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INFORMATION THEORY IN THE CCU

Information theory is the mathematical study of the transmission and coding of signals.[226] Originally developed to understand radio and telephone signals better, it is directly relevant to some of the problems of instrument use in the CCU. CCU practice is characterized by large amounts of constantly changing data. This data-rich environment pushes the dominant paradigms for clinical decision making to the breaking point. One thoughtful article that reviewed the theories of clinical decision making and their relevance to critical care medicine stressed the importance of examining CCU practice patterns for pitfalls and blind alleys that compromise patient care.[227]

Introspection about critical care decision making is not a hollow academic exercise. It is practiced on a daily basis by quality assurance committees, at morbidity and mortality conferences, and in medical negligence litigation. A physician who does not think about "thinking about" decision making (meta decision making) is in a poor position to document and explain that decision making when it is retrospectively reviewed.

Critical care medicine can be distinguished from other practice situations by the information flow in the CCU. This is useful because information theory is concerned with the basic problem of CCU medicine: decision making under uncertainty. An intensivist must cope with costly information in a high noise environment. By explicitly recognizing the cost of information and its inherent uncertainty, intensivists may be better able to make and defend decisions made in the "fog of war" that typifies critical care medicine.

Information is frequently confused with data. Information is a datum that allows a decision to be made. The results of laboratory tests are not information unless they aid in the clinical decision-making process. Data that are not information are noise. The intensive care environment is extremely noisy because it is saturated with data that do not contribute to clinical decision making. Sorting the information from this data stream is costly in both the economic sense and in other measures of value, such as delay and physical risk to the patient. What separates the noise problem in critical care decision making from that in other data-intensive medical environments is the time domain.

[226]Richards EP: Living with uncertainty: Information theory and critical care decisionmaking. J Intensive Care Med 1990; 5:91-92.

[227]Goldman GM: Judgmental error in intensive care practice. J Intensive Care Med 1990; 5(3):93-103.

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