Related Experiment Video
Updated: Jul 5, 2026
06:16
Signal Acquisition, Score Interpretation, and Economics of a Non-Invasive Point-of-Care Test for Coronary Artery Disease
Published on: August 9, 2024
When is diagnostic testing inappropriate or irrational? Acceptable regret approach.
Iztok Hozo1, Benjamin Djulbegovic
1Department of Mathematics, Indiana University Northwest, Gary, IN, USA.
Summary
Physicians
Area of Science:
- Decision-making in medicine
- Behavioral economics
- Medical practice variations
Background:
- Physicians' diagnostic test ordering behavior is often perceived as irrational.
- Existing models do not fully explain observed clinical practices.
- Theories of bounded rationality offer a potential framework for understanding these behaviors.
Purpose of the Study:
- To propose a new model of physician test ordering behavior based on bounded rationality.
- To challenge the notion that physicians act irrationally in clinical practice.
- To explain variations in medical decision-making.
Main Methods:
- Modeling physician decision-making within the framework of bounded rationality.
- Incorporating the concept of 'acceptable regret' into decision models.
- Analyzing the impact of varying regret thresholds on test ordering behavior.
Main Results:
- Physicians order diagnostic tests at higher pretest probabilities of disease than predicted by expected utility theory when acceptable regret is considered.
- Overtesting occurs when the regret associated with erroneous decisions is minimal.
- Individual differences in acceptable regret explain variations in clinical practice and decision-making.
Conclusions:
- Physician test ordering behavior can be rational under bounded rationality, accounting for acceptable regret.
- The concept of acceptable regret explains deviations from purely rational models and variations in practice.
- Different acceptable regret thresholds lead to diverse, yet rational, clinical strategies.
Related Concept Videos
01:14Errors In Hypothesis Tests
When performing a hypothesis test, there are four possible outcomes depending on the actual truth (or falseness) of the null hypothesis and the decision to reject or not.
01:00Detection of Gross Error: The Q Test
When one or more data points appear far from the rest of the data, there is a need to determine whether they are outliers and whether they should be eliminated from the data set to ensure an accurate representation of the measured value. In many cases, outliers arise from gross errors (or human errors) and do not accurately reflect the underlying phenomenon. In some cases, however, these apparent outliers reflect true phenomenological differences. In these cases, we can use statistical methods...
01:24Rational Emotive Behavior Therapy
Cognitive-behavioral therapies (CBTs) are grounded in the belief that our thoughts profoundly influence our emotions and actions. Advocates of CBT emphasize three core assumptions: first, that cognitions are identifiable and measurable; second, that they are central to psychological functioning; and third, that irrational or maladaptive beliefs can be replaced with rational and adaptive ones. This transformative approach to therapy has paved the way for specific models such as Albert Ellis's...
01:10Documentation of Nursing Diagnosis
The nurse documents nursing diagnoses and enters them into the patient record. The identified patient's nursing diagnosis is either written out with a plan of care or entered into the electronic health record.
In some settings, data-driven computerized decision support systems are in place, allowing for more accurate nursing diagnoses. The database within one of these systems includes diagnostic labels defining characteristics, activities, and indicators for nursing. A nurse enters assessment...
In some settings, data-driven computerized decision support systems are in place, allowing for more accurate nursing diagnoses. The database within one of these systems includes diagnostic labels defining characteristics, activities, and indicators for nursing. A nurse enters assessment...
01:17Hypothesis: Accept or Fail to Reject?
The outcome of any hypothesis testing leads to rejecting or not rejecting the null hypothesis. This decision is taken based on the analysis of the data, an appropriate test statistic, an appropriate confidence level, the critical values, and P-values. However, when the evidence suggests that the null hypothesis cannot be rejected, is it right to say, 'Accept' the null hypothesis?
There are two ways to indicate that the null hypothesis is not rejected. 'Accept' the null hypothesis and 'fail to...
There are two ways to indicate that the null hypothesis is not rejected. 'Accept' the null hypothesis and 'fail to...
01:14Decision Making: Traditional Method
The process of hypothesis testing based on the traditional method includes calculating the critical value, testing the value of the test statistic using the sample data, and interpreting these values.
First, a specific claim about the population parameter is decided based on the research question and is stated in a simple form. Further, an opposing statement to this claim is also stated. These statements can act as null and alternative hypotheses, out of which a null hypothesis would be a...
First, a specific claim about the population parameter is decided based on the research question and is stated in a simple form. Further, an opposing statement to this claim is also stated. These statements can act as null and alternative hypotheses, out of which a null hypothesis would be a...