MRI log file analysis for workflow improvement.

Magnetic Resonance Imaging (MRI) is an important diagnostic scanning tool for the detection and monitoring of specific diseases and conditions. However, the equipment cost, maintenance and specialty training of the technologists make the examination expensive. Consequently, unnecessary scanner time caused by poor scheduling, repeated sequences, aborted sequences, scanner idleness, or capture of non-diagnostic or low-value sequences is an opportunity to reduce costs and increase efficiency. This paper analyzes data collected from log files on 29 scanners over several years. 'Wasted' time is defined and key performance indicators (KPIs) are identified. A decrease in exam duration results when actively modifying and monitoring the number of sequences that comprise the exam card for a protocol.

Systems Modeling Approach for Reducing the Risk of Healthcare-Associated Infections.

Healthcare-associated infections (HAIs) are a major cause of concern because of the high levels of associated morbidity, mortality, and cost. In addition, children and intensive care unit (ICU) patients are more vulnerable to these infections due to low levels of immunity. Various medical interventions and statistical process control techniques have been suggested to counter the spread of these infections and aid early detection of an infection outbreak. Methods such as hand hygiene help in the prevention of HAIs and are well-documented in the literature. This chapter demonstrates the utilization of a systems methodology to model and validate factors that contribute to the risk of HAIs in a pediatric ICU. It proposes an approach that has three unique aspects: it studies the problem of HAIs as a whole by focusing on several HAIs instead of a single type, it projects the effects of interventions onto the general patient population using the system-level model, and it studies both medical and behavioral interventions and compares their effectiveness. This methodology uses a systems modeling framework that includes simulation, risk analysis, and statistical techniques for studying interventions to reduce the transmission likelihood of HAIs.