BACKGROUND: Medical-error analyses have been conducted to determine the root cause of adverse events and near misses. More precise determination of the cause-and-effect relationship likely will require a prospective design path analysis including both direct and indirect effects. METHODS: The authors performed a 6-month prospective cohort study using structural-equation modelling (SEM). Of the 879 nurses approached, 789 (89.8%) were included in the final analysis. Potential predictors provided for analysis included age, years of nursing experience, mean frequency of night shifts per month, nursing-specific job stressors, degree of depression, frequency of feeling unskilled, feeling time pressure, feeling a lack of communication between self and other hospital staff members, frequency of suffering from sleep disturbance and frequency of feeling a decrease in attention. The authors regarded a latent variable composed of frequencies for near misses and adverse events as an outcome. RESULTS AND CONCLUSION: The SEM model constructed in this study suggested that potential root causes (exogenous variables directly or indirectly connected to the outcome which are not affected by other variables) were years of nursing experience, feeling unskilled, job stressors and sleep disturbance, with estimated standardised total (direct and indirect) effects of -0.22, 0.21, 0.008 and 0.005, respectively. A prospective design path analysis using the SEM model for both direct and indirect effects enabled a statistical exploration of root causes and estimation of their impact on the outcome. Our findings suggested such an analysis to be useful in devising countermeasures against medical errors.
BACKGROUND: Medical-error analyses have been conducted to determine the root cause of adverse events and near misses. More precise determination of the cause-and-effect relationship likely will require a prospective design path analysis including both direct and indirect effects. METHODS: The authors performed a 6-month prospective cohort study using structural-equation modelling (SEM). Of the 879 nurses approached, 789 (89.8%) were included in the final analysis. Potential predictors provided for analysis included age, years of nursing experience, mean frequency of night shifts per month, nursing-specific job stressors, degree of depression, frequency of feeling unskilled, feeling time pressure, feeling a lack of communication between self and other hospital staff members, frequency of suffering from sleep disturbance and frequency of feeling a decrease in attention. The authors regarded a latent variable composed of frequencies for near misses and adverse events as an outcome. RESULTS AND CONCLUSION: The SEM model constructed in this study suggested that potential root causes (exogenous variables directly or indirectly connected to the outcome which are not affected by other variables) were years of nursing experience, feeling unskilled, job stressors and sleep disturbance, with estimated standardised total (direct and indirect) effects of -0.22, 0.21, 0.008 and 0.005, respectively. A prospective design path analysis using the SEM model for both direct and indirect effects enabled a statistical exploration of root causes and estimation of their impact on the outcome. Our findings suggested such an analysis to be useful in devising countermeasures against medical errors.