Author: Zieda, Anete; Sbardella, Silvia; Patel, Malika; Smith, Richard W
Title: Diagnostic Bias in the COVID-19 Pandemic: A Series of Short Cases. Cord-id: qeq261zd Document date: 2021_1_1
ID: qeq261zd
Snippet: During the COVID-19 pandemic, healthcare systems have faced unprecedented pressures. One challenge has been to promptly recognise non-COVID-19 conditions. Cognitive bias due to the availability heuristic may cause difficulties in reaching the correct diagnosis. Confirmation bias may also affect imaging interpretation. We report three cases with an alternative final diagnosis in whom COVID-19 was initially suspected: (a) Pneumocystis jirovecii pneumonia with unrecognised HIV infection; (b) pulmon
Document: During the COVID-19 pandemic, healthcare systems have faced unprecedented pressures. One challenge has been to promptly recognise non-COVID-19 conditions. Cognitive bias due to the availability heuristic may cause difficulties in reaching the correct diagnosis. Confirmation bias may also affect imaging interpretation. We report three cases with an alternative final diagnosis in whom COVID-19 was initially suspected: (a) Pneumocystis jirovecii pneumonia with unrecognised HIV infection; (b) pulmonary lymphangitis carcinomatosis; and (c) ST elevation myocardial infarction causing acute pulmonary oedema. To help mitigate bias, there is no substitute for thoughtful clinical assessment and critical appraisal when evaluating new information and formulating the differential diagnosis. LEARNING POINTS The availability heuristic during the recent pandemic may lead to cognitive bias in favour of COVID-19 diagnosis and delayed recognition of other conditions, especially in patients presenting with similar non-specific features.Confirmation bias towards COVID-19 can also affect the interpretation of pulmonary imaging which is central to the investigation of cases with suspected pneumonitis.Diagnostic bias can be mitigated by recognition and allowing time for a thorough clinical history and methodical examination of the patients.
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