Are Cognitive Biases Influencing Your Clinical Decisions?

Confirmation bias occurs when clinicians seek to confirm a diagnosis rather than rule it out. For example, a patient presents with first-time, new-onset “classic” migraine symptoms, characterized as “the worst headache of her life.” The provider asks patient history questions to confirm the initial impression of a migraine headache and does not order a CT scan.

Posterior probability is a bias whereby the clinician gives excessive weight to a patient’s previous medical history. It occurs, for example, when a patient with chronic back pain is diagnosed with musculoskeletal back pain without considering other causes, such as urinary tract infection or pyelonephritis.

Diagnosis momentum bias occurs when a clinician relies on information handed down from numerous parties involved with the patient. An example is a patient who has a syncopal episode in church and several tonic-clonic movements while briefly unconscious. Nearby witnesses describe the event as a “seizure,” and paramedics relaying information to the emergency department indicate that the patient had a “seizure.” Ultimately, the triage information records “seizure” as the diagnosis. A cognitive error can occur if the treating clinician does not take a thorough history to consider an alternative diagnosis.

Fundamental attribution error bias occurs when a provider is judgmental and blames the patient for their disease. A provider who quips, “No wonder that patient has diabetes and hypertension; she weighs 325 lb,” is exhibiting fundamental attribution error bias.

Ascertainment bias allows preconceived notions, including stereotypes, to influence a clinician’s thinking. A provider who determines that all female patients with multiple somatic complaints have anxiety and depression is subject to this bias.

Triage cueing occurs when some aspect of the triage process influences the clinician’s thinking, such as when the clinician assumes that patients who are placed in the fast track are low acuity and therefore gives no consideration to higher acuity diagnoses.

Playing the odds assumes that a patient with a vague presentation has a benign condition rather than a serious one because the odds favor that. An example of this bias occurs when a 65-year-old woman with vomiting during flu season is quickly diagnosed with gastroenteritis. Fortunately, the patient is on a telemetry monitor while getting IV fluids and antinausea medication. The monitor results indicate that her vomiting episodes are occurring during long periods of sinus arrest.

Psych-out bias applies when signs or symptoms in a patient with a psychiatric diagnosis are ascribed to the underlying psychiatric condition and other serious possibilities are quickly dismissed. For example, a provider who assumes that an unstable psychiatric patient is nonadherent with her prescribed medication or is abusing substances rather than considering an underlying medical illness is demonstrating psych-out bias.

Illusory correlation bias occurs, for example, when the provider makes the assumption that the emergency department will be busy because there is a full moon.

Continue to find out if you are at risk for being wrong >>