Accuracy of bar codes versus handwriting for recording trauma resuscitation events

To compare the accuracy of computerized bar code data entry with conventional handwritten data entry during videotaped trauma resuscitations. Laboratory; video simulation. Twenty-four emergency nurses. The nurses viewed videotapes of four different major trauma resuscitations during a single session. Each nurse recorded resuscitation events by handwritten entry in two cases and by bar code entry in another two. A computerized bar code system was designed specifically for contemporaneous charting of rapidly occurring events during trauma resuscitations. The handwritten and bar-coded records then were compared with a master list of events, and the number of entry errors were counted. Errors were defined as “omissions” (failing to record an event), “commissions” (recording an event that did not occur), or “inaccuracies” (errors in recording details of an event). Differences in the number of entry errors between the two recording methods were compared using unpaired t-tests. Differences in the number of errors after adjusting for the different nurses, different case being viewed, and order of viewing were analyzed using balanced analysis of variance techniques. P < .05 was considered significant. The mean ± SEM number of total errors per record for bar codes was 2.63 ± 0.24 compared with 4.48 ± 0.30 for handwriting ( P < .0001). The mean number of omissions per record for bar codes was 2.25 ± 0.21 compared with 3.65 ± 0.27 for handwriting ( P = .0001). The mean number of inaccuracies per record for bar codes was 0.38 ± 0.10 compared with 0.83 ± 0.12 for handwriting ( P = .0038). There were no commission-type errors. Computerized bar code data entry of trauma resuscitation events had significantly fewer entry errors than handwritten data entry in a laboratory setting. Potential advantages of bar code data entry include keyless data entry, automatic time-stamping, standardization of documentation, legibility of the medical record, and “point-of-care” data capture.