scholarly journals Peer Teaching with Root Cause Analysis Method in Increasing Obedience Reporting of Patient Safety Incident

Author(s):  
Harlina Putri Rusiana ◽  
Tri Kurniati ◽  
Abdul Aziz Alimul Hidayat
Radiographics ◽  
2020 ◽  
Vol 40 (5) ◽  
pp. 1434-1440
Author(s):  
Ashley S. Rosier ◽  
Laura C. Tibor ◽  
Mara A. Turner ◽  
Carrie J. Phillips ◽  
A. Nicholas Kurup

Author(s):  
Sang-Min Park ◽  
Young-Gab Kim ◽  
Doo-Kwon Baik

Feature-level sentiment analysis can retrieve the sentimental preferences for the features of products but cannot retrieve the causes of the preferences. Previous sentiment analysis methods used sentiment words to calculate the sentiment polarity for specific features but could not utilize neutral sentiment words, even when they constituted a large proportion of the sentiment words. Fault diagnosis can extract causes and determine the root cause by using factual information and the cause-effect relation, but is not used for sentiment data. For the retrieval of sentiment root causes, we propose a sentiment root cause analysis method for user preferences. We consider sentiment relations based on fuzzy formal concept analysis (FFCA) to extend hierarchical feature-level sentiment analysis. A hierarchical relation of neutral sentiment words and explicit causal relation based on causal conjunctions is utilized to retrieve the cross features of root causes. A sentiment root cause is determined from the extracted causes to explain the preference of a sentiment expression by using a fuzzy cognitive map with a relations method. We demonstrate a factual ontology and sentiment ontology based on a feature ontology for clothing products. We evaluated the proposed sentiment root cause analysis method and verified that it is improved as compared with term frequency-based methods and sentiment score analysis.


2010 ◽  
Vol 2010 ◽  
pp. 1-5 ◽  
Author(s):  
Subramanian Vaidyanathan ◽  
Bakul M. Soni ◽  
Peter L. Hughes ◽  
Gurpreet Singh ◽  
Tun Oo

Never Events are serious, largely preventable patient safety incidents that should not occur if the available preventative measures have been implemented. We propose that a list of “Never Events” is created for spinal cord injury patients in order to improve the quality of care. To begin with, following two preventable complications related to management of neuropathic bladder may be included in this list of “Never Events.” (i) Severe ventral erosion of glans penis and penile shaft caused by indwelling urethral catheter; (ii) incorrect placement of a Foley catheter leading to inflation of Foley balloon in urethra. If a Never Event occurs, health professionals should report the incident through hospital risk management system to National Patient Safety Agency's Reporting and Learning System, communicate with the patient, family, and their carer as soon as possible about the incident, undertake a comprehensive root cause analysis of what went wrong, how, and why, and implement the changes that have been identified and agreed following the root cause analysis.


Author(s):  
Annamária Koncz ◽  
László Pokorádi ◽  
Zsolt Csaba Johanyák

The automotive industry is one of the most dynamically growing fields of the manufacturingarea. Besides this, it has very strict rules concerning safety and reliability. In our work, our aim is to point out the importance of the automotive industry (based on statistics) and the rules in connection with risk and root cause analysis. The most important risk analysis method is the Failure Mode and Effect Analysis (FMEA). According to standards and OEM regulations, FMEA is obligatory in the automotive sector. In our study, we summarise the area of FMEA usage, its types and process steps.


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