Many service systems have servers with different capabilities and customers with varying needs. One common way this occurs is when servers are hierarchical in their skills or in the level of service they can provide. Much of the literature studying such systems relies on an understanding of the relative costs and benefits associated with serving different customer types by the different levels of service. In this work, we focus on estimating these costs and benefits in a complex healthcare setting where the major differentiation among server types is the intensity of service provided. Step-down units (SDUs) were initially introduced in hospitals to provide an intermediate level of care for semicritically ill patients who are not sick enough to require intensive care but not stable enough to be treated in the general medical/surgical ward. One complicating factor is that the needs of customers is sometimes uncertain—specifically, it is difficult to know a priori which level of care a particular patient needs. Using data from 10 hospitals from a single hospital network, we take a data-driven approach to classify patients based on severity and empirically estimate the clinical and operational outcomes associated with routing these patients to the SDU. Our findings suggest that an SDU may be a cost-effective way to treat patients when used for patients who are post-ICU (intensive care unit). However, the impact of SDU care is more nuanced for patients admitted from the emergency department and may result in increased mortality risk and hospital length of stay for patients who should be treated in the ICU. Our results imply that more study is needed when using SDU care this way.