Narrative Review of Decision-Making Processes in Critical Care

Anesth Analg. 2019 May;128(5):962-970. doi: 10.1213/ANE.0000000000003683.

Abstract

Several theories describing the decision-making process in the intensive care unit (ICU) have been formulated. However, none of them appreciate the complexities of the process in an eclectic way by unifying several miscellaneous variables in 1 comprehensive theory. The purpose of this review is to highlight the key intricacies associated with the decision-making process in the ICU, to describe the theoretical frameworks with a special emphasis on gaps of knowledge, and to offer some avenues for improvement. The application of theoretical framework helps us to understand and to modify the structure of the process. Expected utility theory, regret theory, prospect theory, fuzzy-trace theory, construal level theory, and quantum probability theory were formulated over the years to appreciate an increased complexity of the decision-making process in the ICU. However the decision makers engage, these models may affect patient care because each of these frameworks has several benefits and downsides. There are gaps of knowledge in understanding how physicians match the different theoretical frameworks of the decision-making process with the potentially high ICU variability and load, especially when the "best outcome" is often nondiscrete and multidimensional. Furthermore, it is unclear when the preferential application of reflexive, habitual, variable, and biased-prone processes results in patient and staff detriment. We suggest better matching of theoretical frameworks with strengths of the human decision-making process and balanced application computer aids, artificial intelligence, and organizational modifications. The key component of this integration is work to increase the self-awareness of decision-making processes among residents, fellows, and attending physicians.

Publication types

  • Review

MeSH terms

  • Clinical Decision-Making*
  • Critical Care / methods*
  • Critical Care / standards*
  • Decision Support Systems, Clinical
  • Fuzzy Logic
  • Humans
  • Intensive Care Units*
  • Interdisciplinary Communication
  • Medical Staff, Hospital
  • Models, Organizational
  • Patient Care Team
  • Physicians
  • Probability
  • Qualitative Research
  • Treatment Outcome