title: Dual Processing Model for Medical Decision-Making: An Extension to Diagnostic Testing.
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.
authors.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.
authors.forename: Athanasios
authors.initials: A
authors.lastname: Tsalatsanis
authors.affiliation: Department of Mathematics, Indiana University of Northwest, Gary, IN, United States of America.
authors.forename: Iztok
authors.initials: I
authors.lastname: Hozo
authors.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.
authors.forename: Ambuj
authors.initials: A
authors.lastname: Kumar
authors.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; Departments of Hematology and Health Outcomes and Behavior, H. Lee Moffitt Cancer Center & Research Institute, Tampa, FL, United States of America.
authors.forename: Benjamin
authors.initials: B
authors.lastname: Djulbegovic
mesh_terms: D000368:Aged; D001706:Biopsy / Q000009:adverse effects; D000066491:Clinical Decision-Making / Q000379:methods*; D003661:Decision Support Techniques; D019468:Disease Management; D019317:Evidence-Based Medicine; D006801:Humans; D008297:Male; D015233:Models, Statistical; D011336:Probability; D011467:Prostate / Q000473:pathology* / Q000601:surgery; D011468:Prostatectomy / Q000009:adverse effects; D011471:Prostatic Neoplasms / Q000175:diagnosis* / Q000601:surgery / Q000628:therapy*