An elderly woman with ‘heart failure’: Cognitive biases and diagnostic error

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ABSTRACTErrors in diagnosis can arise from the clinician’s cognitive biases as well as from problems in the healthcare system. Here the authors review a case with a bad outcome to analyze what went wrong and why.


  • Diagnostic errors are common and lead to bad outcomes.
  • Factors that increase the risk of diagnostic error include initial empiric treatment, nonspecific or vague symptoms, atypical presentation, confounding comorbid conditions, contextual factors, and physician factors.
  • Common types of cognitive error include the framing effect, anchoring bias, diagnostic momentum, availability bias, confirmation bias, blind obedience, overconfidence bias, base-rate neglect, and premature closure.
  • Organizations and leaders can implement strategies to reduce diagnostic errors.



An elderly Spanish-speaking woman with morbid obesity, diabetes, hypertension, and rheumatoid arthritis presents to the emergency department with worsening shortness of breath and cough. She speaks only Spanish, so her son provides the history without the aid of an interpreter.

Her shortness of breath is most noticeable with exertion and has increased gradually over the past 2 months. She has a nonproductive cough. Her son has noticed decreased oral intake and weight loss over the past few weeks. She has neither traveled recently nor been in contact with anyone known to have an infectious disease.

A review of systems is otherwise negative: specifically, she denies chest pain, fevers, or chills. She saw her primary care physician 3 weeks ago for these complaints and was prescribed a 3-day course of azithromycin with no improvement.

Her medications include lisinopril, atenolol, glipizide, and metformin; her son believes she may be taking others as well but is not sure. He is also unsure of what treatment his mother has received for her rheumatoid arthritis, and most of her medical records are within another health system.

The patient’s son believes she may be taking other medications but is not sure; her records are at another institution

On physical examination, the patient is coughing and appears ill. Her temperature is 99.9°F (37.7°C), heart rate 105 beats per minute, blood pressure 140/70 mm Hg, res­piratory rate 24 per minute, and oxygen saturation by pulse oximetry 89% on room air. Heart sounds are normal, jugular venous pressure cannot be assessed because of her obese body habitus, pulmonary examination demonstrates crackles in all lung fields, and lower-extremity edema is not present. Her extremities are warm and well perfused. Musculoskeletal examination reveals deformities of the joints in both hands consistent with rheumatoid arthritis.

Laboratory data:

  • White blood cell count 13.0 × 109/L (reference range 3.7–11.0)
  • Hemoglobin level 10 g/dL (11.5–15)
  • Serum creatinine 1.0 mg/dL (0.7–1.4)
  • Pro-brain-type natriuretic peptide (pro-BNP) level greater than the upper limit of normal.

A chest radiograph is obtained, and the resident radiologist’s preliminary impression is that it is consistent with pulmonary vascular congestion.

The patient is admitted for further diagnostic evaluation. The emergency department resident orders intravenous furosemide and signs out to the night float medicine resident that this is an “elderly woman with hypertension, diabetes, and heart failure being admitted for a heart failure exacerbation.”

What is the accuracy of a physician’s initial working diagnosis?

Diagnostic accuracy requires both clinical knowledge and problem-solving skills.1

A decade ago, a National Patient Safety Foundation survey2 found that one in six patients had suffered a medical error related to misdiagnosis. In a large systematic review of autopsy-based diagnostic errors, the theorized rate of major errors ranged from 8.4% to as high as 24.4%.3 A study by Neale et al4 found that admitting diagnoses were incorrect in 6% of cases. In emergency departments, inaccuracy rates of up to 12% have been described.5

What factors influence the prevalence of diagnostic errors?

Initial empiric treatments, such as intravenous furosemide in the above scenario, add to the challenge of diagnosis in acute care settings and can influence clinical decisions made by subsequent providers.6

Nonspecific or vague symptoms make diagnosis especially challenging. Shortness of breath, for example, is a common chief complaint in medical patients, as in this case. Green et al7 found emergency department physicians reported clinical uncertainty for a diagnosis of heart failure in 31% of patients evaluated for “dyspnea.” Pulmonary embolism and pulmonary tuberculosis are also in the differential diagnosis for our patient, with studies reporting a misdiagnosis rate of 55% for pulmonary embolism8 and 50% for pulmonary tuberculosis.9

Hertwig et al,10 describing the diagnostic process in patients presenting to emergency departments with a nonspecific constellation of symptoms, found particularly low rates of agreement between the initial diagnostic impression and the final, correct one. In fact, the actual diagnosis was only in the physician’s initial “top three” differential diagnoses 29% to 83% of the time.

Atypical presentations of common diseases, initial nonspecific presentations of common diseases, and confounding comorbid conditions have also been associated with misdiagnosis.11 Our case scenario illustrates the frequent challenges physicians face when diagnosing patients who present with nonspecific symptoms and signs on a background of multiple, chronic comorbidities.

Contextual factors in the system and environment contribute to the potential for error.12 Examples include frequent interruptions, time pressure, poor handoffs, insufficient data, and multitasking.

In our scenario, incomplete data, time constraints, and multitasking in a busy work environment compelled the emergency department resident to rapidly synthesize information to establish a working diagnosis. Interpretations of radiographs by on-call radiology residents are similarly at risk of diagnostic error for the same reasons.13

Physician factors also influence diagnosis. Interestingly, physician certainty or uncertainty at the time of initial diagnosis does not uniformly appear to correlate with diagnostic accuracy. A recent study showed that physician confidence remained high regardless of the degree of difficulty in a given case, and degree of confidence also correlated poorly with whether the physician’s diagnosis was accurate.14

For patients admitted with a chief complaint of dyspnea, as in our scenario, Zwaan et al15 showed that “inappropriate selectivity” in reasoning contributed to an inaccurate diagnosis 23% of the time. Inappropriate selectivity, as defined by these authors, occurs when a probable diagnosis is not sufficiently considered and therefore is neither confirmed nor ruled out.

In our patient scenario, the failure to consider diagnoses other than heart failure and the inability to confirm a prior diagnosis of heart failure in the emergency department may contribute to a diagnostic error.

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