Learning curves, taking instructions, and patient safety:using a theoretical domains framework in an interview study to investigate prescribing errors among trainee doctors

ABSTRACT:

DiveRsity: An R package for the estimation and exploration of population genetics parameters and their associated errors

Summary: We present a new R package, diveRsity, for the calculation of various diversity statistics, including common diversity partitioning statistics (?, G) and population differentiation statistics (D, GST ', ? test for population heterogeneity), among others. The package calculates these estimators along with their respective bootstrapped confidence intervals for loci, sample population pairwise and global levels. Various plotting tools are also provided for a visual evaluation of estimated values, allowing users to critically assess the validity and significance of statistical tests from a biological perspective. diveRsity has a set of unique features, which facilitate the use of an informed framework for assessing the validity of the use of traditional F-statistics for the inference of demography, with reference to specific marker types, particularly focusing on highly polymorphic microsatellite loci. However, the package can be readily used for other co-dominant marker types (e.g. allozymes, SNPs). Detailed examples of usage and descriptions of package capabilities are provided. The examples demonstrate useful strategies for the exploration of data and interpretation of results generated by diveRsity. Additional online resources for the package are also described, including a GUI web app version intended for those with more limited experience using R for statistical analysis. © 2013 British Ecological Society.

Monitoring daily MLC positional errors using trajectory log files and EPID measurements for IMRT and VMAT deliveries

This work investigated the differences between multileaf collimator (MLC) positioning accuracy determined using either log files or electronic portal imaging devices (EPID) and then assessed the possibility of reducing patient specific quality control (QC) via phantom-less methodologies. In-house software was developed, and validated, to track MLC positional accuracy with the rotational and static gantry picket fence tests using an integrated electronic portal image. This software was used to monitor MLC daily performance over a 1 year period for two Varian TrueBeam linear accelerators, with the results directly compared with MLC positions determined using leaf trajectory log files. This software was validated by introducing known shifts and collimator errors. Skewness of the MLCs was found to be 0.03 ± 0.06° (mean ±1 standard deviation (SD)) and was dependent on whether the collimator was rotated manually or automatically. Trajectory log files, analysed using in-house software, showed average MLC positioning errors with a magnitude of 0.004 ± 0.003 mm (rotational) and 0.004 ± 0.011 mm (static) across two TrueBeam units over 1 year (mean ±1 SD). These ranges, as indicated by the SD, were lower than the related average MLC positioning errors of 0.000 ± 0.025 mm (rotational) and 0.000 ± 0.039 mm (static) that were obtained using the in-house EPID based software. The range of EPID measured MLC positional errors was larger due to the inherent uncertainties of the procedure. Over the duration of the study, multiple MLC positional errors were detected using the EPID based software but these same errors were not detected using the trajectory log files. This work shows the importance of increasing linac specific QC when phantom-less methodologies, such as the use of log files, are used to reduce patient specific QC. Tolerances of 0.25 mm have been created for the MLC positional errors using the EPID-based automated picket fence test. The software allows diagnosis of any specific leaf that needs repair and gives an indication as to the course of action that is required.

Online Thévenin Equivalent Determination Considering System Side Changes and Measurement Errors

This paper presents a new method for online determination of the Thèvenin equivalent parameters of a power system at a given node using the local PMU measurements at that node. The method takes into account the measurement errors and the changes in the system side. An analysis of the effects of changes in system side is carried out on a simple two-bus system to gain an insight of the effect of system side changes on the estimated Thévenin equivalent parameters. The proposed method uses voltage and current magnitudes as well as active and reactive powers; thus avoiding the effect of phase angle drift of the PMU and the need to synchronize measurements at different instances to the same reference. Applying the method to the IEEE 30-bus test system has shown its ability to correctly determine the Thévenin equivalent even in the presence of measurement errors and/or system side changes.

Multiuser Scheduling for Cognitive MIMO with Channel Estimation Errors and Feedback Delay

A multiuser scheduling multiple-input multiple-output (MIMO) cognitive radio network (CRN) with space-time block coding (STBC) is considered in this paper, where one secondary base station (BS) communicates with one secondary user (SU) selected from K candidates. The joint impact of imperfect channel state information (CSI) in BS → SUs and BS → PU due to channel estimation errors and feedback delay on the outage performance is firstly investigated. We obtain the exact outage probability expressions for the considered network under the peak interference power IP at PU and maximum transmit power Pm at BS which cover perfect/imperfect CSI scenarios in BS → SUs and BS → PU. In addition, asymptotic expressions of outage probability in high SNR region are also derived from which we obtain several important insights into the system design. For example, only with perfect CSIs in BS → SUs, i.e., without channel estimation errors and feedback delay, the multiuser diversity can be exploited. Finally, simulation results confirm the correctness of our analysis.

Prevalence, Nature, Severity and Risk Factors for Prescribing Errors in Hospital Inpatients: Prospective Study in 20 UK Hospitals

Introduction: It has been suggested that doctors in their first year of post-graduate training make a disproportionate number of prescribing errors.

Obkective: This study aimed to compare the prevalence of prescribing errors made by first-year post-graduate doctors with that of errors by senior doctors and non-medical prescribers and to investigate the predictors of potentially serious prescribing errors.

Methods: Pharmacists in 20 hospitals over 7 prospectively selected days collected data on the number of medication orders checked, the grade of prescriber and details of any prescribing errors. Logistic regression models (adjusted for clustering by hospital) identified factors predicting the likelihood of prescribing erroneously and the severity of prescribing errors.

Results: Pharmacists reviewed 26,019 patients and 124,260 medication orders; 11,235 prescribing errors were detected in 10,986 orders. The mean error rate was 8.8 % (95 % confidence interval [CI] 8.6-9.1) errors per 100 medication orders. Rates of errors for all doctors in training were significantly higher than rates for medical consultants. Doctors who were 1 year (odds ratio [OR] 2.13; 95 % CI 1.80-2.52) or 2 years in training (OR 2.23; 95 % CI 1.89-2.65) were more than twice as likely to prescribe erroneously. Prescribing errors were 70 % (OR 1.70; 95 % CI 1.61-1.80) more likely to occur at the time of hospital admission than when medication orders were issued during the hospital stay. No significant differences in severity of error were observed between grades of prescriber. Potentially serious errors were more likely to be associated with prescriptions for parenteral administration, especially for cardiovascular or endocrine disorders.

Conclusions: The problem of prescribing errors in hospitals is substantial and not solely a problem of the most junior medical prescribers, particularly for those errors most likely to cause significant patient harm. Interventions are needed to target these high-risk errors by all grades of staff and hence improve patient safety.