دانلود و نمایش مقالات مرتبط با Triage::صفحه 1
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نتیجه جستجو - Triage

تعداد مقالات یافته شده: 12
ردیف عنوان نوع
1 Clinical Decision Support Systems for Triage in the Emergency Department using Intelligent Systems: a Review
سیستم های پشتیبانی از تصمیم گیری بالینی برای آزمایش در بخش اورژانس با استفاده از سیستم های هوشمند: یک مرور-2020
Motivation: Emergency Departments’ (ED) modern triage systems implemented worldwide are solely based upon medical knowledge and experience. This is a limitation of these systems, since there might be hidden patterns that can be explored in big volumes of clinical historical data. Intelligent techniques can be applied to these data to develop clinical decision support systems (CDSS) thereby providing the health professionals with objective criteria. Therefore, it is of foremost importance to identify what has been hampering the application of such systems for ED triage. Objectives: The objective of this paper is to assess how intelligent CDSS for triage have been contributing to the improvement of quality of care in the ED as well as to identify the challenges they have been facing regarding implementation. Methods: We applied a standard scoping review method with the manual search of 6 digital libraries, namely: ScienceDirect, IEEE Xplore, Google Scholar, Springer, MedlinePlus and Web of Knowledge. Search queries were created and customized for each digital library in order to acquire the information. The core search consisted of searching in the papers’ title, abstract and key words for the topics “triage”, “emergency department”/“emergency room” and concepts within the field of intelligent systems. Results: From the review search, we found that logistic regression was the most frequently used technique for model design and the area under the receiver operating curve (AUC) the most frequently used performance measure. Beside triage priority, the most frequently used variables for modelling were patients’ age, gender, vital signs and chief complaints. The main contributions of the selected papers consisted in the improvement of a patients prioritization, prediction of need for critical care, hospital or Intensive Care Unit (ICU) admission, ED Length of Stay (LOS) and mortality from information available at the triage. Conclusions: In the papers where CDSS were validated in the ED, the authors found that there was an improvement in the health professionals’ decision-making thereby leading to better clinical management and patients’ outcomes. However, we found that more than half of the studies lacked this implementation phase. We concluded that for these studies, it is necessary to validate the CDSS and to define key performance measures in order to demonstrate the extent to which incorporation of CDSS at triage can actually improve care.
Keywords: Triage | CDSS | EHR | Machine learning | Critical care
مقاله انگلیسی
2 The challenge of identifying historic ‘private browsing’ sessions on suspect devices
چالش شناسایی تاریخی "مرور خصوصی" جلسات در دستگاه های مشکوک-2020
Those subject to supervision orders requiring the lawful regulation of their Internet activity provide an investigatory challenge to law enforcement practitioners. Where a defendants Internet history must be retained and made accessible for review at defined intervals, investigators must apply principles of digital triage to quickly evaluate existing content in order to identify any potential breaching activity. Such processes are often undertaken ‘on-scene’ and under time constraints. Whilst in some cases detecting offending actions may be simple, particularly if illegal history records are retained, it may be the case that some techniques such as private browsing functions leave minimal trace of usage postevent. As a result, live monitoring and activity capture may provide the only viable solution with regards to the effective regulation of Internet usage for those under supervision. This work examines the use of AppLocker and a bespoke developed solution ‘Private-Spy’ for the purpose of private browsing session detection. Both solutions are evaluated and findings are offered.
Keywords: Digital forensics | Private browsing | Internet | Criminal investigation | Monitoring
مقاله انگلیسی
3 Judging health care priority in emergency situations: Patient facial appearance matters
قضاوت در مورد اولویت مراقبت های بهداشتی در مواقع اضطراری: ظاهر چهره بیمار اهمیت دارد-2020
Rationale: Extensive research has shown that implicit trait inferences from facial appearance can bias everyday life in a pervasive way, influencing our decisions in different social contexts such as mate choice, political vote and criminal sentence. In situations characterized by time pressure and scant information, decisions based on inferences from facial appearance may have particularly critical and serious consequences, such as in emergency healthcare. No studies today have investigated this aspect in an actual emergency. Objective: The aim of the present study was to go beyond this gap and to determine whether implicit inferences from patients’ facial appearance could be predictive of disparities in clinical evaluations and priority of treatment. Methods: In total, 183 cases of patients were evaluated by independent judges at zero acquaintance on the basis of different implicit facial appearance-based inferences, including trustworthiness and distress. Color-based priority code (White, Green, or Yellow) attributed by the triage nurse at the end of the registration process were recorded. Results: Our results showed that more trustworthy- and distressed- looking patients faces have been associated with a higher priority code. Conclusions: The present study shows that specific facial appearance-based inferences influence the attribution of priority code in healthcare that require quick decisions based on scarce clinical information such as in emergency. These results suggest the importance to bring to the attention of the healthcare professionals’ the possibility of being victims of implicit inferences, and prompt to design educational interventions capable to increase their awareness of this bias in clinical evaluation.
Keywords: Face perception | Facial appearance | First impression | Implicit bias | Healthcare | Emergency | Social cognition
مقاله انگلیسی
4 Setting up standards: A methodological proposal for pediatric Triage machine learning model construction based on clinical outcomes
تنظیم استانداردها: یک پیشنهاد روش شناختی برای ساخت مدل یادگیری ماشین تراشی کودکان براساس نتایج بالینی-2019
Triage is a critical process in hospital emergency departments (ED). Specifically, we consider how to achieve fast and accurate patient Triage in the ED of a pediatric hospital. The goal of this paper is to establish methodological best practices for the application of machine learning (ML) to Triage in pediatric ED, providing a comprehensive comparison of the performance of ML techniques over a large dataset. Our work is among the first attempts in this direction. Following very recent works in the literature, we use the clinical outcome of a case as its label for supervised ML model training, instead of the more uncertain labels provided by experts. The experimental dataset contains the records along 3 years of operation of the hospital ED. It consists of 189,718 patients visits to the hospital. The clinical outcome of 9271 cases (4.98%) wa hospital admission, therefore our dataset is highly class imbalanced. Our reported performance comparison results focus on four ML models: Deep Learning (DL), Random Forest (RF), Naive Bayes (NB) and Support Vector Machines (SVM). Data preprocessing includes class imbalance correction, and case re-labeling. We use different well known metrics to evaluate performance of ML models in three different experimental settings: (a) classification of each case into the standard five Triage urgency levels, (b) discrimination of high versus low case severity according to its clinical outcome, and (c) comparison of the number of patients assigned to each standard Triage urgency level against the Triage rule based expert system currently in use at the hospital. RF achieved greater AUC, accuracy, PPV and specificity than the other models in the dychotomic classification experiments. On the implementation side, our study shows that ML predictive models trained according to clinical outcomes, provide better Triage performance than the current rule based expert system in operation at the hospital.
Keywords: Machine learning | Emergency department | Triage | Data science | Clinical decision support systems
مقاله انگلیسی
5 Setting up standards: A methodological proposal for pediatric Triage machine learning model construction based on clinical outcomes
تنظیم استانداردها: یک پیشنهاد روش شناختی برای ساخت مدل یادگیری ماشین تراشی کودکان براساس نتایج بالینی-2019
Triage is a critical process in hospital emergency departments (ED). Specifically, we consider how to achieve fast and accurate patient Triage in the ED of a pediatric hospital. The goal of this paper is to establish methodological best practices for the application of machine learning (ML) to Triage in pediatric ED, providing a comprehensive comparison of the performance of ML techniques over a large dataset. Our work is among the first attempts in this direction. Following very recent works in the literature, we use the clinical outcome of a case as its label for supervised ML model training, instead of the more uncertain labels provided by experts. The experimental dataset contains the records along 3 years of operation of the hospital ED. It consists of 189,718 patients visits to the hospital. The clinical outcome of 9271 cases (4.98%) wa hospital admission, therefore our dataset is highly class imbalanced. Our reported performance comparison results focus on four ML models: Deep Learning (DL), Random Forest (RF), Naive Bayes (NB) and Support Vector Machines (SVM). Data preprocessing includes class imbalance correction, and case re-labeling. We use different well known metrics to evaluate performance of ML models in three different experimental settings: (a) classification of each case into the standard five Triage urgency levels, (b) discrimination of high versus low case severity according to its clinical outcome, and (c) comparison of the number of patients assigned to each standard Triage urgency level against the Triage rule based expert system currently in use at the hospital. RF achieved greater AUC, accuracy, PPV and specificity than the other models in the dychotomic classification experiments. On the implementation side, our study shows that ML predictive models trained according to clinical outcomes, provide better Triage performance than the current rule based expert system in operation at the hospital.
Keywords: Machine learning | Emergency department | Triage | Data science | Clinical decision support systems
مقاله انگلیسی
6 Discovering role interaction models in the Emergency Room using Process Mining
کشف مدل های تعامل نقش در اتاق اورژانس با استفاده از فرآیند کاوی-2018
A coordinated collaboration among different healthcare professionals in Emergency Room (ER) processes is critical to promptly care for patients who arrive at the hospital in a delicate health condition, claiming for an immediate attention. The aims of this study are (i) to discover role interaction models in (ER) processes using process mining techniques; (ii) to understand how healthcare professionals are currently collaborating; and (iii) to provide useful knowledge that can help to improve ER processes. Methods: A four step method based on process mining techniques is proposed. An ER process of a university hospital was considered as a case study, using 7160 episodes that contains specific ER episode attributes. Results: Insights about how healthcare professionals collaborate in the ER was discovered, including the identification of a prevalent role interaction model along the major triage categories and specific role interaction models for different diagnoses. Also, common and exceptional professional interaction models were discovered at the role level. Conclusions: This study allows the discovery of role interaction models through the use of real-life clinical data and process mining techniques. Results show a useful way of providing relevant insights about how healthcare professionals collaborate, uncovering opportunities for process improvement.
Keywords: Healthcare ، Processes ، Process mining ، Case studies ، Organizational mining ، Organizational team patterns
مقاله انگلیسی
7 The industrial control system cyber defence triage process
سیستم های کنترل صنعتی فرآیند تریاژ دفاع سایبری-2017
The threat to Industrial Control Systems (ICS) from cyber attacks is widely acknowledged by governments and literature. Operators of ICS are looking to address these threats in an effective and cost-sensitive manner that does not expose their operations to additional risks through invasive testing.Whilst existing standards and guidelines offer comprehensive advice for reviewing the security of ICS infrastructure, resource and time limitations can lead to incomplete assessments or undesirably long countermeasure implementation schedules. In this paper we consider the problem of undertaking efficient cyber security risk as sessments and implementing mitigations in large, established ICS operations for which a full security review cannot be implemented on a constrained timescale. The contribution is the Industrial Control System Cyber Defence Triage Process (ICS-CDTP). ICS-CDTP deter mines areas of priority where the impact of attacks is greatest, and where initial investment reduces the organisation’s overall exposure swiftly. ICS-CDTP is designed to be a precursor to a wider, holistic review across the operation following established security manage ment approaches. ICS-CDTP is a novel combination of the Diamond Model of Intrusion Analysis, the Mandiant Attack Lifecycle, and the CARVER Matrix, allowing for an effective triage of attack vectors and likely targets for a capable antagonist. ICS-CDTP identifies and focuses on key ICS processes and their exposure to cyber threats with the view to main tain critical operations. The article defines ICS-CDTP and exemplifies its application using a fictitious water treatment facility, and explains its evaluation as part of a large-scale serious game exercise.
Keywords: ICS | SCADA | Cyber | Security | Triage | Risk
مقاله انگلیسی
8 Digital forensics: Understanding the development of criminal law in England and Wales on images depicting child sexual abuse
پزشکی قانونی دیجیتال: درک توسعه حقوق کیفری در انگلستان و ولز بر روی تصاویر سوء استفاده جنسی از کودکان-2016
In 2015, offences surrounding the possession, distributing, creation and publication of images depicting child sexual abuse (IDCSA) are prevalent. As a result, it is well publicised that law enforcement and associated digital forensic organisations are incurring substantial case backlogs in this area. As more investigations of this type are faced, it is becoming increasingly essential for practitioners to maintain an understanding of current legislative developments, as a digital forensic investigation of suspected offences surrounding IDCSA does not just involve the blanket recovery of all digital imagery on a device. Governed by this complex area of law, practitioners must appreciate the intricacies of these offences, ensuring any examination policies are correctly defined whilst recovering information that will support criminal justice processes. In addition, as triage strategies are increasingly employed in an effort to speed up investigations, it is crucial to recognise the types of evidence that are of use to a prosecuting authority in order to ensure these examination techniques are both efficient and effective. This paper offers a comprehensive analysis of legislative developments for offences surrounding IDCSA in the United Kingdom, bringing together the disciplines of law and digital forensics. Evidence of value to a prosecution for these offences is also considered taking into account existing case law precedents in line with contentious areas including the Internet cache and unallocated clusters.
Keywords: Digital forensics | Images depicting child sexual abuse | Legislation | Law
مقاله انگلیسی
9 A cross-sectional study of the clinical characteristics of cancer patients presenting to one tertiary referral emergency department
یک مطالعه به صورت مقطعی از ویژگی های بالینی بیماران مبتلا به سرطان مراجعه کننده که یک سوم به بخش اورژانس ارجاع داده می شوند-2016
Introduction: There is increasing evidence of cancer patients presenting to emergency departments (ED). The study aim was to analyse the characteristics of adult cancer patients presenting to one ED. Understanding cancer patient presentations could assist in the development of new models of care.
Methods: A 12 month retrospective audit was conducted of a random sample of cancer patients. Demographics and characteristic variables were analysed using descriptive, comparative and correlational statistics.
Results: The presentation rate for adult cancer patients was 1110 (2.4%) with 290 sampled. The common symptoms were fever (n = 54: 18.6%), abdominal pain (n = 34: 11.7%), and shortness of breath (n = 32: 11%). The majority of patients were allocated a Triage Category 2 (n = 94: 32.4%) or Triage Category 3 (n = 131: 45.2%). The majority of patients presented between 2 and 15 times. For patients administered antibiotics the average time was 119.8 minutes (SD ± 85.5). The average ED length of stay was mean 8.08 hours with 271 patients (93.4%) admitted to the hospital. Of the 290 patients, 105 (36.2%) had died within 12 months of ED presentation.
Conclusion: The study has shown that while cancer patients are only a small percentage of ED presentations the vast majority are allocated high triage codes, have high admission rates and high mortality rates.
Keywords: Cancer | Oncology | Haematology | Emergency | Time to antibiotic | Chemotherapy | Radiation
مقاله انگلیسی
10 آموزش حرفه ای در مراقبت های اولیه سالمندان: یک مطالعه مقدماتی
سال انتشار: 2013 - تعداد صفحات فایل pdf انگلیسی: 7 - تعداد صفحات فایل doc فارسی: 16
پیش زمینه: سیستم مراقبت سلامتی هلند با چالش های بزرگی در رابطه با تقاضا در مراقبت از سالمندان و مهارت های مورد نیاز پرستاران و پزشکان برای مواجه با این تقاضا روبرو میباشد . در حال حاضر، تمرکز اصلی مراقبت های بهداشتی در هلند بر بیماری و درمان است . با این حال، سالمندان ( افراد ناتوان و ضعیف ) نیاز به مواقبت وحمایتی دارند تا وظایف روزانه و رفاهشان را در نظر گیرد . بنابراین، متخصصین مراقبت های بهداشتی ، به ویژه کسانی که در مراقبت های اولیه نظیر: پزشکان و پرستاران عمومی تخصص دارند ، با یک تغییر الگو در اهمیت درمان بیماری به ترویج سلامت ( پیری سالم ) به چالش کشیده میشوند . برای تشخیص این تغییر در رفتار حرفه ای نیاز به تحصیلات تخصصی می باشد. شواهد نشان می دهد که تحصیلات حرفه ای ( IPE ) می تواند نقش مهمی را در ارتقای صلاحیت های حرفه ای به منظور ارائه مراقبت های سالمندان ایفا کند که به طور موثری ، یکپارچه و هماهنگ میباشد . با این حال ، IPE به ندرت در مراقبت های اولیه هلند مورد استفاده قرار میگرد . بنابراین، هدف این مطالعه مقدماتی ، توسعه یک برنامه IPE برای پزشکان عمومی و پرستاران قراردادی و ارزیابی احتمال یک برنامه IPE برای حرفه ای ها با زمینه های مختلف آموزشی و تاثیر آن بر تقسیم وظایف و مسئولیت های حرفه ای است . روش ها : ده پزشک عمومی و ده پرستار قراردادی از هشت شیوه مراقبتی در دو استان در شمال هلند، گرونینگن و درنته ( کل جمعیت 1.1 میلیون نفر( در برنامه مقدماتی IPE شرکت کردند . یک طرح از روش های مختلط که شامل روش های کمی و کیفی است برای ارزیابی برنامه IPE مورد استفاده قرار گرفت . نتایج : در طول برنامه ، وظایف و مسئولیت ها ، خصوصا، آن هایی که مرتبط با طرح مراقبتی هستند ، از پزشکان عمومی به پرستاران قراردادی تغییر یافت. نگرش شرکت کنندگان نسبت به افراد مسن ( مراقبت از آنها ) تغییر یافت و ابزار قراردادیی برای تنظیمات ضروری افراد مسن و بحث در مورد کاربرد داروهایشان ، به عنوان ارزش افزوده به توسعه طرح مراقبت در نظر گرفته شد . نتیجه گیری : نتایج این مطالعه مقدماتی نشان می دهد که یک برنامه آموزش حرفه ای برای حرفه ای ها با پیش زمینه های مختلف آموزشی ( پزشکان عمومی و پرستاران قراردادی ) امکان پذیر است و دارای ارزش افزوده در تعریف جدید وظایف و مسئولیت ها در میان پزشکان عمومی و پرستاران قراردادی است .
کلمات کلیدی: حرفه ای | آموزش | مراقبت های اولیه | پزشک | پرستاری
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