Knowing Less After a Diagnostic Test: Dilation in Clinical Decision-Making

Joint with Gabriel Ziegler.

Abstract: Dilation (Seidenfeld and Wasserman 1993) occurs when conditioning on new information only increases uncertainty regardless of what the information reveals. This paper shows that following established clinical guidance can induce dilation, even for diagnostic tests that meet conventional performance benchmarks. We characterize when a test is dilation-inducing and show that a ubiquitous feature of performance studies – evaluating tests against an imperfect reference – creates scope for dilation. To facilitate detection before clinical use and inform regulatory standards, we develop a finite-sample valid hypothesis test of the null that a diagnostic test is dilation-inducing in this context. Applying the method to an influential study that recommended chest CT scans for COVID-19 detection and contributed to their clinical adoption, we find that the data are consistent with dilation.