Cognitive Biases




  • Patient care example

  1. Scenario: Consider a case of a 24-year-old with known Crohn`s disease suffering from nausea, abdominal pains, and diarrhea. A colonoscopy shows inflammation along the colon wall. His doctor attributes the inflammation to his Crohn’s disease. Further testing indicates that the patient was suffering from Appendicitis.

  2. Buchbinder and Shanks (2011) observed that anchoring bias is a problem since the examiner fails to consider other diagnoses, which possess a high risk to the patient since it causes the possible spread of the condition.

  3. Measures to mitigate this bias may include considering a worst case scenario and obtaining vast information to enable better diagnosis.

  • Healthcare management

  1. Scenario: A manager in a state hospital gets information about the annual salary for a manager in that hospital. During an interaction with the Human resource department, he mentions about the original figure even after he is presented with the more accurate figure.

  2. This situation works to one’s either lead or disadvantage. The contracting manager may decide to adjust to a slightly lower value or increase the figure depending on the direction and degree of the prejudiced figure from the actual figure.

  3. Steps to curb this form of bias include involving HR actively in the exercise, having a well-outlined procedure for the salary negotiations, and acquiring a guiding principle to matters concerning employees’ salaries.


  • Patient care example

  1. Scenario: Consider a young patient with chest pain. Perhaps the clinician of this patient has treated several other patients that day with bronchitis the clinician may be likely to consider bronchitis as a possible cause of the chest pains. However, after better diagnosis, the patient is found to be with significant congenital heart disease and is to be referred to a cardiologist.

  2. Availability bias is a problem since it can lead to multiple misdiagnoses thus endangering many patients’ health and eventually causing further complications (Buchbinder et al., 2011).

  3. Curbing availability bias may include among other measures doctors should try to be aware of the diverse factors that influence a decision or diagnosis.

  • Healthcare management

  1. Scenario: In healthcare management, availability bias occurs when some patients are treated for a particular condition, then the management chooses to stock drugs that can only treat that condition. Such a scenario endangers patients with other conditions.

  2. Availability bias is a problem since it increases patients’ health challenges since the whole health system can be inclined towards one direction (Buchbinder et al., 2011).

  3. Use of proper handling and analysis of trends in the healthcare industry and consideration of multiple probable problems can resolve this issue.

Insensitivityto outcome probabilities

  • Patient care example

  1. Scenario: A 48-year-old cyclist presents shortness of breath after a cycling competition. The cyclist has a trim and muscular body and looks healthy. His physician fails to recognize a possibility of congestive heart failure. Further testing shows a diagnosis of pericarditis, which is later treated through surgery. The doctor makes a mistake of insensitivity to outcome probabilities by ignoring base rate frequencies and perceiving that the cyclist was healthy and fit. His decisions were influenced by the stereotypical image of cyclists being fit.

  2. Insensitivity to outcome probabilities leads to misappropriated diagnosis since the doctor leaves out significant symptoms that direct to better diagnosis.

  3. Doctor`s ability to scrutinize all symptoms and not to leave out the major symptoms can manage this bias. Also, physicians should become familiar with base rates occurrences of a particular disease.

  • Healthcare management

  1. Scenario: In a health service center, samples are interchanged, and results for patients are mixed up. This situation leads to wrong drugs being administered. Since only two lab technicians are on duty, one has to face the consequences. Then the administrator picked on the technician who previously had a late submission of results. Later it was established that the other technician had made the mistake.

  2. In healthcare management, the administrators should learn to isolate events to lower the probability of underestimating low esteemed practitioners to avoid delivery of poor services.

  3. Curbing this problem may involve close follow up on cases and well documentation of records.


  • Patient care example

  1. Scenario: A patient is admitted to hospital with severe pain occurring from multiple Myeloma but the oncologist who attends to her rates very highly his skills to manage pain. However, he is not able to manage it well and leaves the patient suffering from severe pain.

  2. Overconfidence is a problem since it can cause quick diagnosis even when further tests are needed. Also, it can result in doctors continuing to prescribe suboptimal treatment.

  3. Doctors should accept their shortcomings and seek colleagues’ opinions to avoid overconfidence bias.

  • Healthcare management

  1. Scenario: A newly recruited microbiologist approaches the managing director of the firm he works for with an attempt to correct his boss who holds a Ph.D. in the same field and has been practicing for 17 years in the field. The director brushes off the young microbiologist based on his experience. Later on, the new findings from the recruit turn out to be factual.

  2. Overconfidence is a great hindrance for venturing into medical research in previously handled cases especially by Senior and well-experienced practitioners.

  3. This problem can be solved through cohesion amongst all stakeholders within the medical field including the practicing doctors and those in the management level.


Thedecision to settle on something that one feels is positive withoutnecessarily considering its flaws.


Buchbinder,S. B., &amp Shanks, N. H. (2011). Introductionto health care management.Sudbury, MA: Jones and Bartlett.