[Errors in hospital prescriptions of high-alert medications].
OBJECTIVE
Medication errors are currently a worldwide public health issue and it is one of the most serious prescription errors. The objective of the study was to evaluate the practice of prescribing high-alert medications and its association with the prevalence of medication errors in hospital settings.


METHODS
A retrospective cross-sectional study was conducted including 4,026 prescription order forms of high-alert medications. There were evaluated all prescriptions received at the pharmacy of a reference hospital in the state of Minas Gerais, southeastern Brazil, over a 30-day period in 2001. Prescription were checked for legibility, patient name, type of prescription, date, handwriting or writing, prescriber identification, drug prescribed, and use of abbreviations. Prescription errors were classified as writing or decision errors and how the type of prescription affected the occurrence of errors was assessed.


RESULTS
Most prescriptions were handwritten (45.7%). In 47.0% of handwritten, mixed and pre-typed prescriptions had patient name errors; the prescriber name was difficult to identify in 33.7%; 19.3% of them were hardly legible or illegible. Of a total of 7,148 high-alert drugs prescribed, 3,177 errors were found, and the most frequent one was missing information (86.5%). Errors occurred mostly in prescriptions of heparin, phentanyl, and midazolam. Intensive care and neurology units had the highest number of errors per prescription. Non-standard abbreviations were frequent and widespread. Overall it was estimated 3.3 errors per prescription order form. Pre-typed prescriptions were less likely to have errors compared to mixed or handwritten prescriptions.


CONCLUSIONS
The study results show there is a need for standardizing the prescription process and eliminating handwritten prescriptions. The use of pre-typed or edited prescriptions may reduce errors associated to high-alert medications.
Rosa
Mário Borges
MB
Fundação Hospitalar do Estado de Minas Gerais, Belo Horizonte, MG, Brasil. mariobr_ca@yahoo.com
Perini
Edson
E
Anacleto
Tânia Azevedo
TA
Neiva
Hessem Miranda
HM
Bogutchi
Tânia
T
D011307:Drug Prescriptions / Q000592:standards* / Q000706:statistics & numerical data; D004812:Epidemiologic Methods; D006236:Handwriting; D006801:Humans; D008508:Medication Errors / Q000145:classification / Q000706:statistics & numerical data*; D008510:Medication Systems, Hospital; D010818:Practice Patterns, Physicians' / Q000706:statistics & numerical data*; D055553:Prescription Drugs / Q000008:administration & dosage / Q000145:classification*
D055553:Prescription Drugs