Chapter 19: Neurophysiologic Decision Support Systems

Introduction

The intensive care unit (ICU) of the future in which technology enables dramatic improvements to clinical care while reducing costs has been predicted since the 1970s, but has largely been unrealized.¹ In fact, clinicians largely interact with patient data the same way as in the 1950s when ICUs were first introduced. Sensors measure different aspects of patient physiology, with the last 10 seconds of waveform data displayed on a patient monitor. Additional isolated medical devices measure more sophisticated physiological processes that are displayed on its own isolated display.

Very little attention has been given to how to best use data in the ICU. New monitoring technologies are placed next to other devices in already cramped patient rooms, and their data are added to what is already displayed. There is virtually no ability to go back and analyze what has happened over time, no concept of the complex dynamic interactions among all monitored physiological processes. Despite all of the impressive technological advances in the last 60 years, simply determining the average blood pressure over the last few hours is nearly impossible in most ICUs around the world.

The goal of multimodality neuromonitoring is to provide clinicians continuous, real-time assessment of brain physiology to prevent, detect, and attenuate secondary brain injury as well as to improve prognostication of outcome.² In 2014, the Neurocritical Care Society in collaboration with the European Society of Intensive Care Medicine, the Society for Critical Care Medicine, and the Latin America Brain Injury Consortium organized an international, multidisciplinary consensus conference to help develop evidence-based practice recommendations on bedside physiologic monitoring.³ The development of clinical informatics infrastructure in neurocritical care is not only critical to complying with evidence-based practice recommendations, but will reshape how we view physiological data and potentially our entire approach toward scientific discovery.⁴ This chapter is designed to help you understand the potential value and barriers to implementing neurophysiologic-centered DSSs in your ICU.

Why are neurophysiologic DSSs needed in the ICU?

Clinicians may be confronted with more than 200 variables⁵ during morning rounds, and yet they are not able to judge the degree of relatedness between more than two variables.⁶ Each variable collected is treated clinically as an individual parameter to control through treatment. However, patient physiology is not composed of independent processes, but dynamic systems of high-dimensional, nonlinear interactions whereby the level of one parameter affects how other parameters relate (see Figure 19-1). In the absence of genuine understanding about these physiological processes, device alarms are set to go off at the most extreme physiologic thresholds. This strategy only alerts clinicians when patients are on the verge of crashing and does little to identify the earliest stages of pathophysiologic processes in patients when conditions are most amenable to treatment. Devices may also produce thousands of false alarms for each patient⁷ that can lead to ...