Abstract
Background - Pediatric patient blood management (PBM) programs require continuous surveillance of errors and near misses. However, most PBM programs rely on passive surveillance methods. Our objective was to develop and evaluate a set of automated trigger tools for active surveillance of pediatric PBM errors.
Materials and methods - We used the Rand-UCLA method with an expert panel of pediatric transfusion medicine specialists to identify and prioritize candidate trigger tools for all transfused blood products. We then iteratively developed automated queries of electronic health record (EHR) data for the highest priority triggers. Two physicians manually reviewed a subset of cases meeting trigger tool criteria and estimated each trigger tool’s positive predictive value (PPV). We then estimated the rate of PBM errors, whether they reached the patient, and adverse events for each trigger tool across four years in a single pediatric health system.
Results - We identified 28 potential triggers for pediatric PBM errors and developed 5 automated trigger tools (positive patient identification, missing irradiation, unwashed products despite prior anaphylaxis, transfusion lasting >4 hours, over-transfusion by volume). The PPV for ordering errors ranged from 38-100%. The most frequently detected near miss event reaching patients was first transfusions without positive patient identification (estimate 303, 95% CI: 288-318 per year). The only adverse events detected were from over-transfusions by volume, including 4 adverse events detected on manual review that had not been reported in passive surveillance systems.
Discussion - It is feasible to automatically detect pediatric PBM errors using existing data captured in the EHR that enable active surveillance systems. Over-transfusions may be one of the most frequent causes of harm in the pediatric environment.
Downloads
pdf
- Abstract viewed - 485 times
- pdf downloaded - 222 times