Misdiagnoses in the Context of Suspected Pandemic Influenza or Coronavirus Disease 2019: A Systematic Review.
Lucy BrayKaterina MeznikovaDaniel JamesRazan RislanRahul ShahPavan MasonTim StanilandPatrick J LillieGavin BarlowNicholas J W EasomPublished in: Open forum infectious diseases (2022)
There have been numerous reports of patients initially misdiagnosed in the 2009 H1N1 influenza and coronavirus disease 2019 (COVID-19) pandemics within the literature. A systematic review was undertaken to collate misdiagnoses during the H1N1 and COVID-19 pandemics and identify which cognitive biases may contribute to this. MEDLINE, Embase, Cochrane and MedRxiv databases were searched for misdiagnoses or cognitive biases resulting in misdiagnosis, occurring during the H1N1 or COVID-19 virus pandemics. Eligible studies were assessed for quality using JBI criteria; primary outcome was the final diagnosis. Sixty-nine studies involving 2551 participants were included. We identified 686 cases of misdiagnosis, categorized as viral respiratory infection, other respiratory infection, non-respiratory infection, and non-infective. Misdiagnoses are listed and relevant investigations are offered. No article described prospective assessment of decision making in the pandemic setting or debiasing diagnostic thinking. Further research is required to understand why misdiagnoses occur and harm arises and how clinicians can be assisted in their decision making in a pandemic context.
Keyphrases
- coronavirus disease
- sars cov
- respiratory syndrome coronavirus
- end stage renal disease
- systematic review
- ejection fraction
- newly diagnosed
- chronic kidney disease
- emergency department
- palliative care
- prognostic factors
- respiratory tract
- case control
- machine learning
- deep learning
- big data
- quality improvement
- patient reported