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Intensive Care Unit Physicians' Perspectives on Artificial Intelligence-Based Clinical Decision Support Tools: Preimplementation Survey Study.
van der Meijden, Siri L; de Hond, Anne A H; Thoral, Patrick J; Steyerberg, Ewout W; Kant, Ilse M J; Cinà, Giovanni; Arbous, M Sesmu.
Afiliação
  • van der Meijden SL; Department of Intensive Care Medicine, Leiden University Medical Center, Leiden, Netherlands.
  • de Hond AAH; Clinical AI Implementation and Research Lab, Leiden University Medical Center, Leiden, Netherlands.
  • Thoral PJ; Healthplus.ai, Amsterdam, Netherlands.
  • Steyerberg EW; Clinical AI Implementation and Research Lab, Leiden University Medical Center, Leiden, Netherlands.
  • Kant IMJ; Department of Biomedical Data Sciences, Leiden University Medical Center, Leiden, Netherlands.
  • Cinà G; Department of Intensive Care Medicine, Laboratory for Critical Care Computational Intelligence, Amsterdam Medical Data Science, Amsterdam University Medical Centers, Amsterdam, Netherlands.
  • Arbous MS; Department of Biomedical Data Sciences, Leiden University Medical Center, Leiden, Netherlands.
JMIR Hum Factors ; 10: e39114, 2023 Jan 05.
Article em En | MEDLINE | ID: mdl-36602843
ABSTRACT

BACKGROUND:

Artificial intelligence-based clinical decision support (AI-CDS) tools have great potential to benefit intensive care unit (ICU) patients and physicians. There is a gap between the development and implementation of these tools.

OBJECTIVE:

We aimed to investigate physicians' perspectives and their current decision-making behavior before implementing a discharge AI-CDS tool for predicting readmission and mortality risk after ICU discharge.

METHODS:

We conducted a survey of physicians involved in decision-making on discharge of patients at two Dutch academic ICUs between July and November 2021. Questions were divided into four domains (1) physicians' current decision-making behavior with respect to discharging ICU patients, (2) perspectives on the use of AI-CDS tools in general, (3) willingness to incorporate a discharge AI-CDS tool into daily clinical practice, and (4) preferences for using a discharge AI-CDS tool in daily workflows.

RESULTS:

Most of the 64 respondents (of 93 contacted, 69%) were familiar with AI (62/64, 97%) and had positive expectations of AI, with 55 of 64 (86%) believing that AI could support them in their work as a physician. The respondents disagreed on whether the decision to discharge a patient was complex (23/64, 36% agreed and 22/64, 34% disagreed); nonetheless, most (59/64, 92%) agreed that a discharge AI-CDS tool could be of value. Significant differences were observed between physicians from the 2 academic sites, which may be related to different levels of involvement in the development of the discharge AI-CDS tool.

CONCLUSIONS:

ICU physicians showed a favorable attitude toward the integration of AI-CDS tools into the ICU setting in general, and in particular toward a tool to predict a patient's risk of readmission and mortality within 7 days after discharge. The findings of this questionnaire will be used to improve the implementation process and training of end users.
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Tipo de estudo: Prognostic_studies Idioma: En Revista: JMIR Hum Factors Ano de publicação: 2023 Tipo de documento: Article País de afiliação: Holanda

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Tipo de estudo: Prognostic_studies Idioma: En Revista: JMIR Hum Factors Ano de publicação: 2023 Tipo de documento: Article País de afiliação: Holanda