Project description:ObjectivesNear misses happen more frequently than actual errors, and highlight system vulnerabilities without causing any harm, thus provide a safe space for organizational learning. Second-order problem solving behavior offers a new perspective to better understand how nurses promote learning from near misses to improve organizational outcomes. This study aimed to explore frontline nurses' perspectives on using second-order problem solving behavior in learning from near misses to improve patient safety.MethodsA qualitative exploratory study design was employed. This study was conducted in three tertiary hospitals in east China from June to November 2015. Purposive sampling was used to recruit 19 frontline nurses. Semi-structured interviews and a qualitative directed content analysis was undertaken using Crossan's 4I Framework of Organizational Learning as a coding framework.ResultsSecond-order problem solving behavior, based on the 4I Framework of Organizational Learning, was referred to as being a leader in exposing near misses, pushing forward the cause analysis within limited capacity, balancing the active and passive role during improvement project, and promoting the continuous improvement with passion while feeling low-powered.Conclusions4I Framework of Organizational Learning can be an underlying guide to enrich frontline nurses' role in promoting organizations to learn from near misses. In this study, nurses displayed their pivotal role in organizational learning from near misses by using second-order problem solving. However, additional knowledge, skills, and support are needed to maximize the application of second-order problem solving behavior when near misses are recognized.
Project description:Physician stress is associated with near misses and adverse medical events. However, little is known about physiological mechanisms linking stress to such events. We explored the utility of machine learning to determine whether the catabolic stress hormone cortisol and the anabolic, anti-stress hormone dehydroepiandrosterone sulfate (DHEA-S), as well as the cortisol to DHEA-S ratio relate to near misses in emergency medicine residents during active duty in a trauma 1 emergency department. Compared to statistical models better suited for inference, machine learning models allow for prediction in situations that have not yet occurred, and thus better suited for clinical applications. This exploratory study used multiple machine learning models to determine possible relationships between biomarkers and near misses. Of the various models tested, support vector machine with radial bias function kernels and support vector machine with linear kernels performed the best, with training accuracies of 85% and 79% respectively. When evaluated on a test dataset, both models had prediction accuracies of around 80%. The pre-shift cortisol to DHEA-S ratio was shown to be the most important predictor in interpretable models tested. Results suggest that interventions that help emergency room physicians relax before they begin their shift could reduce risk of errors and improve patient and physician outcomes. This pilot demonstrates promising results regarding using machine learning to better understand the stress biology of near misses. Future studies should use larger groups and relate these variables to information in electronic medical records, such as objective and patient-reported quality measures.
Project description:IntroductionStudying gambling behavior is a crucial element in reducing the impact of problem gambling. Nevertheless, most current research is carried out in controlled laboratory settings rather than real-life situations, which raises concerns about how applicable the findings are in the broader context. Virtual reality (VR) has proven to be a valuable tool and has been utilized in various experimental scenarios. A limited number of studies have employed VR to investigate gambling behaviors, and few have explored them in an older adolescent context.MethodsThis study examined the behavioral and physiological effects of gambling behavior, including problem gambling, gaming addiction, and risk-taking decision-making in a sample of 36 high-school students aged between 18 to 20 years using an ad-hoc constructed VR scenario designed to simulate a slot-machine platform.ResultsThe behavioral results highlighted that participants reporting more problem gambling were sensitive to near-misses: i.e., they bet more after near-misses than after losses. This result may reflect the false belief that gamblers, after near-misses, are closer to winning. Physiological data showed that participants exhibited heart rate deceleration during the anticipation of the outcome, which has been suggested to represent a marker of feedback anticipation processing and hyposensitivity to losses.DiscussionOverall, this study provides evidence for a new VR tool to assess gambling behaviors and new insights into gambling-related behavioral and physiological factors. Implications for the treatment of problem gambling are discussed.
Project description:BackgroundePrescribing systems have significant potential to improve the safety and efficiency of healthcare, but they need to be carefully selected and implemented to maximise benefits. Implementations in English hospitals are in the early stages and there is a lack of standards guiding the procurement, functional specifications, and expected benefits. We sought to provide an updated overview of the current picture in relation to implementation of ePrescribing systems, explore existing strategies, and identify early lessons learned.MethodsA descriptive questionnaire-based study, which included closed and free text questions and involved both quantitative and qualitative analysis of the data generated.ResultsWe obtained responses from 85 of 108 NHS staff (78.7% response rate). At least 6% (n = 10) of the 168 English NHS Trusts have already implemented ePrescribing systems, 2% (n = 4) have no plans of implementing, and 34% (n = 55) are planning to implement with intended rapid implementation timelines driven by high expectations surrounding improved safety and efficiency of care. The majority are unclear as to which system to choose, but integration with existing systems and sophisticated decision support functionality are important decisive factors. Participants highlighted the need for increased guidance in relation to implementation strategy, system choice and standards, as well as the need for top-level management support to adequately resource the project. Although some early benefits were reported by hospitals that had already implemented, the hoped for benefits relating to improved efficiency and cost-savings remain elusive due to a lack of system maturity.ConclusionsWhilst few have begun implementation, there is considerable interest in ePrescribing systems with ambitious timelines amongst those hospitals that are planning implementations. In order to ensure maximum chances of realising benefits, there is a need for increased guidance in relation to implementation strategy, system choice and standards, as well as increased financial resources to fund local activities.
Project description:"Near-miss" events, where unsuccessful outcomes are proximal to the jackpot, increase gambling propensity and may be associated with the addictiveness of gambling, but little is known about the neurocognitive mechanisms that underlie their potency. Using a simplified slot machine task, we measured behavioral and neural responses to gambling outcomes. Compared to "full-misses," near-misses were experienced as less pleasant, but increased desire to play. This effect was restricted to trials where the subject had personal control over arranging their gamble. Near-miss outcomes recruited striatal and insula circuitry that also responded to monetary wins; in addition, near-miss-related activity in the rostral anterior cingulate cortex varied as a function of personal control. Insula activity to near-misses correlated with self-report ratings as well as a questionnaire measure of gambling propensity. These data indicate that near-misses invigorate gambling through the anomalous recruitment of reward circuitry, despite the objective lack of monetary reinforcement on these trials.
Project description:BackgroundRelatively little is known about how scorecards presenting performance indicators influence medication safety. We evaluated the effects of implementing a ward-level medication safety scorecard piloted in two English NHS hospitals and factors influencing these.MethodsWe used a mixed methods, controlled before and after design. At baseline, wards were audited on medication safety indicators; during the 'feedback' phase scorecard results were presented to intervention wards on a weekly basis over 7 weeks. We interviewed 49 staff, including clinicians and managers, about scorecard implementation.ResultsAt baseline, 18.7% of patients (total n=630) had incomplete allergy documentation; 53.4% of patients (n=574) experienced a drug omission in the preceding 24 h; 22.5% of omitted doses were classified as 'critical'; 22.1% of patients (n=482) either had ID wristbands not reflecting their allergy status or no ID wristband; and 45.3% of patients (n=237) had drugs that were either unlabelled or labelled for another patient in their drug lockers. The quantitative analysis found no significant improvement in intervention wards following scorecard feedback. Interviews suggested staff were interested in scorecard feedback and described process and culture changes. Factors influencing scorecard implementation included 'normalisation' of errors, study duration, ward leadership, capacity to engage and learning preferences.DiscussionPresenting evidence-based performance indicators may potentially influence staff behaviour. Several practical and cultural factors may limit feedback effectiveness and should be considered when developing improvement interventions. Quality scorecards should be designed with care, attending to evidence of indicators' effectiveness and how indicators and overall scorecard composition fit the intended audience.
Project description:IntroductionNovice and beginner nurses make more medical errors than senior nurses. However, there is significant underreporting of medication errors and near misses among novice and beginner nurses.ObjectiveTo identify the factors that influence the intention of novice and beginner nurses to report medication errors and near misses.MethodsA cross-sectional exploratory study was carried out among third-year nursing students in a Quebec university (n = 143). Data was collected through a self-reported questionnaire based on the adapted Theory of Planned Behavior. Simple descriptive analyses and a series of contingency analyses were performed using Chi-2 or Fisher exact tests. Correction of multiple tests was done using Bonferroni test.ResultsAll theoretical constructs were significantly associated with intention. Sociodemographic factors (age, sex, experience and education program) were also associated with intention.Discussion and conclusionFurther studies are needed to identify the determinants of intention to report medication errors and near misses among novice and beginner nurses. More attention is required in nursing practice and education to act on these factors, thus encouraging novice and beginner nurses to report medication errors and near misses.
Project description:BackgroundIdentifying adverse events and near misses is essential to improving safety in the health care system. Patients are capable of reliably identifying and reporting adverse events. The effect of a patient safety reporting system used by families of pediatric inpatients on reporting of adverse events by health care providers has not previously been investigated.MethodsBetween Nov. 1, 2008, and Nov. 30, 2009, families of children discharged from a single ward of British Columbia's Children's Hospital were asked to respond to a questionnaire about adverse events and near misses during the hospital stay. Rates of reporting by health care providers for this period were compared with rates for the previous year. Family reports for specific incidents were matched with reports by health care providers to determine overlap.ResultsA total of 544 familes responded to the questionnaire. The estimated absolute increase in reports by health care providers per 100 admissions was 0.5% (95% confidence interval -1.8% to 2.7%). A total of 321 events were identified in 201 of the 544 family reports. Of these, 153 (48%) were determined to represent legitimate patient safety concerns. Only 8 (2.5%) of the adverse events reported by families were also reported by health care providers.InterpretationThe introduction of a family-based system for reporting adverse events involving pediatric inpatients, administered at the time of discharge, did not change rates of reporting of adverse events and near misses by health care providers. Most reports submitted by families were not duplicated in the reporting system for health care providers, which suggests that families and staff members view safety-related events differently. However, almost half of the family reports represented legitimate patient safety concerns. Families appeared capable of providing valuable information for improving the safety of pediatric inpatients.
Project description:BackgroundDelayed recognition of decompensation and failure-to-rescue on surgical wards are major sources of preventable harm. This review assimilates and critically evaluates available evidence and identifies opportunities to improve surgical ward safety.Data sourcesFifty-eight articles from Cochrane Library, EMBASE, and PubMed databases were included.ConclusionsOnly 15-20% of patients suffering ward arrest survive. In most cases, subtle signs of instability often occur prior to critical illness and arrest, and underlying pathology is reversible. Coarse risk assessments lead to under-triage of high-risk patients to wards, where surveillance for complications depends on time-consuming manual review of health records, infrequent patient assessments, prediction models that lack accuracy and autonomy, and biased, error-prone decision-making. Streaming electronic heath record data, wearable continuous monitors, and recent advances in deep learning and reinforcement learning can promote efficient and accurate risk assessments, earlier recognition of instability, and better decisions regarding diagnosis and treatment of reversible underlying pathology.