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Article type: Research Article
Authors: Jin, Haizhea | Yao, Junhanb | Xiao, Zhibina | Qu, Qingxinga; * | Fu, Quanweic
Affiliations: [a] Department of Industrial Engineering, School of Business Administration, Northeastern University, Shenyang, China | [b] College of Management and Economics, Tianjin University, Tianjin, China | [c] Dongguan Kanghua Hospital, Dongguan, China
Correspondence: [*] Address for correspondence: Qingxing Qu, Postdoctoral Fellow, Department of Industrial Engineering, School of Business Administration, Northeastern University, No. 195, Chuangxin Road, Hunnan District, Shenyang 110167, China. E-mail: [email protected].
Abstract: BACKGROUND:Medication administration errors by nurses form a high proportion of medical errors in medical institutions. Studies have shown that such errors are closely linked to nursing workload. OBJECTIVE:To quantitatively explore the effects of different types of nursing workloads on different medication administration errors. METHOD:Three medical institutions were selected as the objects of error data collection based on the following criteria: the medical institution experience in error data collection, the complete range of medical departments, and the institution size. Error cases were self-reported from all nurses in all medical departments. The relationship between the error types and nursing workload types were quantitatively examined using partial least squares and structural equation modeling. RESULTS:The study recorded 290 medication administration errors, and extracted four error types and nine nursing workload types. The workload type for each error type was also identified and the path coefficient was found to be between 0.087 to 0.416. CONCLUSION:This study confirmed the effect of workload on medication administration errors and determined a theoretical mechanism for this effect. Research results will provide the evidence for nursing managers to reduce workload and ensure quality in the nursing administration process.
Keywords: Medication administration errors, nursing workload, error types, quantitative study
DOI: 10.3233/WOR-211392
Journal: Work, vol. 74, no. 1, pp. 247-254, 2023
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