1. Development and Introduction of Decision Support Systems
Currently, decision support systems are hardly available in anesthesia, despite many studies showing that these systems can help us to do a better job, and limit human mistakes (6). Some of these systems have been tested in various situations where limited vigilance leads to a constant level of insufficient performance, from missed alarm settings to missed drug administration, the most striking being the administration of preemptive antibiotic prophylaxis. Focusing on ‘smart alarms’, these decision support systems could easily be implemented in current perioperative monitoring systems or anesthesia information management systems. Let us take an example: how often do we forget to monitor neuromuscular blockade, either during surgery or at the end? An honest answer would be quite often. Why is there no ‘smart monitoring system’ that would ask us at the end of surgery to monitor neuromuscular blockade, suggest the correct site (the adductor pollicis muscle), maybe even show it on the screen, ask us to enter the value and then suggest or recommend a line of action, according to current guidelines? Why are such systems not available when every clinician would agree that they add value to anesthetic safety in order to avoid postoperative residual paralysis?
We need to develop and integrate these systems to make anesthesia even safer.
3. Completely Automated Anesthesia
The introduction of automated anesthesia systems in clinical practice is not limited by their performance or their safety but only by the present regulatory hurdles. In the light of the recent FDA approval of the rather controversial Sedasys system, a semi-automated propofol delivery system that will be used by non-anesthetic health care providers (gastroenterologists) controversial because, at this stage, a machine is unable to adjust the level of sedation to the anticipated discomfort of discrete parts of the procedure, or to the specific skill and speed of a given operator, but also because, if a patient gets overly sedated, as is possible even with an experienced practitioner, Sedasys will not lift the jaw or ventilate the patient using a face mask, and there is no reversal agent for propofol one might question the validity of NOT making automated anesthesia delivery systems, tested in thousands of patients, available for use by anesthesiologists, who are experts in anesthesia delivery. Regulatory agencies need to reassess their attitude towards robotic or automated anesthesia systems.
For better or for worse, we cannot resist technological advances. Our role is to manage those advances to best benefit patients, but also to avoid disappearing, like travel agents and bank tellers, who were displaced by the Internet. Taking ownership of the technology is paramount: we need to be the drivers of progress rather than those who resist it out of inertia.
Liu N, Chazot T, Hamada S, Landais A, Boichut N, Dussaussoy C, et al. Closed-loop coadministration of propofol and remifentanil guided by bispectral index: a randomized multicenter study. Anesth Analg. 2011; 112 (3) : 546 -57 [DOI][PubMed]
Hemmerling TM, Taddei R, Wehbe M, Cyr S, Zaouter C, Morse J. Technical communication: First robotic ultrasound-guided nerve blocks in humans using the Magellan system. Anesth Analg. 2013; 116 (2) : 491 -4 [DOI][PubMed]
Salem M, Eyssel F, Rohlfing K, Kopp S, Joublin F. To Err is Human(-like): Effects of Robot Gesture on Perceived Anthropomorphism and Likability. Int J Soc Robot. 2013; 5 (3) : 313 -23 [DOI]
Hemmerling TM, Cirillo F, Cyr S. Decision Support Systems in Medicine - Anesthesia, Critical Care and Intensive Care Medicine.; 2012;
Lortat-Jacob B, Billard V, Buschke W, Servin F. Assessing the clinical or pharmaco-economical benefit of target controlled desflurane delivery in surgical patients using the Zeus anaesthesia machine. Anaesthesia. 2009; 64 (11) : 1229 -35 [DOI][PubMed]