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Dual Processing Model for Medical Decision-Making: An Extension to Diagnostic Testing.

Tsalatsanis A, Hozo I, Kumar A, Djulbegovic B - PLoS ONE (2015)

Bottom Line: The DPM model indicates that doctors decide to treat when treatment benefits outweigh its harms, which occurs when the probability of the disease is greater than the so called "threshold probability" at which treatment benefits are equal to treatment harms.This is because such decisions depend on objective evidence of test/treatment benefits and harms as well as type 1 cognition of benefits and harms, which are not considered under EUT.These findings could explain variations in the treatment and diagnostic patterns documented in today's clinical practice.

View Article: PubMed Central - PubMed

Affiliation: Comparative Effectiveness Research, University of South Florida, Tampa, FL, United States of America; Department of Internal Medicine, University of South Florida, Tampa, FL, United States of America.

ABSTRACT
Dual Processing Theories (DPT) assume that human cognition is governed by two distinct types of processes typically referred to as type 1 (intuitive) and type 2 (deliberative). Based on DPT we have derived a Dual Processing Model (DPM) to describe and explain therapeutic medical decision-making. The DPM model indicates that doctors decide to treat when treatment benefits outweigh its harms, which occurs when the probability of the disease is greater than the so called "threshold probability" at which treatment benefits are equal to treatment harms. Here we extend our work to include a wider class of decision problems that involve diagnostic testing. We illustrate applicability of the proposed model in a typical clinical scenario considering the management of a patient with prostate cancer. To that end, we calculate and compare two types of decision-thresholds: one that adheres to expected utility theory (EUT) and the second according to DPM. Our results showed that the decisions to administer a diagnostic test could be better explained using the DPM threshold. This is because such decisions depend on objective evidence of test/treatment benefits and harms as well as type 1 cognition of benefits and harms, which are not considered under EUT. Given that type 1 processes are unique to each decision-maker, this means that the DPM threshold will vary among different individuals. We also showed that when type 1 processes exclusively dominate decisions, ordering a diagnostic test does not affect a decision; the decision is based on the assessment of benefits and harms of treatment. These findings could explain variations in the treatment and diagnostic patterns documented in today's clinical practice.

No MeSH data available.


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Relation between the probability of disease and the threshold probabilities for testing and treatment (adopted from [3]).
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pone.0134800.g001: Relation between the probability of disease and the threshold probabilities for testing and treatment (adopted from [3]).

Mentions: According to the threshold model [1,2], when faced with a choice of observing the patient, ordering a diagnostic test, or administering treatment, there is a probability of disease, also known as threshold probability, at which a decision maker is indifferent between any two choices (e.g. treating vs. ordering a test, or ordering a test vs. withholding treatment) [3–6]. Furthermore, decisions involving diagnostic testing rely on two probabilities of disease known as testing and treatment thresholds. Testing threshold relates to the decision about ordering a test vs. observing a patient and treatment threshold relates to the decision about administering treatment vs. ordering the diagnostic test. According to the threshold model [1,2], if the probability of disease is smaller than the testing threshold, the test should be withheld. If the probability of disease is above the treatment threshold, then treatment should be ordered without ordering a diagnostic test. The test should only be ordered if the estimated probability of the disease is between the testing and treatment thresholds (Fig 1).


Dual Processing Model for Medical Decision-Making: An Extension to Diagnostic Testing.

Tsalatsanis A, Hozo I, Kumar A, Djulbegovic B - PLoS ONE (2015)

Relation between the probability of disease and the threshold probabilities for testing and treatment (adopted from [3]).
© Copyright Policy
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4526559&req=5

pone.0134800.g001: Relation between the probability of disease and the threshold probabilities for testing and treatment (adopted from [3]).
Mentions: According to the threshold model [1,2], when faced with a choice of observing the patient, ordering a diagnostic test, or administering treatment, there is a probability of disease, also known as threshold probability, at which a decision maker is indifferent between any two choices (e.g. treating vs. ordering a test, or ordering a test vs. withholding treatment) [3–6]. Furthermore, decisions involving diagnostic testing rely on two probabilities of disease known as testing and treatment thresholds. Testing threshold relates to the decision about ordering a test vs. observing a patient and treatment threshold relates to the decision about administering treatment vs. ordering the diagnostic test. According to the threshold model [1,2], if the probability of disease is smaller than the testing threshold, the test should be withheld. If the probability of disease is above the treatment threshold, then treatment should be ordered without ordering a diagnostic test. The test should only be ordered if the estimated probability of the disease is between the testing and treatment thresholds (Fig 1).

Bottom Line: The DPM model indicates that doctors decide to treat when treatment benefits outweigh its harms, which occurs when the probability of the disease is greater than the so called "threshold probability" at which treatment benefits are equal to treatment harms.This is because such decisions depend on objective evidence of test/treatment benefits and harms as well as type 1 cognition of benefits and harms, which are not considered under EUT.These findings could explain variations in the treatment and diagnostic patterns documented in today's clinical practice.

View Article: PubMed Central - PubMed

Affiliation: Comparative Effectiveness Research, University of South Florida, Tampa, FL, United States of America; Department of Internal Medicine, University of South Florida, Tampa, FL, United States of America.

ABSTRACT
Dual Processing Theories (DPT) assume that human cognition is governed by two distinct types of processes typically referred to as type 1 (intuitive) and type 2 (deliberative). Based on DPT we have derived a Dual Processing Model (DPM) to describe and explain therapeutic medical decision-making. The DPM model indicates that doctors decide to treat when treatment benefits outweigh its harms, which occurs when the probability of the disease is greater than the so called "threshold probability" at which treatment benefits are equal to treatment harms. Here we extend our work to include a wider class of decision problems that involve diagnostic testing. We illustrate applicability of the proposed model in a typical clinical scenario considering the management of a patient with prostate cancer. To that end, we calculate and compare two types of decision-thresholds: one that adheres to expected utility theory (EUT) and the second according to DPM. Our results showed that the decisions to administer a diagnostic test could be better explained using the DPM threshold. This is because such decisions depend on objective evidence of test/treatment benefits and harms as well as type 1 cognition of benefits and harms, which are not considered under EUT. Given that type 1 processes are unique to each decision-maker, this means that the DPM threshold will vary among different individuals. We also showed that when type 1 processes exclusively dominate decisions, ordering a diagnostic test does not affect a decision; the decision is based on the assessment of benefits and harms of treatment. These findings could explain variations in the treatment and diagnostic patterns documented in today's clinical practice.

No MeSH data available.


Related in: MedlinePlus