Preferred Terms and Icons for Labels on Electrosurgical Units: Survey of VA Nurses.

Electrosurgical units (ESUs) developed by different manufacturers use varying terminology and icons to label the same components, which can result in confusion among users and the potential for erroneous ESU configuration. The objective of the current study was to identify nurse-preferred terms and icons for labeling ESU components. A total of 165 operating room (OR) nurses from Veterans Health Administration facilities across the United States were surveyed regarding terms and icons found on 25 ESU models. The results showed that 81% of OR nurses preferred ESUs that included both a term and an icon for labeling each component. In addition, greater consensus existed among OR nurses regarding preferred terms, rather than preferred icons, for representing each component. These findings on OR nurses' preferred terms and icons can be leveraged to improve ESU labeling practices and inform the development of a standardized, user-centered set of labels for ESU components.

Assessing Use Errors Related to the Interface Design of Electrosurgical Units.

Medical device use errors, such as instrument connection errors made with electrosurgical units (ESUs), can lead to adverse events. Current device acquisition processes at health care facilities do not typically include a proactive evaluation of use-error risk before device purchase. We conducted an evaluation to identify ESU user interface design features that can help prevent or mitigate instrument connection errors during clinical care. Thirty-six current ESU users participated in the evaluation. We used a randomized crossover design in which each participant used two ESU models in a simulated OR scenario. We compared participants' instrument connection accuracy, efficiency, and subjective feedback regarding the user interface design across the two ESU models. Overall, we found that the ESU model that incorporated more user interface design principles resulted in better performance and increased acceptance from users. Based on the results, we designed a decision-support tool to assess the risk of instrument connection errors before ESU purchase.