BACKGROUND: The potential for simulation-based learning in neurosurgical training has led the Congress of Neurosurgical Surgeons to develop a series of simulationmodules. The Northwestern Objective Microanastomosis Assessment Tool (NOMAT) was created as the corresponding assessment tool for the Congress of Neurosurgical Surgeons Microanastomosis Module. The face and construct validity of the NOMAT have been previously established. OBJECTIVE: To further validate the NOMAT by determining its interrater reliability (IRR) between raters of varying levels of microsurgical expertise. METHODS: The NOMAT was used to assess residents' performance in a microanastomosis simulation module in 2 settings: Northwestern University and the Society of Neurological Surgeons 2014 Boot Camp at the University of Indiana. At Northwestern University, participants were scored by 2 experienced microsurgeons. At the University of Indiana, participants were scored by 2 postdoctoral fellows and an experienced microsurgeon. The IRR of NOMATwas estimated by computing the intraclass correlation coefficient using SPSS v22.0 (IBM, Armonk, New York). RESULTS: A total of 75 residents were assessed. At Northwestern University, 21 residents each performed microanastomosis on 2 model vessels of different sizes, one 3 mm and one 1 mm. At the University of Indiana, 54 residents performed a single microanastomosis procedure on3-mm vessels. The intraclass correlation coefficient of the totalNOMAT scores was 0.88 at Northwestern University and 0.78 at the University of Indiana. CONCLUSION: This study indicates high IRR for the NOMAT. These results suggest that the use of raters with varying levels of expertise does not compromise the precision or validity of the scale. This allows for a wider adoption of the scale and, hence, a greater potential educational impact.
- Northwestern Objective Microanastomosis Assessment Tool
- Objective structured assessment of technical skill
- Resident training
- Simulation education
- Simulation in neurosurgery
ASJC Scopus subject areas
- Clinical Neurology