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Evaluation of medication errors in electronic medical prescriptions and proposal for correction

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Worldwide, the annual cost associated with medication errors is estimated at US$ 42 billion or almost 1% of the total global health expenditure. In Brazil, analysis and measures to minimize these errors has not been well studied. Thus, the present study identified the errors in electronic medical prescriptions and proposed strategies to minimize such errors.


A total of 1980 medical prescriptions were analyzed in a hospital, with 196 beds and 11 sectors located in Votuporanga, SP, Brazil. The errors were listed: Via, Frequency, Time, Duplication, Absence, Diluents, Dose, Medication, and Infusion. The statistical analysis was applied, with a significance level at 5%.


The 2621 found errors correspond to 49.49% of the prescriptions analyzed; 23.68% contained only one prescription error, 11.06% had two errors, and 14.75% included three or more errors. After the evaluation stage, some errors were corrected, and some improvements were suggested. The correction of dose error decrease of 68% and 30% occurred in the consumption of two drugs. For the correction of diluents and time errors, an assertiveness was generated in all the prescriptions analyzed.


A cycle of continuous improvement is proposed for the indicators of medical prescription errors based on four main principles of planning, performing, analyzing, and correcting. The starting point for this process should always be the diagnosis of the main prescription errors. This cycle should be applied annually to reduce prescription errors, thus, offering better treatment to patients and optimizing hospital resources.

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The authors are thankful to CNPq and Capes/Brasil for their support.


S.B.M. Riva is grateful to UNIFEV - CENTRO UNIVERSITÁRIO DE VOTUPORANGA for their financial support.

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Correspondence to Laurita dos Santos.

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Riva, S.B.M., da Costa, M.M. & dos Santos, L. Evaluation of medication errors in electronic medical prescriptions and proposal for correction. Res. Biomed. Eng. 36, 59–65 (2020). https://doi.org/10.1007/s42600-020-00040-4

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  • Medication errors
  • Electronic health record
  • Medical prescription