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1.
Int J Health Care Qual Assur ; 24(3): 238-48, 2011.
Article in English | MEDLINE | ID: mdl-21938969

ABSTRACT

PURPOSE: Medication errors (MEs) are important in terms of their magnitude and severity, and there are numerous systems in place to reduce their occurrence. However, the ideal system has not yet been identified. The authors' institution uses three different medication prescription-dispensation systems which operate simultaneously. ME rates were compared, overall and by phase (prescription, transcription and administration) and their overall and specific clinical impact. DESIGN/METHODOLOGY/APPROACH: The administration of medicinal products was observed directly and compared with medical and nursing prescriptions. Errors and adverse events were classified by a consensus of experts. FINDINGS: In the traditional system the error prevalence rate was 13.59 per cent, (99 per cent CI, 12.15-14.61 per cent), in the single dose system it was 6.43 per cent (99 per cent CI, 5.53-7.32) and in the electronic prescription system it was 8.86 per cent (99 per cent CI, 7.33-10.17). The highest error rates in all phases were found in the traditional system. The phase affected by most errors in all three models was transcription, and the least affected was administration, except for the single dose system, in which prescription was the worst. The effects of errors in the administration phase are greater, although less so than with the automated system. RESEARCH LIMITATIONS/IMPLICATIONS: The dispensation phase was not analyzed. PRACTICAL IMPLICATIONS: A study of errors will enable us to reduce their occurrence if we know the most frequent types and in which phase they are produced, we will be able to prioritise the areas in which to work and select the necessary preventive measures. ORIGINALITY/VALUE: It is possible that automated medication dispensation systems reduce error rates and the severity of their effects.


Subject(s)
Medication Errors/classification , Medication Errors/prevention & control , Medication Systems, Hospital/organization & administration , Pharmacy Service, Hospital/organization & administration , Aged , Body Weight , Electronic Prescribing , Humans , Medical Order Entry Systems/organization & administration , Middle Aged , Polypharmacy
2.
Int J Health Care Qual Assur ; 23(3): 328-38, 2010.
Article in English | MEDLINE | ID: mdl-20535904

ABSTRACT

PURPOSE: Healthcare risk epidemiology identifies medication error as the commonest cause of adverse effects on patients. Medication error can occur at any phase of the complex medication process so prevalence rates need to be estimated at each drug treatment phase: prescription, transcription and administration along with their clinical repercussions. This paper aims to investigate this issue. DESIGN/METHODOLOGY/APPROACH: Medication errors were recorded on an ad hoc sheet and staff were observed handling medications. Recorded errors were later classified and their clinical repercussions determined by experts. FINDINGS: In total 757 inpatients and 5466 drug prescriptions were studied. The prescription error rate was 4.79 percent (95 percent CI 4.21-5.36). The most frequent error in this phase was failing to observe international prescribing standards. The highest error rate was found in transcription (14.61 percent, 95 percent CI 13.67-15.54). Almost 1900 dose administrations were observed. There was a 9.32 percent error rate (95 percent CI 7.98-10.67). The commonest error in this phase was omission. Most were transcription errors, which were detected before harm wasdone. RESEARCH LIMITATIONS/IMPLICATIONS: The dispensation phase is absent. PRACTICAL IMPLICATIONS: Errors can be reduced if they are understood. Education and training based on the study's findings can reduce medication errors. ORIGINALITY/VALUE: The paper highlights ways to reduce errors in the medication process.


Subject(s)
Hospital Administration/statistics & numerical data , Medication Errors/statistics & numerical data , Medication Systems, Hospital/organization & administration , Medication Systems, Hospital/statistics & numerical data , Adult , Aged , Aged, 80 and over , Child , Child, Preschool , Humans , Infant , Medication Errors/classification , Middle Aged , Nursing Staff, Hospital/organization & administration
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