Unmasking expert decisions: Clinicians decision making during a pandemic outbreak

Yuval Bitan, Sagit Lilach-Gueta, Avi Parush

Research output: Contribution to journalArticlepeer-review

Abstract

Decision making is based on information, but in the early days of the COVID-19 pandemic, information was scarce, while healthcare organizations and individual caregivers were pressured to make decisions about working protocols and clinical procedures. This study examined decision-making of individual clinicians that were involved in clinical and operational decisions during the early days of the pandemic. The study followed the critical decision method, and the cognitive interview was administered to 10 healthcare professionals from three countries. The interviews were analysed with an inductive analysis, followed by a theoretical thematic analysis. The inductive themes included the key themes of missing information, information flood, collaboration, collective responsibility, new working procedures, organizational preparedness, over-reactions, operations, dynamic decision making, and personal experience. The theoretical themes that fit natural decision-making models included relevant clinical cues, plausible treatment goals, expectations, actions, and intuition. Additional themes were identified, including operational challenges, evolving goals, ad-hoc actions, and resilience in operational decisions, suggesting that some decisions were unprimed, presenting a new conceptual model. Theoretically, the study suggests that experts can face situations that require them to make decisions that are within their field of operation (within context) and yet ‘out of expertise’, and those decisions may be unprimed.

Original languageAmerican English
Pages (from-to)268-276
Number of pages9
JournalInternational Journal of Healthcare Management
Volume16
Issue number2
DOIs
StatePublished - 1 Jan 2023

Keywords

  • COVID-19
  • Naturalistic decision making
  • out of expertise
  • recognition-primed decision making
  • thematic analysis

All Science Journal Classification (ASJC) codes

  • Leadership and Management
  • Health Policy

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