Modeling critically ill patients with data envelopment analysis
Critically ill patients suffering from either closed head trauma or septic shock were studied retrospectively to see if the mathematical programming technique of Data Envelopment Analysis (DEA) could be used to develop models to assess an individual patient's progress in an Intensive Care Unit (ICU). Unlike current logistic regression models that focus on the mean values for groups of patients, the DEA models evaluate each patient individually by calculating an “efficiency” score based on a patient's ability to maximize output for a given set of physiologic inputs. Patients with high efficiency scores were found to have a better chance of making a full recovery than similarly injured patients that were inefficient, even when the latter had more “normal” values for their variables. New hybrid models that combine DEA with discriminant analysis and correspondence analysis were also developed and their potential role in the ICU is explored. DEA models in the ICU need further study before implementation but appear to offer physicians a deeper understanding of their patients and a better opportunity to improve patient outcome than presently used models based on regression.
Data envelopment analysis
0546: Industrial engineering
0769: Health care