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. 2015 Nov;36(11):1313-7.
doi: 10.1017/ice.2015.179. Epub 2015 Aug 17.

A Pilot Study of a Computerized Decision Support System to Detect Invasive Fungal Infection in Pediatric Hematology/Oncology Patients

Adam Bartlett  1 , Emma Goeman  1 , Aditi Vedi  2 , Mona Mostaghim  3 , Toby Trahair  4 , Tracey A O'Brien  4 , Pamela Palasanthiran  1 , Brendan McMullan  1
Affiliations

A Pilot Study of a Computerized Decision Support System to Detect Invasive Fungal Infection in Pediatric Hematology/Oncology Patients

Adam Bartlett et al. Infect Control Hosp Epidemiol. 2015 Nov.

Abstract

Objective: Computerized decision support systems (CDSSs) can provide indication-specific antimicrobial recommendations and approvals as part of hospital antimicrobial stewardship (AMS) programs. The aim of this study was to assess the performance of a CDSS for surveillance of invasive fungal infections (IFIs) in an inpatient hematology/oncology cohort.

Methods: Between November 1, 2012, and October 31, 2013, pediatric hematology/oncology inpatients diagnosed with an IFI were identified through an audit of the CDSS and confirmed by medical record review. The results were compared to hospital diagnostic-related group (DRG) coding for IFI throughout the same period.

Results: A total of 83 patients were prescribed systemic antifungals according to the CDSS for the 12-month period. The CDSS correctly identified 19 patients with IFI on medical record review, compared with 10 patients identified by DRG coding, of whom 9 were confirmed to have IFI on medical record review.

Conclusions: CDSS was superior to diagnostic coding in detecting IFI in an inpatient pediatric hematology/oncology cohort. The functionality of CDSS lends itself to inpatient infectious diseases surveillance but depends on prescriber adherence.

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