scholarly journals Patterns Contributing to Severe Complications After Liver Resection: An Aggregate Root Cause Analysis of a Prospective Cohort

2020 ◽  
Author(s):  
Kholoud Houssaini ◽  
Oumayma Lahnaoui ◽  
Amine Souadka ◽  
Mohamed-Anass Majbar ◽  
Abdelilah Ghannam ◽  
...  
Keyword(s):  
Liver Resection ◽  
Root Cause Analysis ◽  
Team Work ◽  
Cause Analysis ◽  
Resource Limitations ◽  
Root Cause ◽  
Contributory Factors ◽  
Liver Resections ◽  
Safety Interventions ◽  
Individual Participant

Abstract Background The Aggregate Root Cause Analysis (AggRCA) was designed to improve the understanding of system vulnerabilities contributing to patient harm, including surgical complications. It remains poorly used due to methodological complexity and resource limitations. This study aimed to identify the main patterns contributing to severe complications after liver resection (SC) using an AggRCA. Methods This was a retrospective qualitative study aimed to identify the main patterns contributing to severe complications (SC). All consecutive SC (Clavien-Dindo > 3a within the first 90 days after liver resection) that occurred between January 1st, 2018 and December 31st, 2019 were identified from a prospective electronic database and included in an AggRCA. This included a structured MMR (Morbidity and Mortality Review) reporting tool based on 50 contributory factors adapted from 6 ALARM categories: “Patient”, “Tasks”, “Individual staff”, “Team”, “Work environment”, and “Management and Institutional context”. Data resulting from individual-participant RCA of single-cases were validated collectively then aggregated. The main patterns were suggested from the contributory factors reported in more than half of the cases. Results Among 105 consecutive liver resections, 15 cases (14.3%) including 5 deaths (4.8%) met the inclusion criteria. AggRCA resulted in the identification of 36 contributory factors. Eight contributory factors were reported in more than half of the cases and were compiled in three entangled patterns: (1) Disrupted perioperative process, (2) Unplanned intraoperative change, (3) Ineffective communication. Conclusion A pragmatic aggregated RCA process improved our understanding of system vulnerabilities based on the analysis of a limited number of events and a reasonable resource intensity. The identification of patterns contributing to SC lay the rationale of future contextualized safety interventions beyond the scope of liver resections.

scholarly journals Contributing factors to severe complications after liver resection: an aggregate root cause analysis in 105 consecutive patients.

2020 ◽  
Author(s):  
Kholoud Houssaini ◽  
Oumayma Lahnaoui ◽  
Amine Souadka ◽  
Mohamed-Anass Majbar ◽  
Abdelilah Ghannam ◽  
...  
Keyword(s):  
Liver Resection ◽  
Root Cause Analysis ◽  
Team Work ◽  
Contributing Factors ◽  
Cause Analysis ◽  
Resource Limitations ◽  
Root Cause ◽  
Contributory Factors ◽  
Safety Interventions ◽  
Individual Participant

Abstract Background: The aggregate root cause analysis (AggRCA) was designed to improve the understanding of system vulnerabilities contributing to patient harm, including surgical complications. It remains poorly used due to methodological complexity and resource limitations. This study aimed to identify the main patterns contributing to severe complications after liver resection using an AggRCA.Methods: This was a retrospective qualitative study aimed to identify the main patterns contributing to severe complications, defined as strictly higher than grade IIIa according to the Clavien-Dindo classification within the first 90 days after liver resection. All consecutive severe complications that occurred between January 1st, 2018 and December 31st, 2019 were identified from an electronic database and included in an AggRCA. This included a structured morbidity and mortality review (MMR) reporting tool based on 50 contributory factors adapted from 6 ALARM categories: “Patient”, “Tasks”, “Individual staff”, “Team”, “Work environment”, and “Management and Institutional context”. Data resulting from individual-participant root cause analysis (RCA) of single-cases were validated collectively then aggregated. The main patterns were suggested from the contributory factors reported in more than half of the cases.Results: In 105 consecutive liver resection cases, 15 patients (14.3%) developed severe postoperative complications, including 5 (4.8%) who died. AggRCA resulted in the identification of 36 contributory factors. Eight contributory factors were reported in more than half of the cases and were compiled in three entangled patterns: (1) Disrupted perioperative process, (2) Unplanned intraoperative change, (3) Ineffective communication.Conclusion: A pragmatic aggregated RCA process improved our understanding of system vulnerabilities based on the analysis of a limited number of events and a reasonable resource intensity. The identification of patterns contributing to severe complications lay the rationale of future contextualized safety interventions beyond the scope of liver resections.

scholarly journals Contributing factors to severe complications after liver resection: an aggregate root cause analysis in 105 consecutive patients

2020 ◽  
Vol 14 (1) ◽  
Author(s):  
Kholoud Houssaini ◽  
Oumayma Lahnaoui ◽  
Amine Souadka ◽  
Mohammed Anass Majbar ◽  
Abdelilah Ghannam ◽  
...  
Keyword(s):  
Liver Resection ◽  
Root Cause Analysis ◽  
Team Work ◽  
Contributing Factors ◽  
Cause Analysis ◽  
Resource Limitations ◽  
Root Cause ◽  
Contributory Factors ◽  
Safety Interventions ◽  
Individual Participant

Abstract Background The aggregate root cause analysis (AggRCA) was designed to improve the understanding of system vulnerabilities contributing to patient harm, including surgical complications. It remains poorly used due to methodological complexity and resource limitations. This study aimed to identify the main patterns contributing to severe complications after liver resection using an AggRCA. Methods This was a retrospective qualitative study aimed to identify the main patterns contributing to severe complications, defined as strictly higher than grade IIIa according to the Clavien-Dindo classification within the first 90 days after liver resection. All consecutive severe complications that occurred between January 1st, 2018 and December 31st, 2019 were identified from an electronic database and included in an AggRCA. This included a structured morbidity and mortality review (MMR) reporting tool based on 50 contributory factors adapted from 6 ALARM categories: “Patient”, “Tasks”, “Individual staff”, “Team”, “Work environment”, and “Management and Institutional context”. Data resulting from individual-participant root cause analysis (RCA) of single-cases were validated collectively then aggregated. The main patterns were suggested from the contributory factors reported in more than half of the cases. Results In 105 consecutive liver resection cases, 15 patients (14.3%) developed severe postoperative complications, including 5 (4.8%) who died. AggRCA resulted in the identification of 36 contributory factors. Eight contributory factors were reported in more than half of the cases and were compiled in three entangled patterns: (1) Disrupted perioperative process, (2) Unplanned intraoperative change, (3) Ineffective communication. Conclusion A pragmatic aggregated RCA process improved our understanding of system vulnerabilities based on the analysis of a limited number of events and a reasonable resource intensity. The identification of patterns contributing to severe complications lay the rationale of future contextualized safety interventions beyond the scope of liver resections.

scholarly journals Correction to: Contributing factors to severe complications after liver resection: an aggregate root cause analysis in 105 consecutive patients

2020 ◽  
Vol 14 (1) ◽  
Author(s):  
Kholoud Houssaini ◽  
Oumayma Lahnaoui ◽  
Amine Souadka ◽  
Mohammed Anass Majbar ◽  
Abdelilah Ghannam ◽  
...  
Keyword(s):  
Liver Resection ◽  
Root Cause Analysis ◽  
Contributing Factors ◽  
Cause Analysis ◽  
Root Cause

An amendment to this paper has been published and can be accessed via the original article.

Root Cause analysis of SG tube ODSCC indications within the tube sheets of NPP biblis unit A

2011 ◽  
pp. 78-86
Author(s):  
R. Kilian ◽  
J. Beck ◽  
H. Lang ◽  
V. Schneider ◽  
T. Schönherr ◽  
...  
Keyword(s):  
Root Cause Analysis ◽  
Cause Analysis ◽  
Root Cause

Rule Construction and its Execution for Root Cause Analysis

2012 ◽  
Vol 132 (10) ◽  
pp. 1689-1697
Author(s):  
Yutaka Kudo ◽  
Tomohiro Morimura ◽  
Kiminori Sugauchi ◽  
Tetsuya Masuishi ◽  
Norihisa Komoda
Keyword(s):  
Root Cause Analysis ◽  
Cause Analysis ◽  
Root Cause

Root Cause Analysis Techniques Using Picosecond Time Resolved LADA

2014 ◽  
Author(s):  
Dan Bodoh ◽  
Kent Erington ◽  
Kris Dickson ◽  
George Lange ◽  
Carey Wu ◽  
...  
Keyword(s):  
Integrated Circuits ◽  
Picosecond Laser ◽  
Root Cause Analysis ◽  
Fault Isolation ◽  
Time Resolved ◽  
Cause Analysis ◽  
Root Cause ◽  
Design And Manufacturing ◽  
Multiple Interactions ◽  
Established Technique

Abstract Laser-assisted device alteration (LADA) is an established technique used to identify critical speed paths in integrated circuits. LADA can reveal the physical location of a speed path, but not the timing of the speed path. This paper describes the root cause analysis benefits of 1064nm time resolved LADA (TR-LADA) with a picosecond laser. It shows several examples of how picosecond TR-LADA has complemented the existing fault isolation toolset and has allowed for quicker resolution of design and manufacturing issues. The paper explains how TR-LADA increases the LADA localization resolution by eliminating the well interaction, provides the timing of the event detected by LADA, indicates the propagation direction of the critical signals detected by LADA, allows the analyst to infer the logic values of the critical signals, and separates multiple interactions occurring at the same site for better understanding of the critical signals.

Root Cause Analysis for Pin Leakage

2016 ◽  
Author(s):  
Zhigang Song ◽  
Jochonia Nxumalo ◽  
Manuel Villalobos ◽  
Sweta Pendyala
Keyword(s):  
Failure Analysis ◽  
Root Cause Analysis ◽  
Advanced Technology ◽  
Process Step ◽  
Cause Analysis ◽  
Hard Mask ◽  
Technology Node ◽  
Root Cause ◽  
Tools And Techniques

Abstract Pin leakage continues to be on the list of top yield detractors for microelectronics devices. It is simply manifested as elevated current with one pin or several pins during pin continuity test. Although many techniques are capable to globally localize the fault of pin leakage, root cause analysis and identification for it are still very challenging with today’s advanced failure analysis tools and techniques. It is because pin leakage can be caused by any type of defect, at any layer in the device and at any process step. This paper presents a case study to demonstrate how to combine multiple techniques to accurately identify the root cause of a pin leakage issue for a device manufactured using advanced technology node. The root cause was identified as under-etch issue during P+ implantation hard mask opening for ESD protection diode, causing P+ implantation missing, which was responsible for the nearly ohmic type pin leakage.

Sign in / Sign up

Export Citation Format

Share Document