Clinicians frequently overestimate the presence of bacteremia. The combination of evidence-based practice guidelines and bedside judgment should be leveraged to optimize diagnosis of bacteremia.
KW - Bacteremia
KW - Decision support
KW - Prediction
KW - Quality improvement
KW - Sepsis
KW - Stewardship
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U2 - 10.1186/s12911-020-01165-3
DO - 10.1186/s12911-020-01165-3
M3 - Article
C2 - 32616046
AN - SCOPUS:85087471561
SN - 1472-6947
VL - 20
JO - BMC Medical Informatics and Decision Making
JF - BMC Medical Informatics and Decision Making
IS - 1
M1 - 144
ER -