The health-related impact of disruptions in cancer care and the Waiting Time Paradox

Healthcare system disruptions, such as that caused by the COVID-19 pandemic, can lead to delays in, or lag time to, cancer diagnosis and treatment. In order to quantify the negative impact of disruptions such as this on the health of populations, a better grasp on biases that might affect estimation of effects of diagnosis or treatment delays on clinical outcomes is needed. Here, we discuss some of the methodological difficulties in these analyses, including those posed by what has been referred to as the Waiting Time Paradox. In doing so, we define the effect of lag time using potential outcomes, describe evidence for the Waiting Time Paradox, and present directed acyclic graphs to characterize different contexts when it might occur. Although our discussion is motivated by disruptions in cancer care, accurate quantification of lag time's effect would be valuable for the study of other medical conditions and different types of medical service inefficiencies, as well as in settings where policy changes to minimize waiting time are considered.