Safe Decisions Research Articles

An analysis of ambulance re-contacts after non-conveyance: a retrospective cohort study in the Netherlands

BackgroundNon-conveyance is an increasing part of ambulance care and has to be safe. One of the indicators to measure safety is an ambulance re-contact within 72 h. However, solely measuring the percentage of re-contacts has limited validity as it lacks insight in actual reasons of an ambulance re-contact. Therefore, the aim of our study was to analyze the incidence, reasons and outcomes of ambulance re-contacts within 72 h after non-conveyance.MethodsWe conducted a one year (2022) retrospective study in one EMS region in the Netherlands. Medical records of all non-conveyance runs with a re-contact were analyzed using a framework to categorize re-contact reasons in illness-related, patient-related, professional-related, and unrelated. Re-contact outcomes were measured in terms of (non-)conveyance and mortality.Results585/13.879 (4.2%) non-conveyance runs had a re-contact within 72 h. 547/585 (93.5%) re-contacts could be categorized with the framework. Re-contacts were related to the illness (n = 267, 48.8%), the patient (n = 130, 23.8%), the professional (n = 106, 19.4%) and unrelated (n = 44, 8.0%). Four subreasons accounted for 68.5% of reasons for re-contacts: progression of disease (19.4%), recurrent disease process/exacerbation (18.6%), reassessment and ambulance request by another medical professional (15.9%), and psychiatric disorder and/or substance abuse (14.6%). 403/547 (73.7%) patients with a re-contact were conveyed to the hospital. Mortality rate for patients with a re-contact was 0.5%.ConclusionsRe-contact incidence after non-conveyance is relatively low, with a very small part of re-contacts related to ambulance care professionals making errors in diagnosis or treatment. Combined with low re-contact mortality, this indicates safe non-conveyance decisions. Re-contacts as quality indicator cover a variety of reasons, with almost half of the re-contacts being related to illness. Four subcategories accounted for the majority of all reasons for re-contacts: progression of disease, recurrent disease process/exacerbation, reassessment and ambulance request by another medical professional, and psychiatric disorder and/or substance abuse. Three-quarters of the patients were conveyed, although more re-contacts due to patient related reasons ended in non-conveyance again.

An Autonomous Vehicle Behavior Decision Method Based on Deep Reinforcement Learning with Hybrid State Space and Driving Risk

Behavioral decision-making is an important part of the high-level intelligent driving system of intelligent vehicles, and efficient and safe behavioral decision-making plays an important role in the deployment of intelligent transportation system, which is a hot topic of current research. This paper proposes a deep reinforcement learning (DRL) method based on mixed-state space and driving risk for autonomous vehicle behavior decision-making, which enables autonomous vehicles to make behavioral decisions with minimal instantaneous risk through deep reinforcement learning training. Firstly, based on the various behaviors that may be taken by autonomous vehicles during high-speed driving, a calculation method for autonomous vehicle driving risk is proposed. Then, deep reinforcement learning methods are used to improve the safety and efficiency of behavioral decision-making from the interaction between the vehicle and the driving environment. Finally, the effectiveness of the proposed method is proved by training verification in different simulation scenarios, and the results show that the proposed method can enable autonomous vehicles to make safe and efficient behavior decisions in complex driving environments. Compared with advanced algorithms, the method proposed in this paper improves the driving distance of autonomous vehicle by 3.3%, the safety by 2.1%, and the calculation time by 43% in the experiment.

Sexual education around the world: in Australia and Oceania and Europe.

Sexual education is a vital process of teaching and learning about various aspects of human sexuality, including physical, emotional, social, and cultural dimensions. Its primary goal is to equip individuals, especially adolescents, with the necessary knowledge, skills, and values to make informed, responsible, and safe decisions regarding their sexual and reproductive lives. This article examines sexual education programs in Australia, Oceania, and Europe, addressing the current state, the unique challenges, and recommendations for enhancing these programs to meet the needs of modern society.

Hepatotoxicity of statins: a real-world study based on the US Food and Drug Administration Adverse Event Reporting System database.

Statins, as an important class of lipid-lowering drugs, play a key role in the prevention and treatment of cardiovascular diseases. However, with their widespread use in clinical practice, some adverse events have gradually emerged. In particular, the hepatotoxicity associated with statins use has become one of the clinical concerns that require sufficient attention. In this study, we conducted a comprehensive and detailed analysis of the hepatotoxicity of statins based on the data of the US Food and Drug Administration Adverse Event Reporting System database from the first quarter (Q1) of 2004 to the Q1 of 2024 and used Reporting Odds Ratios and Empirical Bayes Geometric Mean to mine the signal of adverse events. In this study, hepatic disorder related seven statins all exhibited positive signals. Through signal mining, we identified a total of 14,511 cases of adverse events associated with hepatic disorder caused by these statin drugs, with atorvastatin, simvastatin, and rosuvastatin occurring at a higher rate. A total of 148 positive signals related to adverse events of hepatic disorder were captured. Autoimmune hepatitis and drug-induced liver injury both presented positive signals across multiple statin drugs. Notably, atorvastatin had the most significant signal strength in cholestatic pruritus and bilirubin conjugation abnormal. Fluvastatin also showed notable signal strength in autoimmune hepatitis, while simvastatin had a relatively weaker signal strength for hepatic enzyme increased. This study discovered specific adverse event signal values, revealing potential hepatotoxic risks associated with the use of statin drugs. The results provide an important reference for the safe clinical use of drugs, help to improve the understanding of the safety of statins, and also provide a scientific basis for clinicians to make more accurate and safe decisions when making treatment plans.

Fair prediction sets through multi-objective hyperparameter optimization

The widespread implementation of machine learning in safety-critical domains has raised ethical concerns regarding algorithmic discrimination. In such settings, the integration of fairness-aware algorithms with uncertainty quantification tools enables the development of reliable and safe decision-making. In this paper, we introduce a novel methodology that combines conformal prediction, offering rigorous prediction sets, with multi-objective optimization via evolutionary learning. The proposed meta-algorithm optimizes the hyperparameter configuration of classifiers to produce confidence predictors that balance efficiency and equalized coverage guarantees, addressing fairness concerns related to sensitive attributes. We empirically evaluate our methodology with four real-world problems and demonstrate its efficacy in exploring this trade-off and producing a repertoire of Pareto optimal conformal predictors. In this way, our contribution offers different modeling alternatives from which to choose depending on the policy adopted by stakeholders, thus illustrating its capability to enhance equitable decision-making.

Community and familial dynamics influencing risk behavior for HIV acquisition among adolescent girls and young women in Uganda: Qualitative analysis using Protective Motivation Theory.

In Uganda, adolescent girls', and young women's (AGYW-15-24 years) current HIV prevalence is fourfold compared with their male counterparts due to compounded social, economic, and environmental factors. Using the Protective Motivation Theory (PMT), we explored HIV-acquisition risk sources and perceived protective factors from AGYW and caregivers' perspective. During 2018, we conducted a qualitative study guided by PMT to explore factors influencing HIV acquisition among AGYW. We purposively sampled two groups of key informants, AGYW at high-risk for HIV acquisition (uninfected) and AGYW living with HIV, varied by age and place of residence (urban/rural). We conducted 34 focus group discussions with AGYW, nine with AGYW parents, and 25 key informant interviews. Data were analyzed using the framework method based on the PMT and developed from participants' narratives. AGYW were knowledgeable about HIV, HIV acquisition risk factors, and HIV prevention interventions. Nonetheless, few AGYW knew about pre-exposure prophylaxis (PrEP). Imbalance in power relations between the genders explained inability of AGYW making safe healthy decisions, with social norms giving men power over women. Parents modelling positively influenced HIV risk behavior. Many AGYW viewed staying in school a protective factor both while at school and further for life. AGYW identified alcohol use, desire for material possessions, discounting HIV disease severity, social norms, and poverty as barriers to engaging in self-protective behaviors. Several AGYW believed that access to AGYW-focused programs would facilitate healthy sex-positive, protective behaviors. While PMT focuses on individual factors confirmed by our findings, we found HIV risk behavior to be influenced by complex contextual factors including poverty, gender inequality and cultural norms. Distinct HIV risk factors among AGYW require policy and comprehensive targeted interventions addressing violence, alcohol consumption, increased economic opportunities, educational opportunities, safe-sex practices, and PrEP scale-up which may prevent HIV in AGYW and facilitate HIV epidemic control.

Effects of maternal separation on punishment-driven risky decision making in adolescence and adulthood.

Early life adversity (ELA) is associated with a multitude of neural and behavioral aberrations. To develop treatments to mitigate the effects of ELA, it is critical to determine which aspects of cognition are affected and when these disturbances manifest across the lifespan. Here, we tested the effects of maternal separation, an established rodent model of ELA, on punishment-driven risky decision-making longitudinally in both adolescence (25-55days old) and adulthood (80-100days old). Risk-taking was assessed with the Risky Decision-making Task, wherein rats choose between a small, safe reward and a large reward accompanied by an escalating risk of punishment (foot shock). We observed that rats exposed to maternal separation were more prone to risk-taking than controls during adolescence, and demonstrated reduced latency to make both risky and safe decisions. Interestingly, this augmented risk-taking was no longer evident in adulthood. Males and females displayed comparable levels of risk-taking during adolescence then diverged in adulthood, with adult males displaying a sharp increase in risk-taking. Finally, we observed that risk-taking changed across the lifespan in rats exposed to maternal separation, but not in control rats. Collectively, these data reveal that ELA engenders risk-taking in adolescence but not adulthood, and that sex differences in risky decision-making are not evident until adulthood. This has important implications for the development of both behavioral and biological treatments to improve decision-making during the vulnerable adolescent period.

Influence of Time Pressure and Flood Information Type on Flood Alert Effectiveness in Driving

Flood alerts are a means of risk communication that alerts the public to potential floods. The purpose of this research was to investigate factors that affected drivers’ understanding and actions given a flood presented through a mobile navigation application. Two experiments were conducted to examine the effects of time pressure and type of flood information on drivers’ planned actions when faced with potential flooding. Participants were asked about their planned actions given one type of flood information in a driving scenario either with or without time pressure. Our results indicated significant differences in participants’ behaviors across the different flood information types, but not between the two time-pressure conditions. These results suggest that displaying the flood information is helpful in promoting drivers’ safe decisions to avoid the potentially flooded roadway, and that detailed information may help users better perceive the depth and risk of the potential flood.

Good luck or bad luck? The influence of social comparison on risk‐taking decision and the underlying neural mechanism

AbstractThe present study aimed to investigate the impact of social comparison on risk‐taking behaviors and the neural underpinnings within a competitive context. Participants who thought they were playing against a stranger in a gambling task were actually playing against a programmed computer. Eighty‐eight college students were assigned to one of three comparison conditions (downward, upward, and parallel) by varying the probability of gain. Behavioral results showed that disadvantage led to increased risk‐taking. Event‐related potential data analyses showed, in the parallel comparison condition, a significantly larger Feedback‐Related Negativity (FRN) was induced by the self's safe decision than the risky decision and by loss rather than gain. However, in the upward and downward comparison conditions, larger FRN emerged solely in response to the loss of risky rather than safe decisions. On the P3 component, participants in the upward comparison condition showed no significant difference in response to their gain or loss, while the other two conditions did. The highest P3 amplitude, delta/theta power, and aperiodic activity were found in the closely matched condition. Finally, in the downward comparison condition, a stronger delta/theta power was correlated with a less risky decision. Overall, the findings indicate that parity heightens emotional arousal and engages more cognitive resources.

Abstract 4135726: Prospective validation and implementation pilot study of an emergency department heart failure risk stratification tool: STRIDE-HF

Background: We previously found the STRIDE-HF emergency department (ED) risk tool accurately predicted risk of a 30-day serious adverse event (SAE), including 30-day mortality, cardiopulmonary resuscitation, intra-aortic balloon pump insertion, intubation, new dialysis, myocardial infarction, or coronary revascularization. Research question: We sought to prospectively validate STRIDE-HF and describe safety of the deployed model in a clinical pilot. We hypothesized that performance would decrease slightly with prospective evaluation and that real-time risk display would contribute to safe disposition decisions. Goals: 1) To prospectively validate KPCARES-HF across 21 community EDs among ED patients with acute heart failure (AHF) from January 1, 2023 – December 31 st , 2023; and 2) to describe outcomes among patients predicted to be very low risk and discharged home in the clinical pilot. Methods: For prospective validation, we report 30-day mortality rates by risk strata. We assess model performance using area under the receiver operator curve (AUROC) and sensitivity at a key clinical threshold. We describe rates of 30-day SAE among patients predicted to be very low risk and discharged after ED or observation unit care in the clinical pilot. Results: There were 13,274 ED patients in the prospective validation; median age was 76, 50.8% were female, and 44.5% were non-White. We found 11.4%, 24.8%, 31.9%, and 31.9% of patients were very low, low, moderate, and high risk, respectively, while 21.6%, 15.2% and 63.0% were discharged, observed, and admitted, respectively. Among discharged patients, 29.2% and 13.3% were moderate or high risk, respectively, and 30-day mortality rates among these patients were 2.2% and 8.4%, respectively. Among 8,363 admitted patients, 27.7% were very low or low risk. Conclusions: STRIDE-HF maintained high predictive accuracy with prospective validation in this diverse, multi-center cohort. Our findings suggest that use of STRIDE-HF might help better align risk with admission decision and can be safely used to assist providers in identifying patients who may be stable for outpatient care.

Architectural design of national evidence based medicine information system based on electronic health record.

The global implementation of Electronic Health Records has significantly enhanced the quality of medical care and the overall delivery of public health services. The incorporation of Evidence-Based Medicine offers numerous benefits and enhances the efficacy of decision-making in areas such as prevention, prognosis, diagnosis, and therapeutic approaches. The objective of this paper is to propose an architectural design of an Evidence-Based Medicine information system based on the Electronic Health Record, taking into account the existing and future level of interoperability of health information systems in Greece. A study of the suggested evidence-based medicine architectures found in the existing literature was conducted. Moreover, the interoperability architecture of health information systems in Greece was analyzed. The architecture design reviewed by specialized personnel and their recommendations were incorporated into the final design of the proposed architecture. The proposed integrated architecture of an Evidence-Based Medicine system based on the Electronic Health Record integrates and utilizes citizens' health data while leveraging the existing knowledge available in the literature. Taking into consideration the recently established National Interoperability Framework, which aligns with the European Interoperability Framework, the proposed realistic architectural approach contributes to improving the quality of healthcare provided through the ability to make safe, timely and accurate decisions by physicians.

An empirical evaluation of a formal approach versus ad hoc implementations in robot behavior planning

As autonomous robotic systems integrate into various domains, ensuring their safe operation becomes increasingly crucial. A key challenge is guaranteeing safe decision making for cyber-physical systems, given the inherent complexity and uncertainty of real-world environments.Tools like Gwendolen, vGOAL, and Tumato enable the use of formal methods to provide guarantees for correct and safe decision making. This paper concerns Tumato, a formal planning framework that generates complete behavior from a declarative specification. Tumato ensures safety by avoiding unsafe actions and states while achieving robustness by considering nondeterministic outcomes of actions. While formal methods claim to manage complexity, provide safety guarantees, and ensure robustness, empirical evaluation is necessary to validate these claims.This work presents an empirical study comparing the characteristics of various ad hoc behavior planning implementations (developed by participants with diverse levels of experience in computer science), with implementations using Tumato. We investigate the usability of the different approaches and evaluate i) their effectiveness, ii) the achieved safety (guarantees), iii) their robustness in handling uncertainties, and iv) their adaptability, extensibility, and scalability. To our knowledge, this is the first participant-based empirical study of a formal approach for (safe and robust) autonomous behavior.Our analysis confirms that while ad hoc methods offer some development flexibility, they lack the rigorous safety guarantees provided by formal methods. The study supports the hypothesis that formal methods, as implemented in Tumato, are effective tools for developing safe autonomous systems, particularly in managing complexity and ensuring robust decision making and planning.

Health status assessment of pump station units based on spatio-temporal fusion and uncertainty information

An effective health status assessment (HSA) for pump station units (PSUs) is crucial for accurately determining their real status and providing technical support for safe operational decisions. Due to the limitations of existing data-driven HSA methods, which primarily focus on the temporal dependencies of monitoring signals and fail to explore the complex interconnections among signals comprehensively. Moreover, when constructing performance degradation indices based on linear differences, these methods do not effectively integrate heterogeneous signals, resulting in an incomplete and inaccurate assessment of the overall system degradation. This paper proposes a real-time comprehensive HSA method for PSUs based on multi-source heterogeneous uncertainty information. Initially, a health benchmark model (HBM) is built using CrossGNN, which possesses cross-scale and cross-variable interaction capabilities, to precisely capture the temporal dependencies and dynamic relationships among variables in monitoring signals. Subsequently, key measurement points that reflect the operational status of the PSUs are identified through correlation analysis to establish multi-source evaluation indices. Then, considering the uncertainty in signal changes, a novel health degradation index (HDI) is developed using Mahalanobis distance (MD) and the Gaussian Cloud Model (GCM) to analyze changes in unit status. Furthermore, a weighting calculation method based on the non-dominated sorting genetic algorithm (NSGA-II) is proposed to establish a real-time comprehensive health index (RCHDI) for a thorough assessment of PSUs status. Finally, the effectiveness of the proposed method is validated through a case study using data from a pump station in the South-to-North Water Diversion Project in China. The results show that, compared to other studies, the proposed method significantly improves the stability and smoothness of the state assessment curve, with increases of 21.5% and 47.1% respectively, providing a new perspective for comprehensively assessing the health status of PSUs.V

A comprehensive review on safe reinforcement learning for autonomous vehicle control in dynamic environments

To operate safely in a dynamic environment, autonomous vehicles must possess the same level of predictive driving abilities as human drivers and must be capable of anticipating the future actions of other dynamic objects in the environment, especially those of neighboring vehicles. The development of safe autonomous vehicles (AVs) poses a challenging task as it requires algorithms that can make real-time decisions in unpredictable circumstances. Reinforcement learning (RL) presents a promising approach for AV control, as it utilizes trial and error to enable optimal decision-making. However, traditional RL algorithms are unsuitable for safety-critical applications, as they may explore unsafe actions, potentially resulting in accidents. Safe reinforcement learning (SRL) algorithms have been developed to address this issue, prioritizing safe and reliable decisions. These algorithms incorporate constraints to prevent unsafe actions or utilize techniques to estimate action risk and avoid actions deemed excessively risky. Despite computational challenges, SRL holds significant promise for AV control, and is likely to play a crucial role in developing safe and reliable systems. SRL methods are critical for the general adoption of autonomous vehicles by guaranteeing their safety and reliability. These algorithms utilize methods like uncertainty and risk estimation along with penalty functions, to avoid excessively risky actions and have the potential to significantly reduce accidents and build public trust in autonomous driving. However, there are challenges that need to be addressed, such as the dynamic nature of real-world traffic, high computational costs, and the diversity of road design; and these varying conditions make the designing, testing, and validating of SRL algorithms difficult. Despite these challenges, SRL presents a promising solution, through integrating new sensing technologies and machine learning techniques, to develop safe, efficient, and environmentally friendly transportation systems.

Research on the Innovation Path of Enterprise Management Mode in the Era of Big Data

With the continuous development of the market economy and the advent of the big data era, traditional management models cannot meet the requirements for enterprise development, which poses certain obstacles to business growth. Therefore, enterprises must continuously leverage the commercial value embedded in the big data era to innovate their management models. In practical terms, internal managers and relevant personnel can innovate based on traditional management models, fully utilizing the advantages of big data to optimize and innovate enterprise management models. By utilizing information technology for extensive data analysis and integration, businesses can be guided in the right direction, provided with reasonable operational plans, and ensured safe decision-making, thereby achieving healthy and sustainable development. This approach enables enterprise management to keep pace with the progress of the times and enhances the role of management in business operations.

Impact of aesthetic surgery performed abroad on the Irish healthcare system

IntroductionAesthetic surgery tourism is a flourishing trend, and challenges often arise when patients return home with post-operative complications, necessitating follow-up care. MethodsBetween July 2021 and June 2023, we conducted a retrospective analysis of patients who presented with complications from aesthetic surgery tourism in two major teaching hospitals in Ireland. ResultsThirty-three patients with a mean age of 41 years were identified. Procedures were predominantly performed in Turkey (67%), followed by Lithuania (24%). Complications included wound dehiscence (n=22), infections (n=9), seroma (n=9), hematoma (n=2) and skin necrosis (n=1). A total of 27 operations were performed, with an average hospital stay of four days and a per-patient cost of €5 486. ConclusionComplications from aesthetic surgery abroad not only have a psychological and financial impact on the individuals involved but also strain our public healthcare system. Therefore, it is important for us, as medical professionals to advocate for our patients in order for them to make informed and safe decisions before seeking healthcare abroad.

LATEST ADVANCES IN FACIAL NERVE INTRAOPERATIVE MONITORING FOR VESTIBULAR SCHWANNOMA - UP TO DATE 2024

Introduction: Vestibular schwannoma, a benign tumor of the eighth cranial nerve, can be treated with radiosurgery, microsurgery, or observation. This study aims to present advances in intraoperative monitoring techniques for preserving facial nerve function during acoustic neuroma surgeries. By sharing the latest evidence, we hope to influence clinical practices for the benefit of patients. Methodology: Thus, we conducted a comprehensive literature review using the Scopus database, we searched for articles published from 2018 to 2023 using the keywords "facial paralysis," "acoustic neuroma," and "intraoperative monitoring." Results: The use of electromyographic parameters in the pre, intra, and post-resection monitoring of vestibular schwannoma provides valuable indicators of both the functional state of the facial nerve and the tumor adherence. This information plays a crucial role in making safe decisions regarding the extent of tumor resection while minimizing the risk of facial nerve damage during surgery. Supramaximal stimulation of the facial nerve in proximity to the tumor is of utmost importance to preserve facial function. However, the presence of a separate intermediate nerve poses challenges in accurately detecting false positives. Therefore, monitoring the facial nerve during surgery becomes essential to prevent potential injuries and to predict both short- and long-term outcomes. Conclusion: Intraoperative electrophysiological facial nerve monitoring is a crucial strategy to reduce postoperative facial paralysis. While the best technique is still under debate, several options exist to enhance monitoring efficacy and patient safety. By staying informed, clinicians can make better decisions to improve patient outcomes.

Outcomes of adult patients discharged at scene by emergency medical services

BackgroundThe outcomes of patients who call an ambulance but are discharged at scene reflect the safety and quality of emergency medical service (EMS) care. While previous studies have examined the...

Pediatric Syncope: Is the Diagnostic Guideline Implemented and Adhered to?

We sought to investigate adherence to the current pediatric syncope guideline in the emergency department and its impact on the frequency of missed or unnecessary diagnostic measures. For the first time, in 2014 updated guideline defines indispensable basic diagnostic measures and a consecutive algorithm for safe clinical decision making. We analyzed retrospectively 314 pediatric patients, 166 were presented before and 148 after publication of this guideline update. After guideline publication, 54 patients (36.5%) were not treated in accordance with the guideline and 2 (0.63%) cases caused by epileptic seizures were initially misdiagnosed as reflex syncope. Among these 54 patients, 32 (59.3%) inpatient admissions were inappropriate, as well as 11 (20.4%) electroencephalographies, 4 (7.4%) sleep-deprivation EEGs, 2 (3.7%) magnetic resonance imaging, 5 (9.3%) urine diagnostics and 32 (59.3%) blood tests. In 21 cases (38.9%), the medical history was insufficient. ECG was missed in 42 patients (77.8%). There was no significant difference between the pre- and post-guideline groups concerning diagnostic work-up (p=0,12). This non-compliance with the guideline did not cause a large number of misdiagnosed epileptic seizures (1.4%) or adverse outcomes but led to waste of resources in healthcare system and undue burdens on patients and their families. In addition to establishment of clinical guidelines, the need for additional measures and strategies to promote their implementation seems obvious.

Modeling Autonomous Vehicle Responses to Novel Observations Using Hierarchical Cognitive Representations Inspired Active Inference

Equipping autonomous agents for dynamic interaction and navigation is a significant challenge in intelligent transportation systems. This study aims to address this by implementing a brain-inspired model for decision making in autonomous vehicles. We employ active inference, a Bayesian approach that models decision-making processes similar to the human brain, focusing on the agent’s preferences and the principle of free energy. This approach is combined with imitation learning to enhance the vehicle’s ability to adapt to new observations and make human-like decisions. The research involved developing a multi-modal self-awareness architecture for autonomous driving systems and testing this model in driving scenarios, including abnormal observations. The results demonstrated the model’s effectiveness in enabling the vehicle to make safe decisions, particularly in unobserved or dynamic environments. The study concludes that the integration of active inference with imitation learning significantly improves the performance of autonomous vehicles, offering a promising direction for future developments in intelligent transportation systems.