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Einstein (São Paulo)
Article . 2009
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Inpatients’ medical prescription errors

Authors: Aline Melo Santos Silva;

Inpatients’ medical prescription errors

Abstract

Objective: To identify and quantify the most frequent prescription errors in inpatients’ medical prescriptions. Methods: A survey of prescription errors was performed in the inpatients’ medical prescriptions, from July 2008 to May 2009 for eight hours a day. Rresults: At total of 3,931 prescriptions was analyzed and 362 (9.2%) prescription errors were found, which involved the healthcare team as a whole. Among the 16 types of errors detected in prescription, the most frequent occurrences were lack of information, such as dose (66 cases, 18.2%) and administration route (26 cases, 7.2%); 45 cases (12.4%) of wrong transcriptions to the information system; 30 cases (8.3%) of duplicate drugs; doses higher than recommended (24 events, 6.6%) and 29 cases (8.0%) of prescriptions with indication but not specifying allergy. Cconclusion: Medication errors are a reality at hospitals. All healthcare professionals are responsible for the identification and prevention of these errors, each one in his/her own area. The pharmacist is an essential professional in the drug therapy process. All hospital organizations need a pharmacist team responsible for medical prescription analyses before preparation, dispensation and administration of drugs to inpatients. This study showed that the pharmacist improves the inpatient’s safety and success of prescribed therapy.

Keywords

Inpatients, Prescriptions, Medication errors/prevention & control, R, drug, Medicine

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
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