**1. Introduction**

A decision support system (DSS) in medicine is a software designed to assist the medical team in the decision making process; it deals with organizational, diagnostic and therapeu‐ tic problems, using data (e.g. variables of the patient) as inputs to combine with models and algorithms giving advice in form of monitor alerts, color codes, or visual messages; it does not replace the human operator, but can improve the quality of care. Modern society more and more asks the medical community for 'infallibility' in clinical practice, but errors is part of human intervention: emotions, behavioral and psychological patterns, or difficult con‐ texts can influence human performances. For humans, it is simply impossible to recall all di‐ agnostic and therapeutic options at any time for any given patient [1]. The use of DSSs in the clinical management could solve this problem helping specialists with diagnostic or thera‐ peutic suggestions, making it easier to follow validated guidelines, reducing the incidence of faulty diagnoses and therapies [2], and changing incorrect behaviors.

Early computerized medical systems date back to the early 60ies [3]. First prototypes were used to train medical students in establishing a diagnosis [4]. The evolution of these systems has followed the general innovation in technology and their capacities constantly increase over time, from only educational tools to intelligent systems for patient management.

Basically, a DSS can be designed using knowledge representation, in the form of clinical al‐ gorithms, mathematical pathophysiological models, Bayesian statistical systems and dia‐ grams, neural networks, fuzzy logic theories, and symbolic reasoning or "expert" systems [5]. A DSS has to be conceived suitable and user-friendly; the 'rules structure' should be

easily understood, the rules process should be intuitive and open for collaboration, all deci‐ sions should be reproducible and the user interface easy to use (Figure 1) [6].

Anesthesiologists and critical care specialists are very involved in patient safety; excellence in their fields needs a collection of nontechnical, nonclinical skills that may be classified as "task management", "team working", "situation awareness", and "decision-making"[19]. Developing information and decision technology support systems for these skills also means

Decision Support Systems in Medicine - Anesthesia, Critical Care and Intensive Care Medicine

http://dx.doi.org/10.5772/51756

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This chapter will focus on DSSs for anesthesiologists and critical care specialists in different

Anesthesiologists in the operating room have to provide direct patient care. Anesthesiolo‐ gists are considered the "pilots of human biosphere" [21], and terms like "takeoff" and "landing" for the process of inducing anesthesia and reversing it, are very common; since these are the two dominant and critical moments of anesthesia, often, maintenance of anes‐ thesia receives less attention [22]. To assure safe and good patient care during the surgical procedure, an anesthesiologist interacts with several devices: he becomes "the mediator be‐ tween patient and machine while the machine is mediating between patient and anesthesiol‐ ogist; all are hybrids in action and each is unable to act independently" [22]. It is impossible to consider the anesthetic work without machines just as it is impossible to imagine a pilot

Decision support systems for anesthesia in the milieu of the operating room are software shaped to assist the anesthesiologist in his difficult work during the surgical procedure. Let's divide DSSs for anesthesia in the operating room into three classes: DSSs designed for perioperative use, DSSs for one single intraoperative problem (*simple DSSs*) and DSSs for

**2.1. Organizational DSSs and implementation in AIMS in the perioperative context**

In his everyday activity, the anesthesiologist deals not only with patient-related issues, but al‐ so with many kinds of organizational problems, like strictly hierarchical command structures or deficits in providing important drugs or devices that can cause serious accidents. Reason [23] has proposed a scheme of the development of an organizational accident (Figure 2).

It is not possible to consider the anesthesiologist's responsibility only during the surgical in‐ tervention; as a pilot has to control his systems before the flight, anesthesiologists must con‐ tinuously assess the patient status, from pre-operative assessment till post-operative care. As a 'commander-in-chief', he has to make the final check of everything 'anesthetic' in the operating room, despite the presence of nurses or respiratory technicians. One type of DSS

The first example of how DSSs may improve safety in the operating environment is a DSS whhi generates dynamically configured checklists for intraoperative problems [24]. It is interesting that the database built with 600 entries of two anesthesia textbooks and organ‐

can deal with organizational problems in order to prevent accidents.

to significantly improve the quality, flow, and efficiency of medical performance [20].

areas: perioperative management, the emergency and intensive care medicine.

**2. Decision support systems for anesthesia in the operating room**

without his joysticks, buttons and computers.

multiple problems (*complex DSSs*).

**Figure 1.** Graphical user interface [6].

DSSs in medicine could play a role in every field: a modern DSS is conceived to predict rehabil‐ itation protocol for patients with knee osteoarthritis [7]. Another example of a modern DSS is a system that uses anthropometric information and questionnaire data to predict obstructive sleep apnea [8]. The use of DSSs has been proposed to treat major depression [9]; a DSS has been validated recently to diagnose the common flu [10]; a DSS has been developed to support the treatment of epilepsy [11]. Another DSS has been presented in the field of gynecology [12].

At present, it is not clear if an improvement of medical performance can always be transfer‐ red into an improvement of patient outcomes [13, 14] [15], and although better adherence to guidelines is proven, this cannot always be translated into abandoning habits of wrong-do‐ ing [16]. Furthermore, there are some considerable barriers to the widespread diffusion of these systems, like costs, cultural issues and lack of standards [2] [17] [18].

These systems are usually produced with limited private funds; mass production is limited by economic pressures. Lack of standardization often represents a "political" problem. There are always emotional barriers for physicians and other health care providers to 'rely' on the help of devices in order to make proper decision.

Anesthesiologists and critical care specialists are very involved in patient safety; excellence in their fields needs a collection of nontechnical, nonclinical skills that may be classified as "task management", "team working", "situation awareness", and "decision-making"[19]. Developing information and decision technology support systems for these skills also means to significantly improve the quality, flow, and efficiency of medical performance [20].

This chapter will focus on DSSs for anesthesiologists and critical care specialists in different areas: perioperative management, the emergency and intensive care medicine.
