996 resultados para incident management


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Texas Department of Transportation, Austin

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Research in safety management has been inhibited by lack of consensus as to the definitions of the terms with which it is concerned and, in general, the lack of an agreed theoretical framework within which to collate and contrast empirical findings. This thesis sets out definitions of key terms (hazard, risk, accident, incident and safety) and provides a theoretical framework. This framework has been informed by many sources but especially the Management Oversight and Risk Tree (MORT), cybernetics and the Viable System Model (VSM). Fieldwork designs are proposed for the empirical development of an analytical framework and its use to assist study of the development of safety management in organisations.

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Modern IT infrastructures are constructed by large scale computing systems and administered by IT service providers. Manually maintaining such large computing systems is costly and inefficient. Service providers often seek automatic or semi-automatic methodologies of detecting and resolving system issues to improve their service quality and efficiency. This dissertation investigates several data-driven approaches for assisting service providers in achieving this goal. The detailed problems studied by these approaches can be categorized into the three aspects in the service workflow: 1) preprocessing raw textual system logs to structural events; 2) refining monitoring configurations for eliminating false positives and false negatives; 3) improving the efficiency of system diagnosis on detected alerts. Solving these problems usually requires a huge amount of domain knowledge about the particular computing systems. The approaches investigated by this dissertation are developed based on event mining algorithms, which are able to automatically derive part of that knowledge from the historical system logs, events and tickets. ^ In particular, two textual clustering algorithms are developed for converting raw textual logs into system events. For refining the monitoring configuration, a rule based alert prediction algorithm is proposed for eliminating false alerts (false positives) without losing any real alert and a textual classification method is applied to identify the missing alerts (false negatives) from manual incident tickets. For system diagnosis, this dissertation presents an efficient algorithm for discovering the temporal dependencies between system events with corresponding time lags, which can help the administrators to determine the redundancies of deployed monitoring situations and dependencies of system components. To improve the efficiency of incident ticket resolving, several KNN-based algorithms that recommend relevant historical tickets with resolutions for incoming tickets are investigated. Finally, this dissertation offers a novel algorithm for searching similar textual event segments over large system logs that assists administrators to locate similar system behaviors in the logs. Extensive empirical evaluation on system logs, events and tickets from real IT infrastructures demonstrates the effectiveness and efficiency of the proposed approaches.^

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Acknowledgments The authors would like to thank the participants of the EPIC-Norfolk cohort. We thank the nutritionist team and data management team of the EPIC-Norfolk cohort. The EPIC-Norfolk study was supported by grants from the Medical Research Council and Cancer Research UK. Funders had no role in study design or interpretation of the findings.

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Acknowledgments The authors would like to thank the participants of the EPIC-Norfolk cohort. We thank the nutritionist team and data management team of the EPIC-Norfolk cohort. The EPIC-Norfolk study was supported by grants from the Medical Research Council and Cancer Research UK. Funders had no role in study design or interpretation of the findings.

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This paper describes an audit of prevention and management of violence and aggression care plans and incident reporting forms which aimed to: (i) report the compliance rate of completion of care plans; (ii) identify the extent to which patients contribute to and agree with their care plan; (iii) describe de-escalation methods documented in care plans; and (iv) ascertain the extent to which the de-escalation methods described in the care plan are recorded as having been attempted in the event of an incident. Care plans and incident report forms were examined for all patients in men's and women's mental health care pathways who were involved in aggressive incidents between May and October 2012. In total, 539 incidents were examined, involving 147 patients and 121 care plans. There was no care plan in place at the time of 151 incidents giving a compliance rate of 72%. It was documented that 40% of patients had contributed to their care plans. Thematic analysis of de-escalation methods documented in the care plans revealed five de-escalation themes: staff interventions, interactions, space/quiet, activities and patient strategies/skills. A sixth category, coercive strategies, was also documented. Evidence of adherence to de-escalation elements of the care plan was documented in 58% of incidents. The reasons for the low compliance rate and very low documentation of patient involvement need further investigation. The inclusion of coercive strategies within de-escalation documentation suggests that some staff fundamentally misunderstand de-escalation.

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Developments in information technology will drive the change in records management; however, it should be the health information managers who drive the information management change. The role of health information management will be challenged to use information technology to broker a range of requests for information from a variety of users, including he alth consumers. The purposes of this paper are to conceptualise the role of health information management in the context of a technologically driven and managed health care environment, and to demonstrat e how this framework has been used to review and develop the undergraduate program in health information management at the Queensland University of Technology.