Balancing benefit, harm, and uncertainty in diagnosis: determining the testing threshold in clinical practice

Decision making related to diagnostic testing is central to the daily practice of clinical medicine. The decision to obtain or defer certain diagnostic testing can be straightforward in some cases but more nuanced in others. Explicit use of testing thresholds can aid in the decision-making process. First described by Kassirer and colleagues, the testing threshold is that value of the pretest probability that the patient has a particular disease above which performing a given test is expected to provide net benefit. Here we propose a novel framework for analyzing the testing threshold, which includes both patient-specific variables and variables related to broader systems and contexts. Patient-related variables include the amplitude of the symptom or clinical abnormality, time course and pattern of evolution, and the patient's values and preferences. Broader systemic influences include the overall medical context and competing priorities, health-systems costs and logistical considerations, and public health concerns. The testing threshold can also vary depending on the inherent quality, cost, or precision of the diagnostic test itself. Testing thresholds are important for guiding clinicians in making decisions about pursuing specific testing to make diagnoses and deliver high-value care. Testing thresholds are inherently dynamic and should be calibrated as clinical circumstances evolve.