ABSTRACT
The proliferation of monitors and alarms in the operating room may lead to increased confusion and misdiagnosis unless the information provided is better organized. Intelligent alarm systems are being developed to organize these alarms, on the assumption that they will shorten the time anesthesiologists need to detect and correct faults. This study compared the human response time (the time between the sounding of an alarm and the resolution of a fault) when anesthesiologists used a conventional alarm system and when they used an intelligent alarm system. In a simulated operating room environment, we asked 20 anesthesiologists to resolve seven breathing circuit faults as quickly as possible. Human response time was 62% faster, decreasing from 45 to 17 s, when the intelligent alarm system was used. The standard deviations in response time were only half as large for the intelligent alarm system. It appears that the computer-based neural network in the intelligent alarm system diagnosed faults more rapidly and consistently than did the anesthesiologists. This study indicates that breathing circuit faults may be more rapidly corrected when the anesthesiologist is guided by intelligent alarms.
Subject(s)
Anesthesiology/instrumentation , Artificial Intelligence , Monitoring, Physiologic/instrumentation , Operating Rooms , Equipment Failure , Humans , Reaction TimeABSTRACT
The results of an inquiry conducted at 5 university eye hospitals and 9 regional centers in Switzerland, concerning services for low-vision patients, are presented. Most of the services can help these visually handicapped people, but the type of care provided varies considerably from center to center. The authors briefly review the patients examined in Lausanne with regard to diagnosis, age, and the visual acuity of the better eye.
