scholarly journals Evaluation and improvement the safety of total marrow irradiation with helical tomotherapy using repeat failure mode and effects analysis

2019 ◽  
Vol 14 (1) ◽  
Author(s):  
Jiuling Shen ◽  
Xiaoyong Wang ◽  
Di Deng ◽  
Jian Gong ◽  
Kang Tan ◽  
...  
Keyword(s):  
High Risk ◽  
Failure Mode ◽  
Helical Tomotherapy ◽  
Specific Treatment ◽  
Treatment Interruption ◽  
Staff Members ◽  
Total Marrow Irradiation ◽  
Megavoltage Computed Tomography ◽  
Subsequent Calculation ◽  
Potential Failure

Abstract Background & purpose Helical tomotherapy has been applied to total marrow irradiation (HT-TMI). Our objective was to apply failure mode and effects analysis (FMEA) two times separated by 1 year to evaluate and improve the safety of HT-TMI. Materials and methods A multidisciplinary team was created. FMEA consists of 4 main steps: (1) Creation of a process map; (2) Identification of all potential failure mode (FM) in the process; (3) Evaluation of the occurrence (O), detectability (D) and severity of impact (S) of each FM according to a scoring criteria (1–10), with the subsequent calculation of the risk priority number (RPN=O*D*S) and (4) Identification of the feasible and effective quality control (QC) methods for the highest risks. A second FMEA was performed for the high-risk FMs based on the same risk analysis team in 1 year later. Results A total of 39 subprocesses and 122 FMs were derived. First time RPN ranged from 3 to 264.3. Twenty-five FMs were defined as being high-risk, with the top 5 FMs (first RPN/ second RPN): (1) treatment couch movement failure (264.3/102.8); (2) section plan dose junction error in delivery (236.7/110.4); (3) setup check by megavoltage computed tomography (MVCT) failure (216.8/94.6); (4) patient immobilization error (212.5/90.2) and (5) treatment interruption (204.8/134.2). A total of 20 staff members participated in the study. The second RPN value of the top 5 high-risk FMs were all decreased. Conclusion QC interventions were implemented based on the FMEA results. HT-TMI specific treatment couch tests; the arms immobilization methods and strategy of section plan dose junction in delivery were proved to be effective in the improvement of the safety.

scholarly journals Immune Sensing and Potential Immunotherapeutic Approaches to Control Chromoblastomycosis

2020 ◽  
Vol 7 (1) ◽  
pp. 3
Author(s):  
Leandro C. D. Breda ◽  
Isabela G. Menezes ◽  
Larissa N. M. Paulo ◽  
Sandro Rogério de Almeida
Keyword(s):  
Social Stigma ◽  
Treatment Strategies ◽  
Specific Treatment ◽  
Treatment Interruption ◽  
Lower Limbs ◽  
Disease Treatment ◽  
Immune Sensing ◽  
Skin Immunology ◽  
Anti Fungal ◽  
Made In

Chromoblastomycosis (CBM) is a neglected, chronic, and progressive subcutaneous mycosis caused by different species of fungi from the Herpotrichiellaceae family. CBM disease is usually associated with agricultural activities, and its infection is characterized by verrucous, erythematous papules, and atrophic lesions on the upper and lower limbs, leading to social stigma and impacts on patients’ welfare. The economic aspect of disease treatment is another relevant issue. There is no specific treatment for CBM, and different anti-fungal drug associations are used to treat the patients. However, the long period of the disease and the high cost of the treatment lead to treatment interruption and, consequently, relapse of the disease. In previous years, great progress had been made in the comprehension of the CBM pathophysiology. In this review, we discuss the differences in the cell wall composition of conidia, hyphae, and muriform cells, with a particular focus on the activation of the host immune response. We also highlight the importance of studies about the host skin immunology in CBM. Finally, we explore different immunotherapeutic studies, highlighting the importance of these approaches for future treatment strategies for CBM.

74 Improving Handover Between Doctors and Nurses on An Elderly Care Ward

2021 ◽  
Vol 50 (Supplement_1) ◽  
pp. i12-i42
Author(s):  
K Suseeharan ◽  
T Vedutla
Keyword(s):  
High Risk ◽  
Patient Care ◽  
Positive Impact ◽  
Elderly Care ◽  
Task Completion ◽  
Risk Area ◽  
High Risk Area ◽  
Staff Members ◽  
Care Ward ◽  
Doctors And Nurses

Abstract Background The Royal College of Physician guidelines (2011) identified handover as a “high risk step” in patient care, especially in recent times within the NHS where shift patterns lead to more disjointed care with a high reliance on effective handover by all staff members. Introduction At Cannock Chase hospital, Fairoak ward is an elderly care rehabilitation ward where there is a large multi-disciplinary team. While working on the ward as doctors we noticed that handover between the MDT was poor. Anecdotal evidence from both doctors and nurses felt that this was a high risk area in need of improvement. Aim to improve handover between doctors and nurses on this elderly care ward. Method To measure the quality of current handover practice we did a questionnaire. A total of 12 questionnaires were completed which showed that 92% of staff felt that handover on the ward was very poor and 50% preferred both written and verbal handover. We measured the number of tasks verbally handed over between doctors and nurses over 3 days. On average 65% of the tasks were completed. We then made the below interventions and re-audited to see if there was any improvement. Interventions over 3 week period: Results Questionnaire: Measuring task completion after interventions; Conclusion This project has made a positive change qualitatively and quantitatively to the ward handover practice. Staff satisfaction regarding handover has improved and the number of “handed over” tasks completed daily has significantly improved. The written handover sheet had poor utilisation by staff but in 4 months we are going to re-audit and trial the handover sheet again to further improve service delivery. We hope this improvement will have a positive impact on patient care on this elderly care ward.

scholarly journals Fast Megavoltage Computed Tomography: A Rapid Imaging Method for Total Body or Marrow Irradiation in Helical Tomotherapy

2016 ◽  
Vol 96 (3) ◽  
pp. 688-695 ◽  
Author(s):  
Taiki Magome ◽  
Akihiro Haga ◽  
Yutaka Takahashi ◽  
Keiichi Nakagawa ◽  
Kathryn E. Dusenbery ◽  
...  
Keyword(s):  
Computed Tomography ◽  
Helical Tomotherapy ◽  
Imaging Method ◽  
Rapid Imaging ◽  
Megavoltage Computed Tomography ◽  
Total Body

Complaint management model of manufacturing products using text mining and potential failure identification

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Ririn Diar Astanti ◽  
Ivana Carissa Sutanto ◽  
The Jin Ai
Keyword(s):  
Quality Management ◽  
Text Mining ◽  
Failure Mode ◽  
Management System ◽  
Main Part ◽  
Mining Method ◽  
Content Type ◽  
Complaint Management ◽  
Potential Failure ◽  
Failure Identification

PurposeThis paper aims to propose a framework on complaint management system for quality management by applying the text mining method and potential failure identification that can support organization learning (OL). Customer complaints in the form of email text is the input of the framework, while the most frequent complaints are visualized using a Pareto diagram. The company can learn from this Pareto diagram and take action to improve their process.Design/methodology/approachThe first main part of the framework is creating a defect database from potential failure identification, which is the initial part of the failure mode and effect analysis technique. The second main part is the text mining of customer email complaints. The last part of the framework is matching the result of text mining with the defect database and presenting in the form of a Pareto diagram. After the framework is proposed, a case study is conducted to illustrate the applicability of the proposed method.FindingsBy using the defect database, the framework can interpret the customer email complaints into the list of most defect complained by customer using a Pareto diagram. The results of the Pareto diagram, based on the results of text mining of consumer complaints via email, can be used by a company to learn from complaint and to analyze the potential failure mode. This analysis helps company to take anticipatory action for avoiding potential failure mode happening in the future.Originality/valueThe framework on complaint management system for quality management by applying the text mining method and potential failure identification is proposed for the first time in this paper.

Automatic Parotid Gland Segmentation in MVCT Using Deep Convolutional Neural Networks

2022 ◽  
Vol 3 (2) ◽  
pp. 1-15
Author(s):  
Junqian Zhang ◽  
Yingming Sun ◽  
Hongen Liao ◽  
Jian Zhu ◽  
Yuan Zhang
Keyword(s):  
Parotid Gland ◽  
Head And Neck ◽  
Helical Tomotherapy ◽  
Radiation Treatment ◽  
Automatic Segmentation ◽  
Parotid Glands ◽  
Deep Convolutional Neural Networks ◽  
Megavoltage Computed Tomography ◽  
Radiation Induced ◽  
Segmentation Models

Radiation-induced xerostomia, as a major problem in radiation treatment of the head and neck cancer, is mainly due to the overdose irradiation injury to the parotid glands. Helical Tomotherapy-based megavoltage computed tomography (MVCT) imaging during the Tomotherapy treatment can be applied to monitor the successive variations in the parotid glands. While manual segmentation is time consuming, laborious, and subjective, automatic segmentation is quite challenging due to the complicated anatomical environment of head and neck as well as noises in MVCT images. In this article, we propose a localization-refinement scheme to segment the parotid gland in MVCT. After data pre-processing we use mask region convolutional neural network (Mask R-CNN) in the localization stage after data pre-processing, and design a modified U-Net in the following fine segmentation stage. To the best of our knowledge, this study is a pioneering work of deep learning on MVCT segmentation. Comprehensive experiments based on different data distribution of head and neck MVCTs and different segmentation models have demonstrated the superiority of our approach in terms of accuracy, effectiveness, flexibility, and practicability. Our method can be adopted as a powerful tool for radiation-induced injury studies, where accurate organ segmentation is crucial.

scholarly journals Addressing Health Insurance Deductions through an Interventional Study: the Case of a Large Central Hospital

2016 ◽  
Vol 11 (2) ◽  
pp. 39-48
Author(s):  
Erfan Kharazmi ◽  
Asiyeh Salehi ◽  
Neda Hashemi ◽  
Shekufe Ghaderi ◽  
Nahid Hatam
Keyword(s):  
Healthcare Provider ◽  
Failure Mode ◽  
Armed Forces ◽  
Healthcare Services ◽  
Intervention Programs ◽  
Medical Services ◽  
Mode Effects ◽  
The Social ◽  
Potential Failure ◽  
Efficiency And Productivity

Objective: A large proportion of hospitals’ private income is provided by insurance organisations. Hospitals in Iran face various problems in terms of insurance deductions from insurance organisations resulting from inefficient performance by both the hospitals and the insurers. These problems necessitate more specific cost control in this area. This research assesses the causes of insurance deductions by using the Failure Mode Effects Analysis (FMEA) technique, and addresses the issues resulting in deductions by providing some interventions through the Pareto technique. Design: The 10-step pattern of FMEA was implemented for assessing the main causes of insurance deduction in this study. Setting: Data was collected from deduced amounts by three main/largest contracting party insurance organisations (e.g. the Social Security Insurance Organisation, Medical Services Insurance Organisation and Armed Forces Medical Services Insurance Organisation of Namazi Hospital, a large healthcare provider in the South of Iran, in 2014. Findings: Sixty-five potential failure causes were identified, of which 26 were related to the anaesthesia unit, 23 were related to the surgery room unit and 16 were related to the hospitalisation unit. Deductions in the anaesthesia and hospitalisation units and the surgery room were reduced after intervention programs by 14.42%, 57.76%, and 51.52%, respectively. Conclusions: Using the FMEA technique in a large healthcare provider in Iran resulted in identifying the main causes of insurance deductions and provided intervention programs in order to increase the efficiency and productivity of healthcare services. Abbreviations: FMEA – Failure Mode Effects Analysis; RPN – Risk Priority Number.

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