The importance of understanding patient preferences for life-sustaining treatment is well described for individual clinical decisions; however, its role in evaluations of healthcare outcomes and quality has received little attention. Decisions to limit life-sustaining therapies are strongly associated with high risks for death in ways that are unaccounted for by routine measures of illness severity. However, this essential information is generally unavailable to researchers, with the potential for spurious inferences. This may lead to “confounding by unmeasured patient preferences” (a type of confounding by indication) and has implications for assessments of treatment effectiveness and healthcare quality, especially in acute and critical care settings in which risk for death and adverse events are high. Through a collection of case studies, we explore the effect of unmeasured patient resuscitation preferences on issues critical for researchers and research consumers to understand. We then propose strategies to more consistently elicit, record, and harmonize documentation of patient preferences that can be used to attenuate confounding by unmeasured patient preferences and provide novel opportunities to improve the patient centeredness of medical care for serious illness.