Are Mortality and Acute Morbidity in Patients Presenting With Nonspecific Complaints Predictable Using Routine Variables?

Abstract

Modeling techniques can be used to derive formalized models that, on average, predict the outcomes of mortality, acute morbidity, and acute infectious disease in patients with nonspecific complaints with a level of accuracy far beyond chance. The models also predicted these outcomes more accurately than did physicians' intuitive judgments of how ill the patients look; however, the latter was among the small set of best predictors for mortality and acute morbidity. These results lay the groundwork for further refining triage and risk stratification tools for patients with nonspecific complaints. More research, informed by whether the goal of a model is high sensitivity or high specificity, is needed to develop readily applicable clinical decision support tools (e.g., decision trees) that could be supported by electronic health records.