A case study, analyzing how availability bias has affected diagnoses of Covid-19 and Legionella, was recently published and presented a case study of a 56-year-old man who was improperly diagnosed with COVID-19. The patient came in exhibiting many symptoms and diagnostics commonly associated with COIVD-19. Further, he made it known that had had come in contact with confirmed cases of COVID-19 and was deemed to have a high probability of having contracted the disease. Although his COVID-19 tests came back negative three times, due to the powerful effect of anchoring, the diagnosis of COVID-19 remained high. However, on day two of admission, due to persistent hyponatremia, a urine antigen test for Legionella was requested and returned positive. Legionella pneumophila was identified in 1979 as the causative pathogen of previously unidentified pneumonia after an outbreak among attendees at a convention of the American Legion three years earlier. Since then, it has been estimated that about 8,000-18,000 Americans have been hospitalized with Legionnaires’ disease annually. The disease occurs following the inhalation of aerosolized droplets containing the bacteria or after aspiration of contaminated water. The case study suggests that an inaccurate initial diagnosis can result in mismanagement and cause unintended harm to patients. The role of cognitive biases, such as anchoring, overconfidence bias, premature closure, confirmation bias, and availability bias, as sources of flawed medical decision-making and medical errors are well established in the literature. Clinicians’ awareness of these faulty mental frameworks can minimize their adverse effects. In relation to pretest diagnoses of COVID-19, It is equally important to recognize that other diagnoses are possible. This need for a heightened awareness of alternative diagnoses is essential during times when there is a high propensity to fall into the traps of availability bias. This issue can be problematic even among highly experienced clinicians. It is known that clinicians are more prone to biases when using non-analytical reasoning, i.e., the type of reasoning that develops with pattern recognition and, coincidentally, with clinician experience. In response to this, the case study suggests that methods that utilize a more analytic approach may reduce the effects of availability bias and potentially other biases as well. In the present case, analyzing the patient’s particular presentation considered his hyponatremia, which has been associated with Legionella pneumonia and ultimately led to the correct diagnosis. References: To read more about the Availability Bias and its Relationship to Legionnaires’ Disease and COVID-19, click here. To read our firm’s white paper on Legionnaires’ disease and COVID-19, click here. For more information on Legionnaires’ disease, check out the National Academies of Sciences Management of Legionella in Water Systems Report here. Contact Jules Zacher for a 100% free consultation today. THE MATERIALS ON THIS WEBSITE HAVE BEEN PREPARED BY JULES ZACHER, P.C. FOR INFORMATIONAL PURPOSES ONLY AND ARE NOT LEGAL ADVICE OR A SUBSTITUTE FOR LEGAL COUNSEL.