Case Study: Failure to Diagnose Myocardial Infarction Leads to Tragic Outcome
A 47-year-old female presented to her local emergency department (ED) on a Saturday evening with complaints of shoulder discomfort, back pain, nausea, dizziness, and chest tightness. The woman reported that she had spent the morning working in her garden and then attended a family cookout.
An ECG was ordered, and the results were negative. The patient was not referred for further cardiac testing because the emergency physician felt that muscle strain and acid reflux were the cause of the patient's symptoms.
The patient was discharged from the ED and returned home. Two days later, she was found unresponsive in her home and rushed to the hospital, where she died. An autopsy concluded that the cause of death was myocardial infarction (MI) due to atherosclerotic cardiovascular disease.
DiscussionDiagnostic errors are a serious, although sometimes overlooked, problem in healthcare. Outpatient studies suggest that about 1 in 20 U.S. adults experience diagnostic errors each year, and these errors contribute to about 10 percent of patient deaths. Further, medical record reviews show that diagnostic errors are responsible for 6–17 percent of adverse events in hospitals.1 Malpractice claims analyses also are revealing — diagnostic errors account for the largest percentage of malpractice claims and represent the most severe clinical and financial outcomes.2
Various factors can contribute to diagnostic errors. One of the most prevalent is clinical judgment, a complex process that involves various cognitive functions and is potentially vulnerable to a variety of cognitive biases. The case in this example illustrates how potential lapses in clinical judgment can lead to a diagnostic error with a profound outcome. In this particular case, more than one cognitive bias might have been at play. For example, a cognitive bias known as "anchoring" might explain the emergency physician's initial diagnoses.
Anchoring refers to a snap judgment or tendency to diagnose based on the first symptom or lab abnormality.3 Knowing that the patient had spent the morning gardening and later attended a cookout, the emergency physician honed in on muscle strain and acid reflux as the likely causes of the patient's symptoms. The negative ECG results reinforced the physician’s narrow diagnostic focus. As a result, the doctor did not order further testing and prematurely terminated the data-gathering process.
As it turns out, the patient was a heavy smoker and had high cholesterol. She also had a family history of cardiovascular disease, and both her mother and brother died in their early fifties. Further investigation would have likely revealed these details.
In addition to anchoring, another type of bias called an affective influence might have contributed to the faulty clinical judgment in this case. An affective influence refers to emotions or feelings that can sway clinical reasoning.4 These emotions or feelings might relate to patient characteristics like age, gender, ethnicity, and/or socio-economic status.
In this case, for instance, the emergency physician might have prematurely ruled out MI because of the patient's young age and the fact that she was female. Research has shown that both age and gender play a role in the misdiagnosis of cardiac conditions. A study in the New England Journal of Medicine noted that female sex combined with an age of less than 55 years was a risk factor for not hospitalizing patients presenting to the ED with acute cardiac ischemia.5
Although cognitive processes and biases are well-studied, further research is needed to determine how best to prevent the flaws in clinical judgment that can lead to diagnostic errors. However, a number of strategies — such as decision support systems, clinical pathways, checklists, reflective practice, and cognitive awareness — show promise. By considering how to implement these strategies in everyday clinical activities, healthcare providers can begin to take steps toward managing diagnostic risks.
A helpful resource is the Society to Improve Diagnosis in Medicine’s Clinical Reasoning Toolkit for trainees, clinicians, and teachers. The toolkit supports awareness and better understanding of diagnostic reasoning, cognitive psychology, and diagnostic errors. Resources within the toolkit include links to books and articles, slide presentations, and videos focusing on clinical reasoning and cognitive errors.
Endnotes
1 Singh, H., & Graber, M. L. (2015, November). Improving diagnosis in health care — The next imperative. New England Journal of Medicine, 373, 2493–2495; The Institute of Medicine. (2015, September). Improving diagnosis in healthcare (Report in Brief). Washington, DC: National Academies Press; Bixenstine, P. J., Shore, A. D., Mehtsun, W. T., Ibrahim, A. M., Freischlag, J. A., & Makary, M. A. (2014). Catastrophic medical malpractice payouts in the United States. Journal of Healthcare Quality, 36(4), 43–53. doi:10.1111/jhq.12011
2 Society to Improve Diagnosis in Medicine. (n.d.). What is diagnostic error? Retrieved from www.improvediagnosis.org/what-is-diagnostic-error/
3 Phua, D. H., & Tan, N. C. (2013). Cognitive aspect of diagnostic errors. Annals of the Academy of Medicine, Singapore, 42(1), 33–41.
4 Crosskerry, P., Abbass, A. A., & Wu, A. W. (2008, October). How doctors feel: Affective influences in patient's safety. Lancet, 372, 1205–1206.
5 Pope, J. H., Aufderheide, T. P., Ruthazer, R., et al. (2000, April). Missed diagnoses of acute cardiac ischemia in the emergency department. New England Journal of Medicine, 342, 1163–1170.
MedPro 
