Video analytics for the detection of near-miss incidents on approach to railway level crossings

Recent modelling of socio-economic costs by the Australian railway industry in 2010 has estimated the cost of level crossing accidents to exceed AU$116 million annually. To better understand causal factors that contribute to these accidents, the Cooperative Research Centre for Rail Innovation is running a project entitled Baseline Level Crossing Video. The project aims to improve the recording of level crossing safety data by developing an intelligent system capable of detecting near-miss incidents and capturing quantitative data around these incidents. To detect near-miss events at railway level crossings a video analytics module is being developed to analyse video footage obtained from forward-facing cameras installed on trains. This paper presents a vision base approach for the detection of these near-miss events. The video analytics module is comprised of object detectors and a rail detection algorithm, allowing the distance between a detected object and the rail to be determined. An existing publicly available Histograms of Oriented Gradients (HOG) based object detector algorithm is used to detect various types of vehicles in each video frame. As vehicles are usually seen from a sideway view from the cabin’s perspective, the results of the vehicle detector are verified using an algorithm that can detect the wheels of each detected vehicle. Rail detection is facilitated using a projective transformation of the video, such that the forward-facing view becomes a bird’s eye view. Line Segment Detector is employed as the feature extractor and a sliding window approach is developed to track a pair of rails. Localisation of the vehicles is done by projecting the results of the vehicle and rail detectors on the ground plane allowing the distance between the vehicle and rail to be calculated. The resultant vehicle positions and distance are logged to a database for further analysis. We present preliminary results regarding the performance of a prototype video analytics module on a data set of videos containing more than 30 different railway level crossings. The video data is captured from a journey of a train that has passed through these level crossings.

Near-miss event detection at railway level crossings

Recent modelling of socio-economic costs by the Australian railway industry in 2010 has estimated the cost of level crossing accidents to exceed AU$116 million annually. To better understand the causal factors of these accidents, a video analytics application is being developed to automatically detect near-miss incidents using forward facing videos from trains. As near-miss events occur more frequently than collisions, by detecting these occurrences there will be more safety data available for analysis. The application that is being developed will improve the objectivity of near-miss reporting by providing quantitative data about the position of vehicles at level crossings through the automatic analysis of video footage. In this paper we present a novel method for detecting near-miss occurrences at railway level crossings from video data of trains. Our system detects and localizes vehicles at railway level crossings. It also detects the position of railways to calculate the distance of the detected vehicles to the railway centerline. The system logs the information about the position of the vehicles and railway centerline into a database for further analysis by the safety data recording and analysis system, to determine whether or not the event is a near-miss. We present preliminary results of our system on a dataset of videos taken from a train that passed through 14 railway level crossings. We demonstrate the robustness of our system by showing the results of our system on day and night videos.

Improving Near-Miss Event Detection Rate at Railway Level Crossings

Even though crashes between trains and road users are rare events at railway level crossings, they are one of the major safety concerns for the Australian railway industry. Nearmiss events at level crossings occur more frequently, and can provide more information about factors leading to level crossing incidents. In this paper we introduce a video analytic approach for automatically detecting and localizing vehicles from cameras mounted on trains for detecting near-miss events. To detect and localize vehicles at level crossings we extract patches from an image and classify each patch for detecting vehicles. We developed a region proposals algorithm for generating patches, and we use a Convolutional Neural Network (CNN) for classifying each patch. To localize vehicles in images we combine the patches that are classified as vehicles according to their CNN scores and positions. We compared our system with the Deformable Part Models (DPM) and Regions with CNN features (R-CNN) object detectors. Experimental results on a railway dataset show that the recall rate of our proposed system is 29% higher than what can be achieved with DPM or R-CNN detectors.

Brazilian network for the surveillance of maternal potentially life threatening morbidity and maternal near-miss and a multidimensional evaluation of their long term consequences

Background. It has been suggested that the study of women who survive life-threatening complications related to pregnancy (maternal near-miss cases) may represent a practical alternative to surveillance of maternal morbidity/mortality since the number of cases is higher and the woman herself is able to provide information on the difficulties she faced and the long-term repercussions of the event. These repercussions, which may include sexual dysfunction, postpartum depression and posttraumatic stress disorder, may persist for prolonged periods of time, affecting women's quality of life and resulting in adverse effects to them and their babies. Objective. The aims of the present study are to create a nationwide network of scientific cooperation to carry out surveillance and estimate the frequency of maternal near-miss cases, to perform a multicenter investigation into the quality of care for women with severe complications of pregnancy, and to carry out a multidimensional evaluation of these women up to six months. Methods/Design. This project has two components: a multicenter, cross-sectional study to be implemented in 27 referral obstetric units in different geographical regions of Brazil, and a concurrent cohort study of multidimensional analysis. Over 12 months, investigators will perform prospective surveillance to identify all maternal complications. The population of the cross-sectional component will consist of all women surviving potentially life-threatening conditions (severe maternal complications) or life-threatening conditions (the maternal near miss criteria) and maternal deaths according to the new WHO definition and criteria. Data analysis will be performed in case subgroups according to the moment of occurrence and determining cause. Frequencies of near-miss and other severe maternal morbidity and the association between organ dysfunction and maternal death will be estimated. A proportion of cases identified in the cross-sectional study will comprise the cohort of women for the multidimensional analysis. Various aspects of the lives of women surviving severe maternal complications will be evaluated 3 and 6 months after the event and compared to a group of women who suffered no severe complications in pregnancy. Previously validated questionnaires will be used in the interviews to assess reproductive function, posttraumatic stress, functional capacity, quality of life, sexual function, postpartum depression and infant development. © 2009 Cecatti et al.

Fatores determinantes da near miss materna em uma unidade de terapia intensiva obstétrica: avaliação das competências profissionais da área médica

Objective: Evaluate the determinants of morbidity and mortality in an obstetric intensive care unit and professional medical skills of students/residents at a university hospital. Methods: observational cross - sectional with 492 pregnant/pue rperal women and 261 students/residents. Patients were admitted to the obstetric intensive care unit during a year, being informed about the proposals of the study and a questionnaire was applied. The analysis was performed using Microsoft Excel 2013 and G raphPad6. Chi - square tests were used to evaluate risk factors and student t test evaluates resident/students' skills concerning the cognitive test and the Mini - Cex. Results: the main risk factors to near miss were: non - white race (OR = 2.527; RR = 2.342) ; marital status(married women) (OR = 7.968; RR = 7.113) , schooling (primary) (OR = 3.177 ; RR = 2.829) , from country town (OR = 4.643 ; RR = 4.087), low income (OR = 7014 ; RR = 5.554) , gestational hypertensive disorders (OR = 16.35 ; RR = 13.27) , re alization of pre - natal (OR = 5.023 ; RR = 4.254) and C - section before labor(OR = 39.21 ; RR = 31.25). In cognitive/Mini - cex analysis were noted significant difference in the performance of students on the subject (3.75 ± 0.93, 4.03 ± 0.94 and 4.88 ± 0.35). We still observed the best performance of residents, when compared to graduation students (p < 0.01). Conclusions: the prevalence of near miss was associated with socioeconomic/clinics factors and care issues, revealing the importance of interventions to improve these indicators. In addition, we suggest a better curriculum insertion of this subject in the medical Course disciplines due the importance to avoid the near miss through of adequacy of medical education.

Near miss materno e iniquidades em saúde: análise de determinantes contextuais no Rio Grande do Norte, Brasil

The scope of this study was to identify socioeconomic contextual and health care factors in primary care associated with maternal near misses and their marker conditions. This is an ecological study that used aggregated data of 63 clusters formed by the municipalities of State of Rio Grande do Norte, Brazil, using the Skater method of area regionalization, as the unit of analysis. The ratio of maternal near misses and their marker conditions were obtained from the Hospital Information System of the Brazilian Unified Health System. In multiple linear regression analysis, there was a significant association between maternal near misses and variables of poverty and poor primary health care. Hypertensive disorders were also associated with poverty and poor primary care and the occurrence of hemorrhaging was associated with infant mortality. It was observed that the occurrence of maternal near misses is linked to unfavorable socioeconomic conditions and poor quality health care that are a reflection of public policies that accentuate health inequalities.

Near miss materno e iniquidades em saúde: análise de determinantes contextuais no Rio Grande do Norte, Brasil

The scope of this study was to identify socioeconomic contextual and health care factors in primary care associated with maternal near misses and their marker conditions. This is an ecological study that used aggregated data of 63 clusters formed by the municipalities of State of Rio Grande do Norte, Brazil, using the Skater method of area regionalization, as the unit of analysis. The ratio of maternal near misses and their marker conditions were obtained from the Hospital Information System of the Brazilian Unified Health System. In multiple linear regression analysis, there was a significant association between maternal near misses and variables of poverty and poor primary health care. Hypertensive disorders were also associated with poverty and poor primary care and the occurrence of hemorrhaging was associated with infant mortality. It was observed that the occurrence of maternal near misses is linked to unfavorable socioeconomic conditions and poor quality health care that are a reflection of public policies that accentuate health inequalities.

Prevalência e fatores associados ao Near Miss Materno: inquérito populacional em uma capital do Nordeste Brasileiro

The scope of this study was to determine the prevalence of near misses and complications during pregnancy and the puerperal period, identifying the main clinical and intervention markers and socioeconomic and demographic factors associated with near misses. It involved a cross-sectional, population-based and probabilistic study with multi-stage complex sampling design conducted in Natal, State of Rio Grande do Norte, Brazil. A validated questionnaire was given to 848 women aged 15 to 49 identified in 8,227 households in 60 census sectors. In theanalysis of associations, the Chi-square test applied and calculated the prevalence ratio (PR) with Confidence Interval (CI) of 95% and 5% significance. The prevalence of maternal near misses was 41.1/1000LB, with hospitalization in an Intensive Care Unit (19.1/1000LB) and eclampsia (13.5/1000LB) being the most important markers. The prevalence of complications during pregnancy and the puerperal period was 21.2%. The highest prevalence of near misses was observed in older women, of black/brown race and low socioeconomic status. Conducting population surveys is feasible and may add important information to the study of near misses and the markers highlight the need for enhancing maternal care to reduce health inequality.

Prevalência e fatores associados ao Near Miss Materno: inquérito populacional em uma capital do Nordeste Brasileiro

The scope of this study was to determine the prevalence of near misses and complications during pregnancy and the puerperal period, identifying the main clinical and intervention markers and socioeconomic and demographic factors associated with near misses. It involved a cross-sectional, population-based and probabilistic study with multi-stage complex sampling design conducted in Natal, State of Rio Grande do Norte, Brazil. A validated questionnaire was given to 848 women aged 15 to 49 identified in 8,227 households in 60 census sectors. In theanalysis of associations, the Chi-square test applied and calculated the prevalence ratio (PR) with Confidence Interval (CI) of 95% and 5% significance. The prevalence of maternal near misses was 41.1/1000LB, with hospitalization in an Intensive Care Unit (19.1/1000LB) and eclampsia (13.5/1000LB) being the most important markers. The prevalence of complications during pregnancy and the puerperal period was 21.2%. The highest prevalence of near misses was observed in older women, of black/brown race and low socioeconomic status. Conducting population surveys is feasible and may add important information to the study of near misses and the markers highlight the need for enhancing maternal care to reduce health inequality.

Beyond maternal death: improving the quality of maternal care through national studies of ‘near-miss’ maternal morbidity

Knight M, Acosta C, Brocklehurst P, Cheshire A, Fitzpatrick K, Hinton L, Jokinen M, Kemp B, Kurinczuk JJ, Lewis G, Lindquist A, Locock L, Nair M, Patel N, Quigley M, Ridge D, Rivero-Arias O, Sellers S, Shah A on behalf of the UKNeS coapplicant group. Background Studies of maternal mortality have been shown to result in important improvements to women’s health. It is now recognised that in countries such as the UK, where maternal deaths are rare, the study of near-miss severe maternal morbidity provides additional information to aid disease prevention, treatment and service provision. Objectives To (1) estimate the incidence of specific near-miss morbidities; (2) assess the contribution of existing risk factors to incidence; (3) describe different interventions and their impact on outcomes and costs; (4) identify any groups in which outcomes differ; (5) investigate factors associated with maternal death; (6) compare an external confidential enquiry or a local review approach for investigating quality of care for affected women; and (7) assess the longer-term impacts. Methods Mixed quantitative and qualitative methods including primary national observational studies, database analyses, surveys and case studies overseen by a user advisory group. Setting Maternity units in all four countries of the UK. Participants Women with near-miss maternal morbidities, their partners and comparison women without severe morbidity. Main outcome measures The incidence, risk factors, management and outcomes of uterine rupture, placenta accreta, haemolysis, elevated liver enzymes and low platelets (HELLP) syndrome, severe sepsis, amniotic fluid embolism and pregnancy at advanced maternal age (≥ 48 years at completion of pregnancy); factors associated with progression from severe morbidity to death; associations between severe maternal morbidity and ethnicity and socioeconomic status; lessons for care identified by local and external review; economic evaluation of interventions for management of postpartum haemorrhage (PPH); women’s experiences of near-miss maternal morbidity; long-term outcomes; and models of maternity care commissioned through experience-led and standard approaches. Results Women and their partners reported long-term impacts of near-miss maternal morbidities on their physical and mental health. Older maternal age and caesarean delivery are associated with severe maternal morbidity in both current and future pregnancies. Antibiotic prescription for pregnant or postpartum women with suspected infection does not necessarily prevent progression to severe sepsis, which may be rapidly progressive. Delay in delivery, of up to 48 hours, may be safely undertaken in women with HELLP syndrome in whom there is no fetal compromise. Uterine compression sutures are a cost-effective second-line therapy for PPH. Medical comorbidities are associated with a fivefold increase in the odds of maternal death from direct pregnancy complications. External reviews identified more specific clinical messages for care than local reviews. Experience-led commissioning may be used as a way to commission maternity services. Limitations This programme used observational studies, some with limited sample size, and the possibility of uncontrolled confounding cannot be excluded. Conclusions Implementation of the findings of this research could prevent both future severe pregnancy complications as well as improving the outcome of pregnancy for women. One of the clearest findings relates to the population of women with other medical and mental health problems in pregnancy and their risk of severe morbidity. Further research into models of pre-pregnancy, pregnancy and postnatal care is clearly needed.

Beyond the numbers of maternal near-miss in Rwanda - a qualitative study on women's perspectives on access and experiences of care in early and late stage of pregnancy.

BACKGROUND: Rwanda has made remarkable progress in decreasing the number of maternal deaths, yet women still face morbidities and mortalities during pregnancy. We explored care-seeking and experiences of maternity care among women who suffered a near-miss event during either the early or late stage of pregnancy, and identified potential health system limitations or barriers to maternal survival in this setting. METHODS: A framework of Naturalistic Inquiry guided the study design and analysis, and the 'three delays' model facilitated data sorting. Participants included 47 women, who were interviewed at three hospitals in Kigali, and 14 of these were revisited in their homes, from March 2013 to April 2014. RESULTS: The women confronted various care-seeking barriers depending on whether the pregnancy was wanted, the gestational age, insurance coverage, and marital status. Poor communication between the women and healthcare providers seemed to result in inadequate or inappropriate treatment, leading some to seek either traditional medicine or care repeatedly at biomedical facilities. CONCLUSION: Improved service provision routines, information, and amendments to the insurance system are suggested to enhance prompt care-seeking. Additionally, we strongly recommend a health system that considers the needs of all pregnant women, especially those facing unintended pregnancies or complications in the early stages of pregnancy.

Using cooperative vehicle systems to collect near collision incidents events : a simulation study

On the road, near collision events (also close calls or near-miss incidents) largely outnumber actual crashes, yet most of them can never be recorded by current traffic data collection technologies or crashes analysis tools. The analysis of near collisions data is an important step in the process of reducing the crash rate. There have been several studies that have investigated near collisions; to our knowledge, this is the first study that uses the functionalities provided by cooperative vehicles to collect near misses information. We use the VISSIM traffic simulator and a custom C++ engine to simulate cooperative vehicles and their ability to detect near collision events. Our results showed that, within a simple simulated environment, adequate information on near collision events can be collected using the functionalities of cooperative perception systems. The relationship between the ratio of detected events and the ratio of equipped vehicle was shown to closely follow a squared law, and the largest source of nondetection was packet loss instead of packet delays and GPS imprecision.

New graduate occupational therapists' perceptions of near-misses and mistakes in the workplace

Purpose - The purpose of this paper is to explore the perceptions of near-misses and mistakes among new graduate occupational therapists from Australia and Aotearoa/New Zealand (NZ), and their knowledge of current incident reporting systems. Design/methodology/approach - New graduate occupational therapists in Australia and Aotearoa/NZ in their first year of practice (n=228) participated in an online electronic survey that examined five areas of work preparedness. Near-misses and mistakes was one focus area. Findings - The occurrence and disclosure of practice errors among new graduate occupational therapists are similar between Australian and Aotearoa/NZ participants. Rural location, structured supervision and registration status significantly influenced the perceptions and reporting of practice errors. Structured supervision significantly impacted on reporting procedure knowledge. Current registration status was strongly correlated with perceptions that the workplace encouraged event reporting. Research limitations/ implications - Areas for further investigation include investigating the perceptions and knowledge of practice errors within a broader profession and the need to explore definitional aspects and contextual factors of adverse events that occur in allied health settings. Selection bias may be a factor in this study. Practical implications - Findings have implications for university and workplace structures, such as clinical management, supervision, training about practice errors and reporting mechanisms in allied health. Originality/value - Findings may enable the development of better strategies for detecting, managing and preventing practice errors in the allied health professions.

Investigating the rates and impacts of near misses and related incidents among UK cyclists

The paper investigates the occurrence of non-injury incidents among cyclists in the UK, seeking to (i) generate a rate that can be compared with injury rates, (ii) analyse factors affecting incident rates, and (iii) analyse factors affecting the impact of incidents on cyclists. We collected data on non-injury cycling ‘incidents’ (near misses and other frightening and/or annoying incidents) from 1692 online diaries of cycle trip stages1 and incidents, participants having signed up in advance for a specific day. Following data cleaning and coding, a dataset was created covering 1532 diary days and 3994 records of incidents occurring within the UK. Incident rates were calculated and compared to injury risks for cyclists. Cross-tabulation and regression were used to identify factors affecting incident rates and the effect an incident has on the cyclist. Frightening or annoying non-injury incidents, unlike slight injuries, are an everyday experience for most people cycling in the UK. For regular cyclists ‘very scary’ incidents (rated as 3 on a 0–3 scale) are on average a weekly experience, with deliberate aggression experienced monthly. Per mile, non-injury incidents were more frequent for people making shorter and slower trips. People aged over 55 were at lower risk, as were those cycling at the weekend and outside the morning peak. Incidents that involved motor vehicles, especially those involving larger vehicles, were more frightening than those that did not. Near miss and other non-injury incidents are widespread in the UK and may have a substantial impact on cycling experience and uptake. Policy and research should initially target the most frightening types of incident, such as very close passes and incidents involving large vehicles. Further attention needs to be paid to the experiences of groups under-represented among cyclists, such as women making shorter trips.

LEARNING FROM NEAR MISSES IN MEDICATION ERRORS: A BAYESIAN APPROACH

Medical errors originating in health care facilities are a significant source of preventable morbidity, mortality, and healthcare costs. Voluntary error report systems that collect information on the causes and contributing factors of medi- cal errors regardless of the resulting harm may be useful for developing effective harm prevention strategies. Some patient safety experts question the utility of data from errors that did not lead to harm to the patient, also called near misses. A near miss (a.k.a. close call) is an unplanned event that did not result in injury to the patient. Only a fortunate break in the chain of events prevented injury. We use data from a large voluntary reporting system of 836,174 medication errors from 1999 to 2005 to provide evidence that the causes and contributing factors of errors that result in harm are similar to the causes and contributing factors of near misses. We develop Bayesian hierarchical models for estimating the log odds of selecting a given cause (or contributing factor) of error given harm has occurred and the log odds of selecting the same cause given that harm did not occur. The posterior distribution of the correlation between these two vectors of log-odds is used as a measure of the evidence supporting the use of data from near misses and their causes and contributing factors to prevent medical errors. In addition, we identify the causes and contributing factors that have the highest or lowest log-odds ratio of harm versus no harm. These causes and contributing factors should also be a focus in the design of prevention strategies. This paper provides important evidence on the utility of data from near misses, which constitute the vast majority of errors in our data.