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Medical Error Prevalence, Nursing Power, and Structural Empowerment: A Serial Mediation Analysis

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Publisher Wiley
Specialty Biology
Date 2024 May 3
PMID 38699216
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Abstract

Aim: To investigate how structural empowerment and power may contribute to and predict the reduction of medical errors.

Background: Medical errors threaten patient well-being, leading to adverse outcomes. Improving work conditions holds promise for reducing medical errors among nurses.

Methods: A multisite correlational cross-sectional design was utilized. Data were completed by 375 nurses from four hospitals in Jordan. Data collection occurred between September and November 2023 using sociodemographic, structural empowerment, and medical error questionnaires. The study employed descriptive statistics, Pearson correlation, and serial mediation analysis. Informed consent was obtained from each participant.

Results: Pearson correlation revealed significant negative correlations between medical error and structural empowerment, formal power, and informal power. The conceptual framework was significant and predicted 16% of the variance in medical errors. The mediation analysis confirmed that formal power and informal power mediate the relationship between structural empowerment and medical error. . This study sheds light on the intricate connection of structural empowerment, formal and informal power, and their collective impact on reducing medical errors. Understanding and addressing these dynamics allows nurses and administrators to achieve a culture of patient safety. Reduction of medical errors is paramount to a safe healthcare environment that prioritizes patient outcomes. Strategies should be fostered to enhance structural empowerment, refine formal power structures, and leverage the positive aspects of informal networks.

Citing Articles

Innovative behavior and structural empowerment among the Chinese clinical nurses: the mediating role of decent work perception.

Wang Z, Yang L, Zhu Y, Tang X, Wang T, Chen L BMC Nurs. 2024; 23(1):881.

PMID: 39627823 PMC: 11613594. DOI: 10.1186/s12912-024-02554-z.

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