Rethinking sedation and agitation management in critical illness.

Crit Care Resusc

Department of Intensive Care, Christchurch Hospital, University of Otago, Christchurch, New Zealand.

Published: September 2003

Objective: To examine difficulties in sedation management in the critically ill patient and explore how a semi automated sedation controller can improve agitation control. To present recent work on measurements of agitation, dynamic systems modelling and control of patient agitation response.

Data Sources: Articles and peer-reviewed studies identified through a PUBMED search and selected original works from the biomedical engineering literature of relevance to agitation control and management.

Summary Of Review: Over-sedation has an adverse impact on intensive care resources. Interventions to constrain sedation delivery through development of protocols or regular cessation of infusions result in reduction in resource utilisation, but have not significantly addressed existing difficulties in agitation control. We develop a paradigm in which control of agitation in critically ill patients becomes the primary objective of sedation management. This principle is central to the function of a nurse-managed semi-automated sedation delivery device. The clinical application of this device using subjective assessments of agitation is presented. A framework for the development of improved automated sedation delivery systems using objective measurements of agitation and control, based on agitation feedback, is described. Using dynamic systems modelling and a simulated nurse, a bolus-driven approach significantly reduced agitation and minimised drug utilisation. This result challenges the current practice of sedating patients using continuous infusions.

Conclusions: A simple computerised interface with an algorithm that continually reduces the infusion rate in the absence of agitation has successfully been introduced into clinical practice. Nursing staff reported high levels of satisfaction with this device and it has enabled detailed data on patterns of sedation administration to be extracted for analysis. This data has been used to validate a model of the fundamental agitation-sedation dynamics.

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