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Digital smartphone maps have transformed personal travel. Trips that previously required atlases, written instructions, or memorized directions now occur effortlessly. At the same time, the way that we interact with the world has been fundamentally altered by the rise of global positioning systems. More often than not, our increasing dependence on technology has made driving safer and more convenient, though notable exceptions exist (1). Unlike most of our daily commutes, patients discharged from the intensive care unit (ICU) to the general medical ward face a perilous journey. Patients leave the relative “safety” of the ICU and must traverse dangerous obstacles, such as the lack of standardized ICU discharge criteria, the transition to lower-resourced settings, and multiple care handoffs with the potential for communication failures. Each step can result in patient harm (2). It is no surprise, then, that readmissions to the ICU occur, with rates in the literature generally ranging between 4% and 14% (3, 4). Readmissions are important because they have been associated with mortality and increased hospital length of stay (5). Sometimes, ICU readmissions could have been preventable. For example, diagnostic or management errors are unfortunately common and may have been avoided. On the other hand, older age, higher sequential organ failure assessment (SOFA) score, presence of infection, severe disease, immunodeficiency, and vasopressor use are widely considered predictors of ICU readmission (6). These largely nonmodifiable patient factors call into question whether ICU readmissions are a meaningful indicator of quality of care (6). Similar to conventional wisdom for endotracheal reintubations, a certain proportion of ICU readmissions must be tolerated (7). An ICU readmission rate of 0% suggests that patients are being sheltered in the ICU for an unnecessarily long period of time, inflating ICU census, workload, and hampering healthcare efficiency. On the other hand, when ICU readmissions are excessive, patients are being transferred out of the ICU too early (i.e., when they could still benefit from ICU-level care). Despite this complexity, no widely accepted criteria for ICU discharge exists, and ICU discharge decisions are left to clinician discretion. Although literature exists regarding clinicians’ ability to predict mortality, clinicians’ accuracy for predicting ICU readmissions has not been previously studied (4, 8, 9). In this issue of AnnalsATS, Rojas and colleagues (pp. 847–853) conducted a prospective study to examine how well clinicians can predict ICU readmission (10). ICU nurses, residents, fellows, and attendings were surveyed to assess three outcomes: readmission within 48 hours of ICU discharge, readmission at any time, and in-hospital mortality. The authors hypothesized that, on average, clinicians would have poor accuracy in predicting early ICU readmission but that clinicians with more experience would be more accurate than those with less experience. The authors surveyed 2,833 clinicians for 938 ICU transfers, and 4% of patients experienced a readmission to the ICU with a median time to readmission of 82 hours. They found that clinicians, regardless of experience, had only fair accuracy for predicting ICU readmission within 48 hours. Nurses were narrowly the most accurate, followed by residents, attendings, fellows, and interns. Overall, clinicians were felt to have limited ability to predict which patients would be readmitted to the ICU. Interestingly, clinicians in this study were better at predicting mortality than readmissions. This seems problematic because previous studies have shown that clinicians are not very good at predicting mortality (8). In one study, about half of ICU patients survived the hospitalization despite predictions that they would die (9). We believe it is not particularly surprising that clinicians are better at predicting mortality than readmissions. First, most clinical training is intensely focused on identifying patients at high risk of death, rather than patients at high risk of

Navigating Discharges from Intensive Care Unit to Ward