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Review
. 2022 Jan;38(1):129-139.
doi: 10.1016/j.ccc.2021.08.004.

Enhancing Diagnosis Through Technology: Decision Support, Artificial Intelligence, and Beyond

Robert El-Kareh  1 , Dean F Sittig  2
Affiliations
Review

Enhancing Diagnosis Through Technology: Decision Support, Artificial Intelligence, and Beyond

Robert El-Kareh et al. Crit Care Clin. 2022 Jan.

Abstract

Patient care in intensive care environments is complex, time-sensitive, and data-rich, factors that make these settings particularly well-suited to clinical decision support (CDS). A wide range of CDS interventions have been used in intensive care unit environments. The field needs well-designed studies to identify the most effective CDS approaches. Evolving artificial intelligence and machine learning models may reduce information-overload and enable teams to take better advantage of the large volume of patient data available to them. It is vital to effectively integrate new CDS into clinical workflows and to align closely with the cognitive processes of frontline clinicians.

Keywords: Clinical decision support; Clinical informatics; Data visualization; Diagnostic decision support.

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Figures

Figure 1.
Figure 1.
Categories of Diagnostic Tasks and Potential Uses of Clinical Decision Support (ICU: intensive care unit)
See this image and copyright information in PMC

References

    1. Belard A, Buchman T, Forsberg J, et al. Precision diagnosis: a view of the clinical decision support systems (CDSS) landscape through the lens of critical care. J Clin Monitor Comp. 2017;31(2):261–271. - PubMed
    1. Pirracchio R, Cohen MJ, Malenica I, et al. Big data and targeted machine learning in action to assist medical decision in the ICU. Anaesth Crit Care Pain Med. 2019;38(4):377–384. - PubMed
    1. HealthIT.gov. https://www.healthit.gov/topic/safety/clinical-decision-support. Accessed April 10, 2021.
    1. Wright A, Sittig DF, Ash JS, et al. Development and evaluation of a comprehensive clinical decision support taxonomy: comparison of front-end tools in commercial and internally developed electronic health record systems. J Am Med Inform Assoc. 2011;18(3):232–242. - PMC - PubMed
    1. Lim WS, van der Eerden MM, Laing R, et al. Defining community acquired pneumonia severity on presentation to hospital: an international derivation and validation study. Thorax. 2003;58(5):377–382. - PMC - PubMed