Prevalence and determinants of medication administration errors in clinical wards: A two-centre prospective observational study.

AIMS AND OBJECTIVES: To identify the prevalence and determinants of medication administration errors (MAEs). BACKGROUND: Insight into determinants of MAEs is necessary to identify interventions to prevent MAEs. DESIGN: A prospective observational study in two Dutch hospitals, a university and teaching hospital. METHODS: Data were collected by observation. The primary outcome was the proportion of administrations with one or more MAEs. Secondary outcomes were the type, severity and determinants of MAEs. Multivariable mixed-effects logistic regression analyses were used for determinant analysis. Reporting adheres to the STROBE guideline. RESULTS: MAEs occurred in 352 of 2576 medication administrations (13.7%). Of all MAEs (n = 380), the most prevalent types were omission (n = 87) and wrong medication handling (n = 75). Forty-five MAEs (11.8%) were potentially harmful. The pharmaceutical forms oral liquid (odds ratio [OR] 3.22, 95% confidence interval [CI] 1.43-7.25), infusion (OR 1.73, CI 1.02-2.94), injection (OR 3.52, CI 2.00-6.21), ointment (OR 10.78, CI 2.10-55.26), suppository/enema (OR 6.39, CI 1.13-36.03) and miscellaneous (OR 6.17, CI 1.90-20.04) were more prone to MAEs compared to oral solid. MAEs were more likely to occur when medication was administered between 10 a.m.-2 p.m. (OR 1.91, CI 1.06-3.46) and 6 p.m.-7 a.m. (OR 1.88, CI 1.00-3.52) compared to 7 a.m.-10 a.m. and when administered by staff with higher professional education compared to staff with secondary vocational education (OR 1.68, CI 1.03-2.74). MAEs were less likely to occur in the teaching hospital (OR 0.17, CI 0.08-0.33). Day of the week, patient-to-nurse ratio, interruptions and other nurse characteristics (degree, experience, employment type) were not associated with MAEs. CONCLUSIONS: This study identified a high MAE prevalence. Identified determinants suggest that focusing interventions on complex pharmaceutical forms and error-prone administration times may contribute to MAE reduction. RELEVANCE TO CLINICAL PRACTICE: The findings of this study can be used to develop targeted interventions to improve patient safety.

Imaging vessel wall biology to predict outcome in abdominal aortic aneurysm.

BACKGROUND: Abdominal aortic aneurysm (AAA) rupture risk is currently determined based on size and symptoms. This approach does not address the rupture risk associated with small aneurysms. Given the role of matrix metalloproteinases (MMPs) in AAA weakening and rupture, we investigated the potential of MMP-targeted imaging for detection of aneurysm biology and prediction of outcome in a mouse model of AAA with spontaneous rupture. METHODS AND RESULTS: Fifteen-week-old mice (n=66) were infused with angiotensin II for 4 weeks to induce AAA. Saline-infused mice (n=16) served as control. The surviving animals underwent in vivo MMP-targeted micro-single photon emission computed tomographic/computed tomographic imaging, using RP805, a technetium-99m-labeled MMP-specific tracer, followed by ex vivo planar imaging, morphometry, and gene expression analysis. RP805 uptake in suprarenal aorta on micro-single photon emission computed tomographic images was significantly higher in animals with AAA when compared with angiotensin II-infused animals without AAA or control animals. CD68 expression and MMP activity were increased in AAA, and significant correlations were noted between RP805 uptake and CD68 expression or MMP activity but not aortic diameter. A group of angiotensin II-infused animals (n=24) were imaged at 1 week and were followed up for additional 3 weeks. RP805 uptake in suprarenal aorta at 1 week was significantly higher in mice that later developed rupture or AAA. Furthermore, tracer uptake at 1 week correlated with aortic diameter at 4 weeks. CONCLUSIONS: MMP-targeted imaging reflects vessel wall inflammation and can predict future aortic expansion or rupture in murine AAA. If confirmed in humans, this may provide a new paradigm for AAA risk stratification.