Use of Modeling to Identify Vulnerabilities to Human Error in Laparoscopy
| Autor: | Ken Funk, Toni L. Doolen, James D. Bauer, David Telasha, R. Javier Nicolalde, Myra D. Long, Miriam Reeber, Nantakrit Yodpijit |
|---|---|
| Rok vydání: | 2010 |
| Předmět: |
Risk Management
Models Statistical Process modeling Medical Errors business.industry Computer science Process (engineering) Human error Obstetrics and Gynecology Formal methods Machine learning computer.software_genre Risk Assessment Terminology Task (project management) Task Performance and Analysis Task analysis Humans Laparoscopy Artificial intelligence Data mining Factor Analysis Statistical business IDEF0 computer |
| Zdroj: | Journal of Minimally Invasive Gynecology. 17:311-320 |
| ISSN: | 1553-4650 |
| DOI: | 10.1016/j.jmig.2010.01.012 |
| Popis: | 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. |
| Databáze: | OpenAIRE |
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