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First published March 31, 2005 as JAMIA PrePrint; doi:10.1197/jamia.M1692
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J Am Med Inform Assoc. 2005;12:390-397. DOI 10.1197/jamia.M1692.
© 2005 American Medical Informatics Association


Application of Information Technology

Detection and Prevention of Medication Errors Using Real-Time Bedside Nurse Charting

Nancy C. Nelson, RN, MS, R. Scott Evans, PhD, Matthew H. Samore, MD and Reed M. Gardner, PhD

Affiliation of the authors: Department of Medical Informatics, LDS Hospital and University of Utah, Salt Lake City, UT.

Correspondence and reprints: Nancy C. Nelson, RN, MS, Department of Medical Informatics, LDS Hospital, 8th Avenue and "C" Street, Salt Lake City, UT 84143; e-mail: <ldnnelso{at}ihc.com>.

Received for publication: 09/03/04; accepted for publication: 02/11/05.

Objective: Charting systems with decision support have been developed to assist with medication charting, but many of the features of these programs are not properly used in their clinical application. An analysis of medication error reports at LDS Hospital revealed the occurrence of errors that should have been detected and prevented by decision support features if real-time entry at the bedside had taken place. The aim of this study was to increase the real-time bedside charting behavior of nurses.

Design: A quasiexperimental before and after design was used. The study took place in two 40-bed surgical units, one of which served as the study unit, the other as control unit. The study unit received educational intervention about error avoidance through real-time bedside charting, and 12 weeks of monitoring and performance feedback. The real-time and bedside charting rates for the study and control units were measured before and after the intervention.

Results: Before the intervention on the study unit, the real-time charting rate was 59% and the bedside rate was 40%. At the conclusion of a 12-week intervention period, the real-time rate increased to 73% and the bedside rate increased to 63%. Postintervention real-time rates were 75% after eight weeks and remained at 75% after one year. Equivalent control unit real-time rates varied from 53% to 57%, and bedside rates varied from 34% to 44% during the same intervals.

Conclusion: Targeted educational intervention and monitored feedback yielded measurable improvements in the effective use of the computerized medication charting system and must be an ongoing process.




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