Predicting medication omission: a foundation for evidence-based strategies to improve patient safety.

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Latimer, Sharon
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Brisbane, Australia


Introduction: The aim of this study was to identify the incidence and predictors (in terms of patient, system and drug related factors) of non-therapeutic medication omission amongst acutely ill medical and surgical adult patients. Background: The inconsistent definition of non-therapeutic medication omission and a poor understanding of their associated factors hamper efforts to improve medication administration practices. Data/Methods: A chart audit of 288 acutely ill adult medical and surgical patients admitted to four wards in an Australian hospital. All patients admitted to these wards from December 2008 to November 2009, and who had at least one regularly prescribed medication, were eligible for inclusion in the sample. The sample was stratified according to gender, season and ward. A medication chart audit identified medication omissions, and collected data on gender, age, length of stay, co-morbidities, medication history, and clinical pharmacy review. Results: In total, 220 of the 288 patients (74.6%) experienced one or more medication omissions. Of the 15,020 medication administration episodes, there were 1,687 omissions, resulting in an omission rate per medication administration opportunity of 11.2%. Analgesics and aperients were most frequently omitted, with failure to sign the medication record and patient refusal, the main reasons identified. Gender (females) (p < 0.001) and total medication prescriptions (p < 0.001) were statistically significant predictors of omissions. Conclusions: The high incidence of medication omissions suggests the need for the inclusion of omissions as a reportable incident. Increasing medication reconciliation through the implementation of the Medication Management Plan may also reduce the opportunity for error. Contact Details Name: Sharon Latimer Division: School of Nursing and Midwifery Organisation: Griffith University P: 07 5552 9729 F: 07 5552 8526 M: 0416 104 308 E:

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Predicting medication omission: a foundation for evidence-based strategies to improve patient safety.

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