Oncology nurses' perceptions about involving patients in the prevention of chemotherapy administration errors

To explore oncology nurses' perceptions and experiences with patient involvement in chemotherapy error prevention.

Eliminating Adhesion Errors in Nanoindentation of Compliant Polymers and Hydrogels

Nanoindentation is a valuable tool for characterization of biomaterials due to its ability to measure local properties in heterogeneous, small or irregularly shaped samples. However, applying nanoindentation to compliant, hydrated biomaterials leads to many challenges including adhesion between the nanoindenter tip and the sample. Although adhesion leads to overestimation of the modulus of compliant samples when analyzing nanoindentation data using traditional analysis techniques, most studies of biomaterials have ignored its effects. This paper demonstrates two methods for managing adhesion in nanoindentation analysis, the nano-JKR force curve method and the surfactant method, through application to two biomedically-relevant compliant materials, poly(dimethyl siloxane) (PDMS) elastomers and poly(ethylene glycol) (PEG) hydrogels. The nano-JKR force curve method accounts for adhesion during data analysis using equations based on the Johnson-Kendall-Roberts (JKR) adhesion model, while the surfactant method eliminates adhesion during data collection, allowing data analysis using traditional techniques. In this study, indents performed in air or water resulted in adhesion between the tip and the sample, while testing the same materials submerged in Optifree Express() contact lens solution eliminated tip-sample adhesion in most samples. Modulus values from the two methods were within 7% of each other, despite different hydration conditions and evidence of adhesion. Using surfactant also did not significantly alter the properties of the tested material, allowed accurate modulus measurements using commercial software, and facilitated nanoindentation testing in fluids. This technique shows promise for more accurate and faster determination of modulus values from nanoindentation of compliant, hydrated biological samples. Copyright 2013 Elsevier Ltd. All rights reserved.

Cerebrovascular accidents complicating transcatheter aortic valve implantation: frequency, timing and impact on outcomes

Cerebrovascular accidents (CVA) are considered among the most serious adverse events after transcatheter aortic valve implantation (TAVI). The objective of the present study was to evaluate the frequency and timing of CVA after TAVI and to investigate the impact on clinical outcomes within 30 days of the procedure.

Impact of random and systematic recall errors and selection bias in case--control studies on mobile phone use and brain tumors in adolescents (CEFALO study)

Whether the use of mobile phones is a risk factor for brain tumors in adolescents is currently being studied. Case--control studies investigating this possible relationship are prone to recall error and selection bias. We assessed the potential impact of random and systematic recall error and selection bias on odds ratios (ORs) by performing simulations based on real data from an ongoing case--control study of mobile phones and brain tumor risk in children and adolescents (CEFALO study). Simulations were conducted for two mobile phone exposure categories: regular and heavy use. Our choice of levels of recall error was guided by a validation study that compared objective network operator data with the self-reported amount of mobile phone use in CEFALO. In our validation study, cases overestimated their number of calls by 9% on average and controls by 34%. Cases also overestimated their duration of calls by 52% on average and controls by 163%. The participation rates in CEFALO were 83% for cases and 71% for controls. In a variety of scenarios, the combined impact of recall error and selection bias on the estimated ORs was complex. These simulations are useful for the interpretation of previous case-control studies on brain tumor and mobile phone use in adults as well as for the interpretation of future studies on adolescents.

Frequency of and predictors for patient-reported medical and medication errors in Switzerland

OBJECTIVES: To analyse the frequency of and identify risk factors for patient-reported medical errors in Switzerland. The joint effect of risk factors on error-reporting probability was modelled for hypothetical patients. METHODS: A representative population sample of Swiss citizens (n = 1306) was surveyed as part of the Commonwealth Fund’s 2010 lnternational Survey of the General Public’s Views of their Health Care System’s Performance in Eleven Countries. Data on personal background, utilisation of health care, coordination of care problems and reported errors were assessed. Logistic regression analysis was conducted to identify risk factors for patients’ reports of medical mistakes and medication errors. RESULTS: 11.4% of participants reported at least one error in their care in the previous two years (8% medical errors, 5.3% medication errors). Poor coordination of care experiences was frequent. 7.8% experienced that test results or medical records were not available, 17.2% received conflicting information from care providers and 11.5% reported that tests were ordered although they had been done before. Age (OR = 0.98, p = 0.014), poor health (OR = 2.95, p = 0.007), utilisation of emergency care (OR = 2.45, p = 0.003), inpatient-stay (OR = 2.31, p = 0.010) and poor care coordination (OR = 5.43, p <0.001) are important predictors for reporting error. For high utilisers of care that unify multiple risk factors the probability that errors are reported rises up to p = 0.8. CONCLUSIONS: Patient safety remains a major challenge for the Swiss health care system. Despite the health related and economic burden associated with it, the widespread experience of medical error in some subpopulations also has the potential to erode trust in the health care system as a whole.

Impact of measurement errors on the determination of the linear modulus of human meniscal attachments

For the development of meniscal substitutes and related finite element models it is necessary to know the mechanical properties of the meniscus and its attachments. Measurement errors can falsify the determination of material properties. Therefore the impact of metrological and geometrical measurement errors on the determination of the linear modulus of human meniscal attachments was investigated. After total differentiation the error of the force (+0.10%), attachment deformation (−0.16%), and fibre length (+0.11%) measurements almost annulled each other. The error of the cross-sectional area determination ranged from 0.00%, gathered from histological slides, up to 14.22%, obtained from digital calliper measurements. Hence, total measurement error ranged from +0.05% to −14.17%, predominantly affected by the cross-sectional area determination error. Further investigations revealed that the entire cross-section was significantly larger compared to the load-carrying collagen fibre area. This overestimation of the cross-section area led to an underestimation of the linear modulus of up to −36.7%. Additionally, the cross-sections of the collagen-fibre area of the attachments significantly varied up to +90% along their longitudinal axis. The resultant ratio between the collagen fibre area and the histologically determined cross-sectional area ranged between 0.61 for the posterolateral and 0.69 for the posteromedial ligament. The linear modulus of human meniscal attachments can be significantly underestimated due to the use of different methods and locations of cross-sectional area determination. Hence, it is suggested to assess the load carrying collagen fibre area histologically, or, alternatively, to use the correction factors proposed in this study.