Trend in data errors after the implementation of an electronic medical record system: A longitudinal study in an Australian regional Drug and Alcohol Service
© 2020 Elsevier B.V. Objectives: To investigate trends in data errors over the 40 months after the implementation of an electronic medical record (eMR) system in an Australian regional Drug and Alcohol (D&A) Service. Methods: One hundred and twenty three error reports and data on occasions of service were obtained from the D&A Service. Statistical analysis was conducted to describe types of errors, to compare distribution of error types among different documentation forms, D&A Service sites and job roles. Error rates were also analysed. Results: In the 40 months after the implementation, a total of 18,549 errors occurred. These errors were grouped into four types: mismatched data fields (54.5 %), duplicate medical record (1.8 %), date/time error (8.2 %) and blank field (35.4 %). The distribution of error types differed in the forms being completed, the sites and the job roles. Quarterly error rate increased from 28.8 errors per 100 occasions of service in Year 1 Quarter 1–40.6 in Quarter 3, then decreased to 18.1 in Quarter 4. It dropped to 6.6 in Year 2 Quarter 2 and continued to decrease to 2.5 in Year 4 Quarter 1. Monthly error rate was the highest at 44.6 in Month 8, fell to the lowest at 1.0 in Month 18 and remained at under 7.3 from Month 19 to Month 40. Conclusions: After the implementation of the eMR system, the error rate increased in the first three quarters before decreasing. It reached stability about one and a half years after implementation. There were significant differences in the error distribution among the documentation forms, sites and job roles. The findings of this study could be used by eMR trainers to tailor training sessions for specific sites and job roles. These findings might also be useful for managers of other D&A Services to plan for the implementation of new electronic documentation systems.