Risk Management Tools & Resources


The Complex Role of Clinical Judgment in Diagnostic Errors

The Complex Role of Clinical Judgment in Diagnostic Errors

Laura M. Cascella, MA, CPHRM

Diagnostic errors are a serious threat to patient safety as well as a significant medical liability concern. MedPro Group malpractice claims data show that diagnosis-related allegations occur across all specialties and healthcare locations. Analysis of the risk factors that contribute to these allegations shows that clinical judgment is, by far, the most prevalent.1

Clinical judgment refers to the thought process (clinical reasoning) that allows healthcare providers to arrive at a conclusion (clinical decision-making) based on objective and subjective information about a patient. An article in the Journal of Evaluation in Clinical Practice explains that "Clinical judgment is developed through practice, experience, knowledge and continuous critical analysis."2

Clinical judgment can involve both automatic, intuitive reasoning and analytic, reflective reasoning. These types of reasoning are not mutually exclusive; they can occur in tandem, and healthcare providers might switch their judgment strategy based on the circumstances they encounter. Because the cognitive processes involved in clinical judgment are complex, they are prone to various cognitive errors, such as faulty heuristics/cognitive biases and affective influences/situativity.3

Faulty Heuristics and Cognitive Biases

Heuristics are mental shortcuts in the thought process that help conserve time and effort. These shortcuts are an essential part of thinking, but they also are prone to errors. Cognitive biases occur when heuristics lead to faulty decision-making.4 Some common biases include those listed below:

  • Anchoring refers to a tendency to "anchor" to, or rely too much on, a particular piece of information — often the initial information obtained, the first symptom, or the first lab abnormality.
  • Under-adjustment is the inability to revise a diagnosis based on additional clinical data.
  • Premature closure refers to terminating the data-gathering process (e.g., patient history, family history, and medication list) before all of the information is known.
  • Primacy effect, similar to anchoring, refers to a tendency to show bias toward initial information.
  • Confirmation refers to the tendency to focus on information that confirms an initial diagnosis or to manipulate information to fit preconceptions.
  • Availability can occur if a clinician considers a diagnosis more likely because it easily comes to mind. Past experience and recent, frequent, or prominent cases can all play a role in availability bias.
  • Framing effect refers to perceiving a narrative in the way in which it is framed or presented.
  • Sunk cost refers to maintaining a diagnosis because of the time and effort invested.
  • Overconfidence refers to an overestimation of an individual's own knowledge and skills as well as an inability to identify knowledge gaps. Overconfidence bias might result from a lack of feedback related to diagnostic accuracy, which may cause clinicians to overestimate their diagnostic precision. To this point, researchers suggest that overconfidence might increase as a doctor's level of expertise increases.5

Affective Influences/Situativity

Whereas cognitive biases are lapses in thinking, affective influences are emotions and feelings that can sway clinical judgment.6 Preconceived notions and stereotypes about a patient might influence how a healthcare provider views the patient's complaints and symptoms. For example, if a patient has a history of substance abuse, the provider might view complaints about pain as drug-seeking behavior. Although this impulse might be accurate, the patient could potentially have a legitimate clinical issue.

Additionally, negative feelings about patients might cause providers to consciously or subconsciously blame patients for their symptoms or conditions — a bias called attribution error. For example, a provider may attribute a patient's obesity to laziness or general disregard for health and wellness. Similarly, a patient who does not adhere to their care plan might be viewed as difficult — in reality, though, the nonadherence might be related to financial issues or another cause. Elderly patients also might be vulnerable to attribution errors because clinicians have a tendency to attribute these patients' symptoms to advancing age, rather than exploring other potential causes.7

Positive feelings about patients also can affect diagnostic decisions. In outcome bias, for example, a provider might overlook certain clinical data in order to select a diagnosis with better outcomes. By doing so, the clinician is placing more value on what they hope will happen, rather than what might realistically happen.

Beyond positive and negative feelings about patients, clinician and patient characteristics — such as age, gender, socioeconomic status, and ethnicity — also can affect the diagnostic process. For example, research has shown that various implicit and explicit biases related to race, ethnicity, and gender can affect pain management decisions.8

A variety of other factors also can affectively influence a clinician's reasoning, such as:

  • Environmental circumstances, e.g., high levels of noise or frequent interruptions
  • Sleep deprivation, irritability, fatigue, and stress
  • Mood disorders, mood variations, and anxiety disorders9

More recent research continues to expand the understanding of cognition and clinical reasoning by viewing them through the lens of situativity. "Situativity" is an umbrella term that describes a series of cognitive theories that examine clinical judgment and reasoning in the context of the situations in which they occur.

These theories move "beyond individual beliefs and knowledge construction to consider those present during the encounter (e.g., the patient and his/her family members, other health care workers, learners), the multiple environmental inputs (e.g. appointment length, artifacts such as electronic health record [EHR] functionality, culture), and their dynamic interactions."10

In Summary

The complex interaction between cognitive biases, affective influences, and clinical context can have a profound effect on clinical reasoning and decision-making, which in turn can lead to lapses in clinical judgment and diagnostic errors.

To learn more about the role of clinical judgment in diagnostic errors, including strategies to help improve the diagnostic decision-making process, see MedPro's article Clinical Judgment in Diagnostic Errors: Let's Think About Thinking, the Society to Improve Diagnosis in Medicine's Clinical Reasoning Toolkit, and the Agency for Healthcare Research and Quality's Diagnostic Safety and Quality website.


1 MedPro Group. (2022). Diagnostic errors: Contributing factors and risk strategies (a 10-year claims analysis). Retrieved from www.medpro.com/diagnostic-errors-contributing-factors-od

2 Kienle, G. S., & Kiene, H. (2011, August). Clinical judgment and the medical profession. Journal of Evaluation in Clinical Practice, 17(4), 621–627.

3 Phua, D. H., & Tan, N. C. (2013). Cognitive aspect of diagnostic errors. Annals of the Academy of Medicine, Singapore, 42(1), 33–41; Merkebu, J., Battistone, M., McMains, K., McOwen, K., Witkop, C., Konopasky, A., Torre, D., . . . Durning, S. J. (2020). Situativity: a family of social cognitive theories for understanding clinical reasoning and diagnostic error. Diagnosis, 7(3), 169–176. doi: https://doi.org/10.1515/dx-2019-0100

4 Phua, et al., Cognitive aspect of diagnostic errors.

5 Clark, C. (2013, August 27). Physicians' diagnostic overconfidence may be harming patients. HealthLeaders Media. Retrieved from www.healthleadersmedia.com/clinical-care/physicians-diagnostic-overconfidence-may-be-harming-patients; Phua, et al., Cognitive aspect of diagnostic errors.

6 Crosskerry, P., Abbass, A. A., & Wu, A. W. (2008, October). How doctors feel: Affective influences in patient's safety. Lancet, 372, 1205–1206; Phua, et al. Cognitive aspect of diagnostic errors.

7 Smith, W., Elkin, D., & Walaszek, A. (2023, October). How to draw on narrative to mitigate ageism. AMA Journal of Ethics, 25(10), E745–750. doi: 10.1001/amajethics.2023.745.

8 Campbell, C. M., & Edwards, R. R. (2012). Ethnic differences in pain and pain management. Pain Management, 2(3), 219–230; Drwecki, B. B. (2015, March). Education to identify and combat racial bias in pain treatment. AMA Journal of Ethics, 17(3), 221–228; Fassler, J. (2015, October 15). How doctors take women's pain less seriously. The Atlantic. Retrieved from www.theatlantic.com/health/archive/2015/10/emergency-room-wait-times-sexism/410515/; Hoffman, D. E., & Tarzian, A. J. (2001). The girl who cried pain: A bias against women in the treatment of pain. Journal of Law, Medicine, and Ethics, 29, 13-27.

9 Crosskerry, P., et al., How doctors feel.

10 Merkebu, et al., Situativity: A family of social cognitive theories for understanding clinical reasoning and diagnostic error.

MedPro Twitter


View more on Twitter