Evidence map›Paper›PMID 26032826›Full record

Observational studySurgery2015

Surgical never events and contributing human factors.

Cornelius A Thiels, Tarun Mohan Lal, Joseph M Nienow, Kalyan S Pasupathy, Renaldo C Blocker, Johnathon M Aho, Timothy I Morgenthaler, Robert R Cima, Susan Hallbeck, Juliane Bingener

Abstract readObservational Study
In one paragraph

Observational study in Surgery, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 34 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
34citing papers in PubMed, 2 pooled it
12.3field-weighted citation impact, top 1% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

34 citing papers in PubMed, 2 syntheses or guidelines pooled it, 124 citations in OpenAlex.

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  16. Exploring Intraoperative Cognitive Biases in Cardiac Surgery Teams.Applied Human Factors and Ergonomics Conference · 2024
    Article
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

10 authors at 2 institutions in 1 country.

Cornelius A ThielsDepartment of Surgery, Mayo Clinic, Rochester, MN.
Tarun Mohan LalCenter for the Science of Health Care Delivery, Mayo Clinic, Rochester, MN.
Joseph M NienowQuality Management Services, Mayo Clinic, Rochester, MN.
Kalyan S PasupathyCenter for the Science of Health Care Delivery, Mayo Clinic, Rochester, MN.
Renaldo C BlockerCenter for the Science of Health Care Delivery, Mayo Clinic, Rochester, MN.
Johnathon M AhoDepartment of Surgery, Mayo Clinic, Rochester, MN.
Timothy I MorgenthalerPulmonary and Critical Care Medicine, Mayo Clinic, Rochester, MN.
Robert R CimaDepartment of Surgery, Mayo Clinic, Rochester, MN.
Susan HallbeckCenter for the Science of Health Care Delivery, Mayo Clinic, Rochester, MN.
Juliane BingenerDepartment of Surgery, Mayo Clinic, Rochester, MN. Electronic address: Bingenercasey.juliane@mayo.edu.
Mayo Clinic · USMayo Clinic in Arizona · US

Funding

Comparative Effectiveness of Novel Minimally Invasive Surgical ProceduresK23DK093553 · NIDDK · MAYO CLINIC ROCHESTER · PI BINGENER-CASEY, JULIANE · 2012 to 2014
$465k
NIDDK NIH HHS K23 DK093553NIDDK NIH HHS K23DK93553
6 · The paper itself

Abstract

introductionWe report the first prospective analysis of human factors elements contributing to invasive procedural never events by using a validated Human Factors Analysis and Classification System (HFACS).

methodsFrom August 2009 to August 2014, operative and invasive procedural "Never Events" (retained foreign object, wrong site/side procedure, wrong implant, wrong procedure) underwent systematic causation analysis promptly after the event. Contributing human factors were categorized using the 4 levels of error causation described by Reason and 161 HFACS subcategories (nano-codes).

resultsDuring the study, approximately 1.5 million procedures were performed, during which 69 never events were identified. A total of 628 contributing human factors nano-codes were identified. Action-based errors (n = 260) and preconditions to actions (n = 296) accounted for the majority of the nano-codes across all 4 types of events, with individual cognitive factors contributing one half of the nano-codes. The most common action nano-codes were confirmation bias (n = 36) and failed to understand (n = 36). The most common precondition nano-codes were channeled attention on a single issue (n = 33) and inadequate communication (n = 30).

conclusionTargeting quality and interventions in system improvement addressing cognitive factors and team resource management as well as perceptual biases may decrease errors and further improve patient safety. These results delineate targets to further decrease never events from our health care system.

Indexed as

CausalityFactor Analysis, StatisticalHumansMedical ErrorsMinnesotaPatient SafetyProspective StudiesSurgical Procedures, OperativeTertiary Care Centers

Identifiers

PMID26032826
PMCPMC4492832
OpenAlexW1519085983

What OpenQuestion holds

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Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.