Systematic observation in healthcare: Utility and limitations of a threat and error management-based safety audit

Improving teamwork has become a major safety goal for healthcare organizations. Audit tools currently available are useful, but they remain inadequate because they are reactive and fail to provide context for “the interaction between people and the operational context (i.e., organizational, regulatory and environmental factors) within which people discharge their operational duties” (Maurino, 2005). Accurate and relevant information about real-world team behavior is theorized to confer the ability to address, through process design &/or training, significant issues which can then be re-assessed through repeat observations. In the mid-1990s, the Federal Aviation Administration (FAA) funded collaboration between the University of Texas and Continental Airlines to directly observe in-flight behaviors associated with safety and risk. This methodology, now known as the Line Operation Safety Audit (LOSA), was instrumental in developing the Threat and Error Management (TEM) model of cockpit work performance. In 2006, the FAA made TEM-based LOSA a “voluntary safety recommendation,” and all major US commercial air carriers engage in this on a regular basis as a component of their safety management systems (FAA, 2006). This thesis describes the adaptation of LOSA to a Threat and Error Management-based Clinical Operation Safety Audit (COSA), and reports a series of 30 observations of trauma team activations in the Emergency Department at an American College of Surgeons accredited level 1 trauma center in the United States of America. Results of these observations showed discrepancies between work as designed and as executed, as well as other behaviors, associated with increased risk to patients. Analysis of data revealed important areas for targeted improvement based on risk created by the healthcare system during normal clinical operations. Systematic observation following the COSA protocol can become a vital and essential new tool to assist in improving patient safety in healthcare. The bulk of this thesis considers the criticality of context in work analysis throughout the discussion section. Though concepts of threats and undesired states were easily adaptable to healthcare, error was found to be too narrow a concept. I therefore propose discarding error for a more open and inclusive interpretation of performance: Task Adaptation. We therefore propose to widen our scope and continue to develop Threat Management and Task Adaptation-based COSA throughout the hospital to enhance system performance and improve patient safety

Size effects in ion-neutral complex-mediated alkane eliminations from ionized aliphatic ethers

AbstractThe effects of the size of the ionic and neutral partners on ion-neutral complex-mediated alkane eliminations from ionized aliphatic ethers were determined by obtaining metastable decomposition spectra and photoionization ionization efficiency curves. Increasing the size of the ionic partner decreases the competitiveness of alkane elimination with alkyl loss. This is attributed to decreasing attraction between the partners with increasing distance between the neutral partner and the center of charge in the associated ion. Increasing the size of the neutral partner lowers the threshold for alkane elimination relative to that for simple dissociation when the first threshold is above ΔHf(products). This is attributed to increasing attraction between the partners with increasing polarizability of the radical in the complex. Adding a CH2 to the radical in a complex seems to increase the attraction between the partners by about 24 kJ mol−1

Australian climate warming: observed change from 1850 and global temperature targets

Mean annual temperature is often used as a benchmark for monitoring climate change and as an indicator of its potential impacts. The Paris Agreement of 2015 aims to keep the global average temperature well below 2°C above pre-industrial levels, with a preferred limit of 1.5°C. Therefore, there is interest in understanding and examining regional temperature change using this framework of ‘global warming levels’, as well as through emissions pathways and time horizons. To apply the global warming level framework regionally, we need to quantify regional warming from the late 19th century to today, and to future periods where the warming levels are reached. Here we supplement reliable observations from 1910 with early historical datasets currently available back to 1860 and the latest set of global climate model simulations from CMIP5/CMIP6 to examine the past and future warming of Australia from the 1850–1900 baseline commonly used as a proxy for pre-industrial conditions. We find that Australia warmed by ~1.6°C between 1850–1900 and 2011–2020 (with uncertainty unlikely to substantially exceed ±0.3°C). This warming is a ratio of ~1.4 times the ~1.1°C global warming over that time, and in line with observed global land average warming. Projections for global warming levels are also quantified and suggest future warming of slightly less than the observed ratio to date, at ~1.0–1.3 for all future global warming levels. We also find that to reliably examine regional warming under the emissions pathway framework using the latest climate models from CMIP6, appropriate weights to the ensemble members are required. Once these weights are applied, results are similar to CMIP5

Comparison of various climate change projections of eastern Australian rainfall

The Australian eastern seaboard is a distinct climate entity from the interior of the continent, with different climatic influences on each side of the Great Dividing Range. Therefore, it is plausible that downscaling of global climate models could reveal meaningful regional detail, or ‘added value’, in the climate change signal of mean rainfall change in eastern Australia un-der future scenarios. However, because downscaling is typically done using a limited set of global climate models and downscaling methods, the results from a downscaling study may not represent the range of uncertainty in plausible projected change for a region suggested by the ensemble of host global climate models. A complete and unbiased representation of the plausible changes in the climate is essential in producing climate projections useful for future planning. As part of this aim it is important to quantify any differences in the change signal between global climate models and downscaling, and understand the cause of these differ-ences in terms of plausible added regional detail in the climate change signal, the impact of sub-sampling global climate models and the effect of the downscaling models themselves. Here we examine rainfall projections in eastern Australia under a high emissions scenario by late in the century from ensembles of global climate models, two dynamical downscaling models and one statistical downscaling model. We find no cases where all three downscaling methods show the same clear regional spatial detail in the change signal that is distinct from the host models. However, some downscaled projections suggest that the eastern seaboard could see little change in spring rainfall, in contrast to the substantial rainfall decrease inland. The change signal in the downscaled outputs is broadly similar at the large scale in the various model outputs, with a few notable exceptions. For example, the model median from dynamical downscaling projects a rainfall increase over the entirety of eastern Australia in autumn that is greater than the global models. Also, there are some instances where a downscaling method produces changes outside the range of host models over eastern Australia as a whole, thus ex-panding the projected range of uncertainty. Results are particularly uncertain for summer, where no two downscaling studies clearly agree. There are also some confounding factors from the model configuration used in downscaling, where the particular zones used for statis-tical models and the model components used in dynamical models have an influence on results and produce additional uncertainty

Allele-Specific Up-Regulation of FGFR2 Increases Susceptibility to Breast Cancer

The recent whole-genome scan for breast cancer has revealed the FGFR2 (fibroblast growth factor receptor 2) gene as a locus associated with a small, but highly significant, increase in the risk of developing breast cancer. Using fine-scale genetic mapping of the region, it has been possible to narrow the causative locus to a haplotype of eight strongly linked single nucleotide polymorphisms (SNPs) spanning a region of 7.5 kilobases (kb) in the second intron of the FGFR2 gene. Here we describe a functional analysis to define the causative SNP, and we propose a model for a disease mechanism. Using gene expression microarray data, we observed a trend of increased FGFR2 expression in the rare homozygotes. This trend was confirmed using real-time (RT) PCR, with the difference between the rare and the common homozygotes yielding a Wilcox p-value of 0.028. To elucidate which SNPs might be responsible for this difference, we examined protein–DNA interactions for the eight most strongly disease-associated SNPs in different breast cell lines. We identify two cis-regulatory SNPs that alter binding affinity for transcription factors Oct-1/Runx2 and C/EBPβ, and we demonstrate that both sites are occupied in vivo. In transient transfection experiments, the two SNPs can synergize giving rise to increased FGFR2 expression. We propose a model in which the Oct-1/Runx2 and C/EBPβ binding sites in the disease-associated allele are able to lead to an increase in FGFR2 gene expression, thereby increasing the propensity for tumour formation

mTORC1 plays an important role in osteoblastic regulation of B-lymphopoiesis

Skeletal osteoblasts are important regulators of B-lymphopoiesis, serving as a rich source of factors such as CXCL12 and IL-7 which are crucial for B-cell development. Recent studies from our laboratory and others have shown that deletion of Rptor, a unique component of the mTORC1 nutrient-sensing complex, early in the osteoblast lineage development results in defective bone development in mice. In this study, we now demonstrate that mTORC1 signalling in pre-osteoblasts is required for normal B-lymphocyte development in mice. Targeted deletion of Rptor in osterix-expressing pre-osteoblasts (Rptor; ob; -/-; ) leads to a significant reduction in the number of B-cells in the bone marrow, peripheral blood and spleen at 4 and 12 weeks of age. Rptor; ob; -/-; mice also exhibit a significant reduction in pre-B and immature B-cells in the BM, indicative of a block in B-cell development from the pro-B to pre-B cell stage. Circulating levels of IL-7 and CXCL12 are also significantly reduced in Rptor; ob; -/-; mice. Importantly, whilst Rptor-deficient osteoblasts are unable to support HSC differentiation to B-cells in co-culture, this can be rescued by the addition of exogenous IL-7 and CXCL12. Collectively, these findings demonstrate that mTORC1 plays an important role in extrinsic osteoblastic regulation of B-cell development