Understanding clinical decision-making during the COVID-19 pandemic: A cross-sectional worldwide survey
Data
2020Autor
Martínez-Sanz, Javier
Pérez-Molina, Jose A.
Moreno, Santiago
Zamora, Javier
Serrano-Villar, Sergio
Metadata
Mostrar registro completoResumo
Background: The lack of evidence-based recommendations for therapeutic decisions during the early weeks
of the COVID-19 pandemic creates a unique scenario of clinical decision making which is worth to analyze.
We aim to identify the drivers of therapeutic aggressiveness during the first weeks of the COVID-19
pandemic.
Methods: This cross-sectional worldwide survey (conducted April 12 to 19, 2020) was aimed at physicians
who managed patients diagnosed with COVID-19. Treatment preferences were collected in five different
clinical scenarios. We used multilevel mixed-effects ordered logistic regression to identify variables that
were associated with the use of more aggressive therapies.
Findings: The survey was completed by 852 physicians from 44 different specialties and 29 countries. The
heterogeneity of therapeutic decisions increased as the clinical scenario worsened. Factors associated with
aggressive therapeutic decisions were higher self-perceived expertise (high vs. null, OR 1.95, 95%CI
1.31 2.89), perceived quality of COVID-19 publications (high vs. null, OR 1.92, 95%CI 1.17 3.16), and female
sex (OR 1.17, 95%CI 1.02 1.33). Conversely, Infectious Diseases specialty, Latin American and North American origin, lower confidence in the treatments chosen, and having published articles indexed in PubMed as
the first-author were associated with the use of less aggressive therapies.
Interpretation: Our study provides insight into the drivers of the decision-making process during a new and
extreme health emergency. Different factors including the perceived expertise and quality of publications,
gender, geographic origin, medical specialty and implication in medica
Palabras clave
COVID-19; Clinical decision-making; Surveys and questionnaires; Therapeutics; UncertaintyLink para o recurso
https://doi.org/10.1016/j.eclinm.2020.100539Collections
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