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When is rational to order a diagnostic test, or prescribe treatment: the threshold model as an explanation of practice variation
Author(s) -
Djulbegovic Benjamin,
Ende Jef,
Hamm Robert M.,
Mayrhofer Thomas,
Hozo Iztok,
Pauker Stephen G.
Publication year - 2015
Publication title -
european journal of clinical investigation
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.164
H-Index - 107
eISSN - 1365-2362
pISSN - 0014-2972
DOI - 10.1111/eci.12421
Subject(s) - regret , rationality , credibility , action (physics) , expected utility hypothesis , variation (astronomy) , order (exchange) , actuarial science , medicine , psychology , risk analysis (engineering) , computer science , economics , epistemology , philosophy , physics , mathematical economics , finance , quantum mechanics , machine learning , astrophysics
Background The threshold model represents an important advance in the field of medical decision‐making. It is a linchpin between evidence (which exists on the continuum of credibility) and decision‐making (which is a categorical exercise – we decide to act or not act). The threshold concept is closely related to the question of rational decision‐making. When should the physician act, that is order a diagnostic test, or prescribe treatment? The threshold model embodies the decision theoretic rationality that says the most rational decision is to prescribe treatment when the expected treatment benefit outweighs its expected harms. However, the well‐documented large variation in the way physicians order diagnostic tests or decide to administer treatments is consistent with a notion that physicians' individual action thresholds vary. Methods We present a narrative review summarizing the existing literature on physicians' use of a threshold strategy for decision‐making. Results We found that the observed variation in decision action thresholds is partially due to the way people integrate benefits and harms. That is, explanation of variation in clinical practice can be reduced to a consideration of thresholds. Limited evidence suggests that non‐expected utility threshold (non‐ EUT ) models, such as regret‐based and dual‐processing models, may explain current medical practice better. However, inclusion of costs and recognition of risk attitudes towards uncertain treatment effects and comorbidities may improve the explanatory and predictive value of the EUT ‐based threshold models. Conclusions The decision when to act is closely related to the question of rational choice. We conclude that the medical community has not yet fully defined criteria for rational clinical decision‐making. The traditional notion of rationality rooted in EUT may need to be supplemented by reflective rationality, which strives to integrate all aspects of medical practice – medical, humanistic and socio‐economic – within a coherent reasoning system.