Introduction: Data collection is among important steps that needs the use of right tools. Psychometric tools for measuring medication errors and strategies to reduce medication errors are very important. This study aimed at assessing validation of tools for measuring medication errors model variables that have been modeled on Reason human error.
Methods: In this methodological study after obtaining a planning permission for 6 instruments associated with medication error, Reasonchr('39')s model was used. This model includes care complexity, work dynamics, commitment, doctor/nurse relationship, medication error, and climate learning, and uses a seven-step learning process based on the translation of Wild et al. in 2005. In this study, firstly, the English version of the tools was translated to Persian and then back translated to English. The tools were then revised and summed to psychometrics, face validity and reliability using Cronbachchr('39')s alpha coefficient in 63 samples for homogeneity and stability in a sample of 12 nurses at Imam Hussein healthcare center in Tehran.
Results: The face validity of the views of nurses and nursing faculty members, and tools used in the proposed amendments were reviewed. The face validity of the views of nurses and nursing faculty members, and tools to review the proposed amendments were then applied. Also reliability using Cronbachchr('39')s alpha coefficient for internal consistency and correlation coefficient in test-retest for stability, complexity of care (r = 0.88, α = 0.61), work dynamics (r = 0.96, α = 0.81), work commitment (r = 0.96, α = 0.88), physician-nurse communication (r = 0.80, α = 0.80), the climate learning t (r = 0.98, α = 0.80) and medication errors (r = 0.83, α = 0.83) were obtained and instruments in terms of reliability and validity were confirmed.
Conclusions: The results showed that foreign tools of medication errors can be used in the Iranian society. Validity of the instrument using confirmatory factor analysis to examine the factor structure, is recommended.