Evidence map›Paper›PMID 31365107›Full record

Observational studyJAMA network open2019

Analysis of Human Performance Deficiencies Associated With Surgical Adverse Events.

James W Suliburk, Quentin M Buck, Chris J Pirko, Nader N Massarweh, Neal R Barshes, Hardeep Singh, Todd K Rosengart

Abstract readObservational Study
In one paragraph

Observational study in JAMA network open, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 68 papers, 6 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
68citing papers in PubMed, 6 pooled it
–field-weighted citation impact
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

68 citing papers in PubMed, 6 syntheses or guidelines pooled it.

  1. Pooled it
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  7. Surgical bleeding prediction using transformer: an application to laparoscopic cholecystectomy.International journal of computer assisted radiology and surgery · 2026
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  12. Artificial intelligence-based anatomical recognition improves surgeon decision-making during robotic gastrectomy.Gastric cancer : official journal of the International Gastric Cancer Association and the Japanese Gastric Cancer Association · 2026
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8 more citing papers are in PubMed but not listed here.

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

7 authors.

James W SuliburkMichael E. DeBakey Department of Surgery, Baylor College of Medicine, Houston, Texas.
Quentin M BuckDepartment of Medicine, Baylor College of Medicine, Houston, Texas.
Chris J PirkoMichael E. DeBakey Department of Surgery, Baylor College of Medicine, Houston, Texas.
Nader N MassarwehMichael E. DeBakey Department of Surgery, Baylor College of Medicine, Houston, Texas.
Neal R BarshesMichael E. DeBakey Department of Surgery, Baylor College of Medicine, Houston, Texas.
Hardeep SinghDepartment of Medicine, Baylor College of Medicine, Houston, Texas.
Todd K RosengartMichael E. DeBakey Department of Surgery, Baylor College of Medicine, Houston, Texas.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Importance: Potentially preventable adverse events remain a formidable cause of patient harm and health care expenditure despite advances in systems-based risk-reduction strategies. Objective: To analyze and describe the incidence of human performance deficiencies (HPDs) during the provision of surgical care to identify opportunities to enhance patient safety. Design, Setting, and Participants: This quality improvement study used a new taxonomy to inform the development and implementation of an HPD classifier tool to categorize HPDs into errors associated with cognitive, technical, and team dynamic functions. The HPD classifier tool was then used to concurrently analyze surgical adverse events in 3 adult hospital affiliates-a level I municipal trauma center, a quaternary care university hospital, and a US Veterans Administration hospital-from January 2, 2018, to June 30, 2018. Surgical trainees presented data describing all adverse events associated with surgical services at weekly hospital-based morbidity and mortality conferences. Adverse events and HPDs were classified in discussion with attending faculty and residents. Data were analyzed from July 9, 2018, to December 23, 2018. Main Outcomes and Measures: The incidence and primary and secondary causes of HPDs were classified using an HPD classifier tool. Results: A total of 188 adverse events were recorded, including 182 adverse events (96.8%) among 5365 patients who underwent surgical operations and 6 adverse events (3.2%) among patients undergoing nonoperative treatment. Among these 188 adverse events, 106 (56.4%) were associated with HPDs. Among these 106 HPD adverse events, a total of 192 HPDs (mean [SD], 1.8 [0.9] HPDs per HPD event) were identified. Human performance deficiencies were categorized as execution (98 HPDs [51.0%]), planning or problem solving (55 HPDs [28.6%]), communication (24 HPDs [12.5%]), teamwork (9 HPDs [4.7%]), and rules violation (6 HPDs [3.1%]). Human performance deficiencies most commonly presented as cognitive errors in execution of care or in case planning or problem solving (99 of 192 HPDs [51.6%]). In contrast, technical execution errors without other associated HPDs were observed in 20 of 192 HPDs (10.4%). Conclusions and Relevance: Human performance deficiencies were identified in more than half of adverse events, most commonly associated with cognitive error in the execution of care. These data provide a framework and impetus for new quality improvement initiatives incorporating cognitive training to mitigate human error in surgery.

Indexed as

FemaleHospitalsHumansIncidenceMaleMedical ErrorsPatient SafetyPostoperative ComplicationsProspective StudiesQuality ImprovementSurgical Procedures, OperativeTrauma Centers

Identifiers

PMID31365107
PMCPMC6669897

What OpenQuestion holds

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LicenceCC BY
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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.