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Acad Med. 2010 Mar;85(3):556-63. doi: 10.1097/ACM.0b013e3181ccd59b.

Perspective: Uses and misuses of thresholds in diagnostic decision making.

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1
Division of Hematology and Oncology, Beth Israel Deaconess Medical Center, Boston, Massachusetts, USA. jlwarner@bidmc.harvard.edu

Abstract

The concept of thresholds plays a vital role in decisions involving the initiation, continuation, and completion of diagnostic testing. Much research has focused on the development of explicit thresholds, in the form of practice guidelines and decision analyses. However, these tools are used infrequently; most medical decisions are made at the bedside, using implicit thresholds. Study of these thresholds can lead to a deeper understanding of clinical decision making. The authors examine some factors constituting individual clinicians' implicit thresholds. They propose a model for static thresholds using the concept of situational gravity to explain why some thresholds are high, and some low. Next, they consider the hypothetical effects of incorrect placement of thresholds (miscalibration) and changes to thresholds during diagnosis (manipulation). They demonstrate these concepts using common clinical scenarios. Through analysis of miscalibration of thresholds, the authors demonstrate some common maladaptive clinical behaviors, which are nevertheless internally consistent. They then explain how manipulation of thresholds gives rise to common cognitive heuristics including premature closure and anchoring. They also discuss the case where no threshold has been exceeded despite exhaustive collection of data, which commonly leads to application of the availability or representativeness heuristics. Awareness of implicit thresholds allows for a more effective understanding of the processes of medical decision making and, possibly, to the avoidance of detrimental heuristics and their associated medical errors. Research toward accurately defining these thresholds for individual physicians and toward determining their dynamic properties during the diagnostic process may yield valuable insights.

PMID:
20182138
DOI:
10.1097/ACM.0b013e3181ccd59b
[Indexed for MEDLINE]
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