Errores de prescripción en recetas médicas atendidas en el Centro de Salud Mental Comunitario Allin Kawsay, Puno abril - junio 2023.
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Universidad Privada de Huancayo Franklin Roosevelt
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La investigación tuvo como objetivo identificar los errores de prescripción en las recetas médicas atendidas en el Centro de Salud Mental Comunitario ALLIN KAWSAY. El tipo de investigación fue aplicada y de nivel descriptivo. Es un estudio de diseño no experimental, retrospectivo y transversal, La población estuvo conformada por todas las recetas atendidas. los principales resultados identificamos, el porcentaje promedio de errores equivalentes al 1.6%, 0.4%, 0.6% y 7.7% para las dimensiones de datos del paciente, datos del prescriptor, datos del medicamento y legibilidad, respectivamente. Se concluye que en el 2.6% de la totalidad de las recetas médicas atendidas entre los meses de abril a mayo del 2023 presentaron por lo menos un tipo de error de prescripción.
The objective of the research was to identify prescription errors in prescriptions filled at the ALLIN KAWSAY Community Mental Health Center. The type of research was applied and descriptive. It is a non-experimental, retrospective and cross-sectional design study. The population consisted of all the prescriptions filled. The main results identified the average percentage of errors equivalent to 1.6%, 0.4%, 0.6% and 7.7% for the dimensions of patient data, prescriber data, medication data and legibility, respectively. It is concluded that 2.6% of all prescriptions filled between April and May 2023 presented at least one type of prescription error.
The objective of the research was to identify prescription errors in prescriptions filled at the ALLIN KAWSAY Community Mental Health Center. The type of research was applied and descriptive. It is a non-experimental, retrospective and cross-sectional design study. The population consisted of all the prescriptions filled. The main results identified the average percentage of errors equivalent to 1.6%, 0.4%, 0.6% and 7.7% for the dimensions of patient data, prescriber data, medication data and legibility, respectively. It is concluded that 2.6% of all prescriptions filled between April and May 2023 presented at least one type of prescription error.
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