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Purpose Results of a study incorporating real-world results into a predictive model to assess the cost-effectiveness of procalcitonin (PCT)-guided antibiotic use in intensive care unit patients with sepsis are reported. Methods A single-center, retrospective cross-sectional study was conducted to determine whether reductions in antibiotic therapy duration and other care improvements resulting from PCT testing and use of an associated treatment pathway offset the costs of PCT testing. Selected base-case cost outcomes in adults with sepsis admitted to a medical intensive care unit (MICU) were assessed in preintervention and postintervention cohorts using a decision analytic model. Cost-minimization and cost–utility analyses were performed from the hospital perspective with a 1-year time horizon. Secondary and univariate sensitivity analyses tested a variety of clinically relevant scenarios and the robustness of the model. Results Base-case modeling predicted that use of a PCT-guided treatment algorithm would results in hospital cost savings of $45 per patient and result in a gain of 0.0001 quality-adjusted life-year. After exclusion of patients in the postintervention cohort for PCT test ordering outside of institutional guidelines, the mean inpatient antibiotic therapy duration was significantly reduced in the postintervention group relative to the preintervention group (6.2 days versus 4.9 days, p = 0.04) after adjustment for patient sex and age, Charlson Comorbidity Index score, study period, vasopressor use, and ventilator use. Total annual hospital cost savings of $4,840 were predicted. Conclusion Real-world implementation of PCT-guided antibiotic use may have improved patients' quality of life while decreasing hospital costs in MICU patients with undifferentiated sepsis. [ABSTRACT FROM AUTHOR]

Precision medicine endeavors to leverage all available medical data in pursuit of individualized diagnostic and therapeutic plans to improve patient outcomes in a cost-effective manner. Its promise in the field of critical care remains incompletely realized. The Department of Defense has a vested interest in advancing precision medicine for those sent into harm's way and specifically seeks means of individualizing care in the context of complex and highly dynamic combat clinical decision environments. Building on legacy research efforts conducted during the Afghanistan and Iraq conflicts, the Uniformed Service University (USU) launched the Surgical Critical Care Initiative (SC2i) in 2013 to develop clinical- and biomarker-driven Clinical Decision Support Systems (CDSS), with the goals of improving both patient-specific outcomes and resource utilization for conditions with a high risk of morbidity or mortality. Despite technical and regulatory challenges, this military-civilian partnership is beginning to deliver on the promise of personalized care, organizing and analyzing sizable, real-time medical data sets to support complex clinical decision-making across critical and surgical care disciplines. We present the SC2i experience as a generalizable template for the national integration of federal and non-federal research databanks to foster critical and surgical care precision medicine. [ABSTRACT FROM AUTHOR]