Dataset Information

Surgical procedural map scoring for decision-making in laparoscopic cholecystectomy.

ABSTRACT: INTRODUCTION:The objective of this study was to determine whether decision-based procedural mapping demonstrates differences in attendings versus residents. METHODS:Attendings and residents were interviewed about operative decision-making in laparoscopic cholecystectomy (LC) using a cognitive task analysis framework. Interviews were converted into procedural maps. Operative steps, patient factors, and surgeon factors noted by attendings and residents were compared. Two scoring methods were used to compare map structures of attendings versus residents. RESULTS:Six attendings and six residents were interviewed. There were no significant differences in the number of patient or surgeon factors identified. Attendings had significantly more operative steps (29.67?±?1.9 vs. 23.3?±?1.9, p?=?0.04) and crosslinks (3.2?±?0.5 vs. 1?±?0.4, p?=?0.005) in their maps and a higher total score (90.2?±?8.4 vs. 63.2?±?3.8, p?=?0.015) than residents. CONCLUSION:LC procedural map scoring for attendings and residents demonstrated significant differences in structural complexity and may provide a useful framework for assessing decision making.

SUBMITTER: Hashimoto DA

PROVIDER: S-EPMC6581213 | biostudies-literature | 2019 Feb

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Surgical procedural map scoring for decision-making in laparoscopic cholecystectomy.

Hashimoto Daniel A DA Axelsson C Gustaf CG Jones Cara B CB Phitayakorn Roy R Petrusa Emil E McKinley Sophia K SK Gee Denise D Pugh Carla C

American journal of surgery 20181114 2

<h4>Introduction</h4>The objective of this study was to determine whether decision-based procedural mapping demonstrates differences in attendings versus residents.<h4>Methods</h4>Attendings and residents were interviewed about operative decision-making in laparoscopic cholecystectomy (LC) using a cognitive task analysis framework. Interviews were converted into procedural maps. Operative steps, patient factors, and surgeon factors noted by attendings and residents were compared. Two scoring met ...[more]

PMID: 30470551

Similar Datasets

Project description:BackgroundSurgical errors are acts or omissions resulting in negative consequences and/or increased operating time. This study describes surgeon-reported errors in laparoscopic cholecystectomy.MethodsIntraoperative videos were uploaded and annotated on Touch SurgeryTM Enterprise. Participants evaluated videos for severity using a 10-point intraoperative cholecystitis grading score, and errors using Observational Clinical Human Reliability Assessment, which includes skill, consequence, and mechanism classifications.ResultsNine videos were assessed by 8 participants (3 junior (specialist trainee (ST) 3-5), 2 senior trainees (ST6-8), and 3 consultants). Participants identified 550 errors. Positive relationships were seen between total operating time and error count (r2 = 0.284, P < 0.001), intraoperative grade score and error count (r2 = 0.578, P = 0.001), and intraoperative grade score and total operating time (r2 = 0.157, P < 0.001). Error counts differed significantly across intraoperative phases (H(6) = 47.06, P < 0.001), most frequently at dissection of the hepatocystic triangle (total 282; median 33.5 (i.q.r. 23.5-47.8, range 15-63)), ligation/division of cystic structures (total 124; median 13.5 (i.q.r. 12-19.3, range 10-26)), and gallbladder dissection (total 117; median 14.5 (i.q.r. 10.3-18.8, range 6-26)). There were no significant differences in error counts between juniors, seniors, and consultants (H(2) = 0.03, P = 0.987). Errors were classified differently. For dissection of the hepatocystic triangle, thermal injuries (50 in total) were frequently classified as executional, consequential errors; trainees classified thermal injuries as step done with excessive force, speed, depth, distance, time or rotation (29 out of 50), whereas consultants classified them as incorrect orientation (6 out of 50). For ligation/division of cystic structures, inappropriate clipping (60 errors in total), procedural errors were reported by junior trainees (6 out of 60), but not consultants. For gallbladder dissection, inappropriate dissection (20 errors in total) was reported in incorrect planes by consultants and seniors (6 out of 20), but not by juniors. Poor economy of movement (11 errors in total) was reported more by consultants (8 out of 11) than trainees (3 out of 11).ConclusionThis study suggests that surgical experience influences error interpretation, but the benefits for surgical training are currently unclear.

Project description:BackgroundSurgical patients incur preventable harm from cognitive and judgment errors made under time constraints and uncertainty regarding patients' diagnoses and predicted response to treatment. Decision analysis and techniques of reinforcement learning theoretically can mitigate these challenges but are poorly understood and rarely used clinically. This review seeks to promote an understanding of decision analysis and reinforcement learning by describing their use in the context of surgical decision-making.MethodsCochrane, EMBASE, and PubMed databases were searched from their inception to June 2019. Included were 41 articles about cognitive and diagnostic errors, decision-making, decision analysis, and machine-learning. The articles were assimilated into relevant categories according to Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews guidelines.ResultsRequirements for time-consuming manual data entry and crude representations of individual patients and clinical context compromise many traditional decision-support tools. Decision analysis methods for calculating probability thresholds can inform population-based recommendations that jointly consider risks, benefits, costs, and patient values but lack precision for individual patient-centered decisions. Reinforcement learning, a machine-learning method that mimics human learning, can use a large set of patient-specific input data to identify actions yielding the greatest probability of achieving a goal. This methodology follows a sequence of events with uncertain conditions, offering potential advantages for personalized, patient-centered decision-making. Clinical application would require secure integration of multiple data sources and attention to ethical considerations regarding liability for errors and individual patient preferences.ConclusionTraditional decision-support tools are ill-equipped to accommodate time constraints and uncertainty regarding diagnoses and the predicted response to treatment, both of which often impair surgical decision-making. Decision analysis and reinforcement learning have the potential to play complementary roles in delivering high-value surgical care through sound judgment and optimal decision-making.

Dataset Information

Surgical procedural map scoring for decision-making in laparoscopic cholecystectomy.

Publications

Surgical procedural map scoring for decision-making in laparoscopic cholecystectomy.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets