Emergency Department Provider Satisfaction with EMS Turnover Reports in Critical Trauma Patients

Introduction: Trauma accounts for 23% of all emergency department (ED) visits and is a leading cause of morbidity and mortality.1,2 Many critical trauma patients arrive to the ED by emergency medical services (EMS). EMS-ED handoff quality affects patient safety and quality of care.3-6 However, there is a scarcity of literature examining trauma patient handoffs and hospital staff satisfaction. The goal of this study was to investigate the relationship of specific information given during EMS handoffs with hospital staff satisfaction. Methods: This study observed handoffs of patients sustaining major trauma at the University of New Mexico (UNM) Hospital, the state’s only level I trauma center. UNM Hospital has a trauma alert protocol (TAP) to notify emergency medicine and surgery teams of incoming patients; these patients are assessed, stabilized, and treated by these teams. Data were collected from January 1, 2017 to December 31, 2017. This study included handoffs for TAP patients who were brought in by EMS. ED research assistants directly observed handoffs and recorded information using electronic data capture. Data points included vital signs (blood pressure, pulse, blood glucose, and mental status) and medical factors (allergies, IV access, injury mechanism, medications given by EMS, and home medications). Subjective factors included numerical satisfaction scores of EMS and various hospital providers for the handoff and the initial treatment/resuscitation after the handoff (both used 10-point Likert scales).
 Stata™ 14 was used for all analyses, with significance determined using t-tests and a type 1 error rate of 0.05. Results: We observed 180 handoffs and recorded satisfaction scores for 142 ED physicians, 53 surgeons, 68 nurses, and 163 EMS providers. Median satisfaction scores and interquartile ranges were: ED physicians 8 (8-9), surgeons 8 (7-9), nurses 9 (7-10), and EMS providers 9 (8-10). Provider satisfaction was unrelated to the number of vital signs reported, or to whether any individual vital sign was reported. Conversely, most medical factors were related to satisfaction by at least one type of provider (Table). The total number of medical factors reported was associated with satisfaction among ED physicians and nurses. Among physicians, handoff satisfaction and satisfaction with the resuscitation were associated. Conclusion: The quantity of medical factors transferred during EMS-ED handoffs provides a target for improving ED physician satisfaction. Medical factors, individually and in sum, varied in how they influenced receiving provider satisfaction. Emphasis of individual pertinent medical factors may need to be tailored based on audience. A limitation of this study is the use of ED provider satisfaction as a proxy for handoff quality. Of note, ED physician satisfaction was associated with resuscitation satisfaction. This may indicate that using satisfaction as a proxy for handoff quality is confounded by patient outcome. Transfer of vital signs was not correlated to increased satisfaction; this suggests the need for further research on redundancies between handoffs and initial ED assessment

Learning in a State of Confusion: Employing active perception and reinforcement learning in partially observable worlds

Institute of Perception, Action and BehaviourIn applying reinforcement learning to agents acting in the real world we are often faced with tasks that are non-Markovian in nature. Much work has been done using state estimation algorithms to try to uncover Markovian models of tasks in order to allow the learning of optimal solutions using reinforcement learning. Unfortunately these algorithms which attempt to simultaneously learn a Markov model of the world and how to act have proved very brittle. Our focus differs. In considering embodied, embedded and situated agents we have a preference for simple learning algorithms which reliably learn satisficing policies. The learning algorithms we consider do not try to uncover the underlying Markovian states, instead they aim to learn successful deterministic reactive policies such that agents actions are based directly upon the observations provided by their sensors. Existing results have shown that such reactive policies can be arbitrarily worse than a policy that has access to the underlying Markov process and in some cases no satisficing reactive policy can exist. Our first contribution is to show that providing agents with alternative actions and viewpoints on the task through the addition of active perception can provide a practical solution in such circumstances. We demonstrate empirically that: (i) adding arbitrary active perception actions to agents which can only learn deterministic reactive policies can allow the learning of satisficing policies where none were originally possible; (ii) active perception actions allow the learning of better satisficing policies than those that existed previously and (iii) our approach converges more reliably to satisficing solutions than existing state estimation algorithms such as U-Tree and the Lion Algorithm. Our other contributions focus on issues which affect the reliability with which deterministic reactive satisficing policies can be learnt in non-Markovian environments. We show that that greedy action selection may be a necessary condition for the existence of stable deterministic reactive policies on partially observable Markov decision processes (POMDPs). We also set out the concept of Consistent Exploration. This is the idea of estimating state-action values by acting as though the policy has been changed to incorporate the action being explored. We demonstrate that this concept can be used to develop better algorithms for learning reactive policies to POMDPs by presenting a new reinforcement learning algorithm; the Consistent Exploration Q(l) algorithm (CEQ(l)). We demonstrate on a significant number of problems that CEQ(l) is more reliable at learning satisficing solutions than the algorithm currently regarded as the best for learning deterministic reactive policies, that of SARSA(l)

ImageSpirit: Verbal Guided Image Parsing

Humans describe images in terms of nouns and adjectives while algorithms operate on images represented as sets of pixels. Bridging this gap between how humans would like to access images versus their typical representation is the goal of image parsing, which involves assigning object and attribute labels to pixel. In this paper we propose treating nouns as object labels and adjectives as visual attribute labels. This allows us to formulate the image parsing problem as one of jointly estimating per-pixel object and attribute labels from a set of training images. We propose an efficient (interactive time) solution. Using the extracted labels as handles, our system empowers a user to verbally refine the results. This enables hands-free parsing of an image into pixel-wise object/attribute labels that correspond to human semantics. Verbally selecting objects of interests enables a novel and natural interaction modality that can possibly be used to interact with new generation devices (e.g. smart phones, Google Glass, living room devices). We demonstrate our system on a large number of real-world images with varying complexity. To help understand the tradeoffs compared to traditional mouse based interactions, results are reported for both a large scale quantitative evaluation and a user study.Comment: http://mmcheng.net/imagespirit

Exploring the Links between Bilateral and Regional Trade Agreements and Merchandise Trade

Over 200 bilateral and regional trade agreements are currently in force, yet their impact remains a topic of debate. We analyse effects of 27 agreements that are of particular importance for Australia on the value of merchandise trade flows using data from 1970 up to the global financial crisis in 2008. We show that preferential trade agreements generally increase trade between members but that there are often offsetting negative effects on trade with non-signatories. In contrast to regional trading blocs and bilateral accords, agreements more oriented towards open trade principles have a positive impact on all trade flows of member nations

Timing, frequency and environmental conditions associated with mainstem-tributary movement by a lowland river fish, golden perch (Macquaria ambigua)

Tributary and mainstem connections represent important links for the movement of fish and other biota throughout river networks. We investigated the timing, frequency and environmental conditions associated with movements by adult golden perch (Macquaria ambigua) between the mainstem of the mid-Murray River and a tributary, the Goulburn River, in south-eastern Australia, using acoustic telemetry over four years (2007–2011). Fish were tagged and released in autumn 2007–2009 in the mid-Murray (n = 42) and lower Goulburn (n = 37) rivers within 3–6 km of the mid-Murray-lower Goulburn junction. 38% of tagged fish undertook mainstem–tributary movements, characterised mostly by temporary occupation followed by return of fish to the original capture river. Approximately 10% of tagged fish exhibited longer-term shifts between the mainstem and tributary. Movement of fish from the tributary into the mainstem occurred primarily during the spawning season and in some years coincided with the presence of golden perch eggs/larvae in drift samples in the mainstem. Many of the tributary-to-mainstem movements occurred during or soon after changes in flow. The movements of fish from the mainstem into the tributary were irregular and did not appear to be associated with spawning. The findings show that golden perch moved freely across the mainstem–tributary interface. This demonstrates the need to consider the spatial, behavioural and demographic interdependencies of aquatic fauna across geographic management units such as rivers

A digital ecosystems model of assessment feedback on student learning

The term ecosystem has been used to describe complex interactions between living organisms and the physical world. The principles underlying ecosystems can also be applied to complex human interactions in the digital world. As internet technologies make an increasing contribution to teaching and learning practice in higher education, the principles of digital ecosystems may help us understand how to maximise technology to benefit active, self-regulated learning especially among groups of learners. Here, feedback on student learning is presented within a conceptual digital ecosystems model of learning. Additionally, we have developed a Web 2.0-based system, called ASSET, which incorporates multimedia and social networking features to deliver assessment feedback within the functionality of the digital ecosystems model. Both the digital ecosystems model and the ASSET system are described and their implications for enhancing feedback on student learning are discussed