Impact of a Clinical Decision Model for Febrile Children at Risk for Serious Bacterial Infections at the Emergency Department: A Randomized Controlled Trial

Abstract

ObjectivesTo assess the impact of a clinical decision model for febrile children at risk for serious bacterial infections (SBI) attending the emergency department (ED).MethodsRandomized controlled trial with 439 febrile children, aged 1 month-16 years, attending the pediatric ED of a Dutch university hospital during 2010-2012. Febrile children were randomly assigned to the intervention (clinical decision model; n=219) or the control group (usual care; n=220). The clinical decision model included clinical symptoms, vital signs, and C-reactive protein and provided high/low-risks for “pneumonia” and “other SBI”. Nurses were guided by the intervention to initiate additional tests for high-risk children. The clinical decision model was evaluated by 1) area-under-the-receiver-operating-characteristic-curve (AUC) to indicate discriminative ability and 2) feasibility, to measure nurses’ compliance to model recommendations. Primary patient outcome was defined as correct SBI diagnoses. Secondary process outcomes were defined as length of stay; diagnostic tests; antibiotic treatment; hospital admission; revisits and medical costs.ResultsThe decision model had good discriminative ability for both pneumonia (n=33; AUC 0.83 (95% CI 0.75-0.90)) and other SBI (n=22; AUC 0.81 (95% CI 0.72-0.90)). Compliance to model recommendations was high (86%). No differences in correct SBI determination were observed. Application of the clinical decision model resulted in less full-blood-counts (14% vs. 22%, p-value<0.05) and more urine-dipstick testing (71% vs. 61%, p-value<0.05).ConclusionsIn contrast to our expectations no substantial impact on patient outcome was perceived. The clinical decision model preserved, however, good discriminatory ability to detect SBI, achieved good compliance among nurses and resulted in a more standardized diagnostic approach towards febrile children, with less full blood-counts and more rightfully urine-dipstick testing.Trial RegistrationNederlands Trial Register NTR2381

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“…35 A second evaluated the use of the Nijman risk prediction model to guide decisions, and no impact on antibiotic prescribing or hospital admission was observed. 36 Future impact studies need to evaluate the behaviors associated with decision-making. This has been of considerable importance in evaluating interventions to 8 rationalize antibiotic prescribing.…”

Predictors of fever-related admissions to a paediatric assessment unit, ward and reattendances in a South London emergency department: the CABIN 2 study

“…These guidelines lack the support of large prospective studies to aid clinical decision-making relating to admission and safe discharge and they are also insufficiently sensitive or specific for the diagnosis of SBI 6. There are alternative models demonstrating additional value of CRP that can discriminate effectively between pneumonia and other SBI but have no impact on patient outcome 7 8…”

Supporting decisions to increase the safe discharge of children with febrile illness from the emergency department: a systematic review and meta-analysis

“…Figure 1 provides a flow diagram of the search process. Two impact studies evaluated decision rules,20 21 and the remainder were diagnostic accuracy studies of prediction rules. The characteristics of included studies are available as online supplementary tables.…”

“…Two impact studies evaluated decision rules in the management of children with febrile illness in the ED 20 21. One rule was based upon the Lab score and undertaken in children under 3 years (n=271).…”