2020
DOI: 10.21203/rs.3.rs-42879/v2
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Contributing factors to severe complications after liver resection: an aggregate root cause analysis in 105 consecutive patients.

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… Show more

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Cited by 2 publications
(3 citation statements)
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References 22 publications
(30 reference statements)
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“…This unusual complication was discussed in our weekly morbidity and mortality review (MMR). We used a root cause analysis [10] based on the ALARM framework [11] transcripted to an Ishikawa diagram, to identify the contributing factors resulting in this complication.…”
Section: Case Presentationmentioning
confidence: 99%
See 1 more Smart Citation
“…This unusual complication was discussed in our weekly morbidity and mortality review (MMR). We used a root cause analysis [10] based on the ALARM framework [11] transcripted to an Ishikawa diagram, to identify the contributing factors resulting in this complication.…”
Section: Case Presentationmentioning
confidence: 99%
“…We have established in our department a weekly procedure of MMR to examine all cases of severe complications occurring within 90 postoperative day [9] . A root cause analysis [10] is performed based on the ALARM framework from the French High Authority of Health (HAS) [11] , to analyze contributing factors and suggest measures of improvement in order to prevent or detect this lethal situation.…”
Section: Introductionmentioning
confidence: 99%
“…16 30 A second shortcoming of current SAE investigations is that hospitals typically focus on single events within their own organisation, 13 14 even though attempts to learn from aggregate analysis of multiple events across hospitals, as already performed in Australia 37 and the USA, 38 39 are believed to improve learning. [38][39][40][41] It helps to discover combinations of recurring, underlying, patterns of causes and contributing factors 42 and may improve the formulation of more effective, system-aimed recommendations. 14 38 However, methods for analysing SAEs vary substantially, 10 which complicates aggregate crosshospitals analysis of SAEs.…”
Section: Introductionmentioning
confidence: 99%