Randomized trial of automated, electronic monitoring to facilitate early detection of sepsis in the intensive care unit*.

OBJECTIVE: To determine whether automated identification with physician notification of the systemic inflammatory response syndrome in medical intensive care unit patients expedites early administration of new antibiotics or improvement of other patient outcomes in patients with sepsis. DESIGN: : A prospective randomized, controlled, single center study. SETTING: Medical intensive care unit of an academic, tertiary care medical center. PATIENTS: Four hundred forty-two consecutive patients admitted over a 4-month period who met modified systemic inflammatory response syndrome criteria in a medical intensive care unit. INTERVENTION: Patients were randomized to monitoring by an electronic "Listening Application" to detect modified (systemic inflammatory response syndrome) criteria vs. usual care. The listening application notified physicians in real time when modified systemic inflammatory response syndrome criteria were detected, but did not provide management recommendations. MEASUREMENTS AND MAIN RESULTS: The median time to new antibiotics was similar between the intervention and usual care groups when comparing among all patients (6.0 hr vs. 6.1 hr, p = .95), patients with sepsis (5.3 hr vs. 5.1 hr; p = .90), patients on antibiotics at enrollment (5.2 hr vs. 7.0 hr, p = .27), or patients not on antibiotics at enrollment (5.2 hr vs. 5.1 hr, p = .85). The amount of fluid administered following detection of modified systemic inflammatory response syndrome criteria was similar between groups whether comparing all patients or only patients who were hypotensive at enrollment. Other clinical outcomes including intensive care unit length of stay, hospital length of stay, and mortality were not shown to be different between patients in the intervention and control groups. CONCLUSIONS: Realtime alerts of modified systemic inflammatory response syndrome criteria to physicians in one tertiary care medical intensive care unit were feasible and safe but did not influence measured therapeutic interventions for sepsis or significantly alter clinical outcomes.

A modeling environment for patient portals.

Clinical Information Systems (CIS) are complex environments that integrate information technologies, humans, and patient data. Given the sensitivity of patient data, federal regulations require health care providers to define privacy and security policies and to deploy enforcement technologies. The introduction of model-based design techniques, combined with the development of high-level modeling abstractions and analysis methods, provide a mechanism to investigate these concerns by conceptually simplifying CIS without sacrificing expressive power. This work introduces the Model-based Design Environment for Clinical Information Systems (MODECIS), which is a graphical design environment that assists CIS architects in formalizing systems and services. MODECIS leverages Service-Oriented Architectures to create realistic system models as abstractions. MODECIS enables the analysis of legacy architectures and the design and simulation of future CIS. We present the feasibility of MODECIS by modeling operations, such as user authentication, of MyHealth@Vanderbilt, a real world patient portal in use at Vanderbilt University Medical Center.