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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.


Related in: MedlinePlus

Decision tree describing a typical scenario in which a physician is considering administering (Rx) / withholding treatment (NoRx) to/from his patient.xi represents an outcome; γ is the involvement of type 1 in the decision process; p is the probability of disease; UI,i is the utility of the outcome xi under type 1 process; UII,i is the utility of outcome xi under type 2 processes; The valuation of an outcome xi under type 1 is estimated as the regret associated with the outcome xi; the valuation of an outcome xi under type 2 is estimated as the utility of the outcome xi ([12] for details).
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pone.0134800.g002: Decision tree describing a typical scenario in which a physician is considering administering (Rx) / withholding treatment (NoRx) to/from his patient.xi represents an outcome; γ is the involvement of type 1 in the decision process; p is the probability of disease; UI,i is the utility of the outcome xi under type 1 process; UII,i is the utility of outcome xi under type 2 processes; The valuation of an outcome xi under type 1 is estimated as the regret associated with the outcome xi; the valuation of an outcome xi under type 2 is estimated as the utility of the outcome xi ([12] for details).

Mentions: DPM [12] assumes that the valuation of a risky choice is formed as the combination of type 1 and type 2 processes. To demonstrate, consider a clinical scenario (Fig 2) in which a decision maker is faced with a choice of treating (Rx) or not (NoRx) of a patient who has a disease with probability p. Each decision results in a specific outcome xi. For example, outcome x1 corresponds to the decision of treating a patient who had a disease and outcome x2 corresponds to the decision of treating a patient who did not have a disease. The parameters and correspond to valuations of the outcome xi when the decision maker employs type 1 and 2 processes respectively. Each outcome is also associated with type 1, UI,i ≥ 0, and type 2, UII,i ≥ 0, utilities.


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

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

Decision tree describing a typical scenario in which a physician is considering administering (Rx) / withholding treatment (NoRx) to/from his patient.xi represents an outcome; γ is the involvement of type 1 in the decision process; p is the probability of disease; UI,i is the utility of the outcome xi under type 1 process; UII,i is the utility of outcome xi under type 2 processes; The valuation of an outcome xi under type 1 is estimated as the regret associated with the outcome xi; the valuation of an outcome xi under type 2 is estimated as the utility of the outcome xi ([12] for details).
© Copyright Policy
Related In: Results  -  Collection

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

pone.0134800.g002: Decision tree describing a typical scenario in which a physician is considering administering (Rx) / withholding treatment (NoRx) to/from his patient.xi represents an outcome; γ is the involvement of type 1 in the decision process; p is the probability of disease; UI,i is the utility of the outcome xi under type 1 process; UII,i is the utility of outcome xi under type 2 processes; The valuation of an outcome xi under type 1 is estimated as the regret associated with the outcome xi; the valuation of an outcome xi under type 2 is estimated as the utility of the outcome xi ([12] for details).
Mentions: DPM [12] assumes that the valuation of a risky choice is formed as the combination of type 1 and type 2 processes. To demonstrate, consider a clinical scenario (Fig 2) in which a decision maker is faced with a choice of treating (Rx) or not (NoRx) of a patient who has a disease with probability p. Each decision results in a specific outcome xi. For example, outcome x1 corresponds to the decision of treating a patient who had a disease and outcome x2 corresponds to the decision of treating a patient who did not have a disease. The parameters and correspond to valuations of the outcome xi when the decision maker employs type 1 and 2 processes respectively. Each outcome is also associated with type 1, UI,i ≥ 0, and type 2, UII,i ≥ 0, utilities.

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