In a 1951 Electrical Engineering journal, R. G. Bickford suggested that brain electrical activity may be used to create a closed-loop system that controls the amount of anesthetic administrated to a patient in the operating room.1 It is quite humbling to realize that 70 years later, the specialty of anesthesiology still has not delivered on this vision. Indeed, while many developments have occurred in our field, they are largely incremental rather than transformative. Examples of such incremental progress include new and safer drugs and new descriptive monitors. Transformative changes such as the one described in Bickford’s 1951 article are few and far between.
In this issue of Anesthesia & Analgesia, we examine a potential futuristic framework suggested by a group of investigators from Massachusetts General Hospital, host to the first public demonstration of ether anesthesia in 1846. These investigators are proposing a new construct of “systems anesthesiology”2 and draw parallels to the field of “systems biology”—a relatively new interdisciplinary study that integrates computational cell biology, proteomics, genomics, and computational modeling to understand the larger picture of an organism.3 In the case of anesthesiology, the authors suggest incorporating information from the diverse spectrum of molecular, cellular, and computational data as well as a wide use of predictive models. Throughout their Open Mind article, the authors provide some excellent examples of opportunities to integrate molecular, cellular, and computational data in the management of a critically ill patient. Some of these opportunities may already be used today‚ while many are more future-facing. This article is particularly thought provoking because it promotes a discussion both about the term “systems anesthesiology” itself and the future of our specialty.
In a recent editorial, Kain et al4 suggested the need to close the existing knowledge translation gap in medicine and anesthesiology. The editorial highlights that the implementation of scientific progress and advancements (ie, systems anesthesiology) into practice is slow and difficult due to the silo mentality embedded in our health care system, as well as the complexity of human behavior. That is, just because molecular, cellular, or computational data about a particular patient exist does not necessarily mean that an individual practitioner will ultimately use these data in treatment. The same challenge holds right now for practically all monitoring systems we use in our operating rooms. There is a copious amount of data recorded‚ but there is not a process to ensure that the data are used. To adopt a new framework such as systems anesthesiology, our field must also adopt an additional layer of “systems approach and engineering.” In this regard, the two constructs of “systems biology” and “anesthesiology biology” may differ.
Systems engineering is an interdisciplinary construct that focuses on how to develop, integrate, and manage complex systems.5 While this term can be traced back to Bell Telephone Laboratories in the 1940s, it has gained wide adoption and is now being used in many industries, and the term “systems approach” has become popular. In 2005, a Committee on Engineering and the Health Care System from the National Academy of Engineering and Institute of Medicine constructed a report that suggested a partnership between engineers and health care providers aimed toward adapting a systems approach into medicine.6 This initial report was followed by a call for action in a Journal of the American Medical Association editorial7 and a 2013 Institute of Medicine and National Academy of Engineering task force meeting that indicated the urgent need for medicine to adapt a structured, evidence-based systems-engineering approach following the standard in many other industries.8 In health care, this approach is aimed to solve the challenges from the multiplicity of human and system elements interacting to impact outcomes. This approach is complementary to the ‘‘systems anesthesiology” suggested by Ruscic et al, since it takes into consideration the real world of clinical medicine. A recent meta-analysis suggests that this systems and engineering approach results in significant clinical and operational improvements, but more randomized controlled trials are needed.9 Within our discipline of anesthesiology and the perioperative environment, various system-engineering models have been adopted in the areas of patient safety and operational management of the perioperative environment. An example is the perioperative surgical home (PSH) model that calls to transform perioperative care by systems engineering approach to the environment.10 The PSH calls not only for the adoption of specificclinical practices, but also for a transformative workflow that includes clinical, operational, and financial aspects. The relative lack of adoption of the PSH in the United States is a prime example of how resistant the perioperative environment is to any proposed system changes.
In conclusion, we suggest integrating the concept of systems anesthesiology with the body of work done in systems engineering and that the combined model is a better reflection of where our specialty needs to move in the future. Combined, these represent a major advancement in specialty, to a vision outlined years ago.