Use of modeling to identify vulnerabilities to human error in laparoscopy.
This article describes an exercise to investigate the utility of modeling and human factors analysis in understanding surgical processes and their vulnerabilities to medical error. A formal method to identify error vulnerabilities was developed and applied to a test case of Veress needle insertion during closed laparoscopy. A team of 2 surgeons, a medical assistant, and 3 engineers used hierarchical task analysis and Integrated DEFinition language 0 (IDEF0) modeling to create rich models of the processes used in initial port creation. Using terminology from a standardized human performance database, detailed task descriptions were written for 4 tasks executed in the process of inserting the Veress needle. Key terms from the descriptions were used to extract from the database generic errors that could occur. Task descriptions with potential errors were translated back into surgical terminology. Referring to the process models and task descriptions, the team used a modified failure modes and effects analysis (FMEA) to consider each potential error for its probability of occurrence, its consequences if it should occur and be undetected, and its probability of detection. The resulting likely and consequential errors were prioritized for intervention. A literature-based validation study confirmed the significance of the top error vulnerabilities identified using the method. Ongoing work includes design and evaluation of procedures to correct the identified vulnerabilities and improvements to the modeling and vulnerability identification methods.
School of Mechanical, Industrial, and Manufacturing Engineering, 204 Rogers Hall, Oregon State University, Corvallis, OR 97331-6001, USA. funkk@engr.orst.edu
Kenneth H
KH
Funk
James D
JD
Bauer
Toni L
TL
Doolen
David
D
Telasha
R Javier
RJ
Nicolalde
Miriam
M
Reeber
Nantakrit
N
Yodpijit
Myra
M
Long
D005163:Factor Analysis, Statistical; D006801:Humans; D010535:Laparoscopy; D019300:Medical Errors; D015233:Models, Statistical; D018570:Risk Assessment; D012308:Risk Management; D013647:Task Performance and Analysis