Rationale, aims, and objectives: A more effective allocation of critical care resources is important as the cost of intensive care increases. A model has been developed to predict the probability of in-hospital death among patients who received extracorporeal membrane oxygenation (ECMO). Cost-effectiveness analyses (CEA) were performed regarding the relationship between hospitalization expenses and predicted survival outcomes.
Methods: Adult patients who received ECMO in a medical center in Taiwan (2005-2016) were included. A logistic regression model was applied to a spectrum of clinical measures obtained before and during ECMO institutions to identify the risk variables for in-hospital mortality. CEA were reported as a predictive risk in quintiles and defined as the cost of each quality-adjusted life-year (QALY). The distribution of the cost-effectiveness ratio (CER) was measured by the ellipse and acceptability curve methods.
Results: A total of 919 patients (659 males, mean age: 53.7 years) were enrolled. Ten variables emerged as significant predictors of in-hospital death. The area under the receiver operating characteristic curve was 0.75 (95% confidence interval: 0.72-0.79). In-hospital and total follow-up times were 40,366 and 660,205 person-days, respectively. The total in-hospital expense was $31,818,701 USD and the total effectiveness was 1687.3 QALY. For the lowest to the highest risk quintile, the mean mortality risks were 0.30, 0.48, 0.61, 0.75, and 0.88, and mean adjusted CER were $24,230, $43,042, $54,929, $84,973, and $149,095 per QALY, respectively.
Conclusions: The efficient allocation of limited and costly resources is most important when one is forced to decide between groups of critically ill patients. The current analyses of ECMO outcomes should assist in identifying candidates with the greatest prospect for survival while avoiding futile treatments.
Keywords: cost-effectiveness analysis; cost-utility analysis; extracorporeal membrane oxygenation; mortality.
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