Volume 24, Issue 5 e12679
ORIGINAL RESEARCH PAPER

The effect of workload on nurses' non-observance errors in medication administration processes: A cross-sectional study

Haizhe Jin PhD

Corresponding Author

Haizhe Jin PhD

Lecturer

Department of Industrial Engineering, Northeastern University, Shenyang, China

Correspondence

Haizhe Jin, Department of Industrial Engineering, Northeastern University, 3-11, Wenhua Road, Heping District, Shenyang, China.

Email: [email protected]

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Han Chen MS

Han Chen MS

Master Student

Department of Industrial Engineering, Northeastern University, Shenyang, China

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Masahiko Munechika PhD

Masahiko Munechika PhD

Professor

Faculty of Science and Engineering, Waseda University, Tokyo, Japan

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Masataka Sano PhD

Masataka Sano PhD

Associate Professor

Department of Management Information Science, Chiba Institute of Technology, Chiba, Japan

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Chisato Kajihara PhD

Chisato Kajihara PhD

Assistant Professor

Department of Industrial and Management Systems Engineering, Waseda University, Tokyo, Japan

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First published: 12 July 2018
Citations: 14

Abstract

Aim

This study, based on actual medical error cases involving nurses, sought to identify non-observance errors—defying the standard operating procedures—in medication administration processes, and clarify the relationship between nursing workload and such behaviours.

Methods

Based on a cross-sectional survey, non-observance error cases were collected from three Japanese hospitals between January and December 2014, using self-reported data from participating nurses. Standard operating procedures and actual error content were compared to identify non-observance errors and workload. The statistical analysis was used to determine the relationship between non-observance error and workload.

Results

A total of 637 error cases were found in administering medication, of which 163 (25.6%) were workload-related non-observance errors. Individual analysis of the 163 cases identified seven workload issues that caused non-observance error and six categories of non-observance errors. The relationship between workload and such errors was also clarified.

Conclusion

Our findings clarify the influence of workload on non-observance errors and may also help identify adjacent areas for specific improvements.

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