Randomized Trial of a Clinical Decision Support System: Impact on the Management of Children with Fever without Apparent Source
- aDepartment of Pediatrics, Sophia Children’s Hospital, Erasmus MC—University Medical Center Rotterdam, The Netherlands
- bDepartment of Public Health, Center for Medical Decision Making, Erasmus MC—University Medical Center Rotterdam, The Netherlands
- cDepartment of Medical Informatics, Erasmus MC—University Medical Center Rotterdam, The Netherlands
- Correspondence: Henriëtte A. Moll, Department of General Paediatrics, Room SP 1540, Sophia Children’s Hospital, Erasmus Medical Centre, P.O. Box 2060 CB Rotterdam, The Netherlands; e-mail: <h.a.moll{at}erasmusmc.nl>
- Received 31 May 2006
- Accepted 9 August 2007
Introduction
The management of young febrile children is an everyday challenge for emergency department (ED) physicians. Distinguishing children with mild viral disease from those with serious bacterial infection (SBI) is difficult as clinical presentation is often non-specific.1 2 3 Early identification of children at risk for SBI could support appropriate management in terms of diagnostic and therapeutic decisions.
For several diagnostic and therapeutic problems, guidelines or clinical prediction rules were developed.4 5 6 7 8 9 10 Implementation of guidelines may result in reduced diagnostic testing, improved documentation, more appropriate treatment, and a reduction of the time spent in the ED.5 6 However, the translation of guidelines and prediction rules into clinical practice is still a major challenge. Studies of the actual clinical impact of decision rules, i.e., whether or not the use of a decision rule improves clinical decisions or benefits patient care, are limited. Reilly found that decision rule impact analysis was performed in only 9 out of 109 studies in their review. This may be due to limited implementation strategies of decision rules in routine clinical practice.11 Clinical decision support systems (CDSS) may be able to integrate available knowledge (e.g., decision rules) into clinical practice.12 Key features for successful CDSS implementation have been described, but little is known about the effects of CDSS-utilization on patient outcomes.13 14 15
At the Erasmus Medical Center in Rotterdam, The Netherlands, a CDSS was developed for the diagnostic management of young children with fever without apparent source (FWS), based on previously derived and validated prediction rules. From July 2003, the computerized CDSS was used routinely by the ED nursing staff to register children presenting with fever. First, the CDSS automatically identified children with FWS, second, children at high risk for SBI were identified based on clinical …
