Quality Control in the Healthcare Industry: An Analysis of Surgery Turnover Times

For virtually all hospitals, utilization rates are a critical managerial indicator of efficiency and are determined in part by turnover time. Turnover time is defined as the time elapsed between surgeries, during which the operating room is cleaned and preparedfor the next surgery. Lengthier turnover times result in lower utilization rates, thereby hindering hospitals’ ability to maximize the numbers of patients that can be attended to. In this thesis, we analyze operating room data from a two year period provided byEvangelical Community Hospital in Lewisburg, Pennsylvania, to understand the variability of the turnover process. From the recorded data provided, we derive our best estimation of turnover time. Recognizing the importance of being able to properly modelturnover times in order to improve the accuracy of scheduling, we seek to fit distributions to the set of turnover times. We find that log-normal and log-logistic distributions are well-suited to turnover times, although further research must validate this finding. Wepropose that the choice of distribution depends on the hospital and, as a result, a hospital must choose whether to use the log-normal or the log-logistic distribution. Next, we use statistical tests to identify variables that may potentially influence turnover time. We find that there does not appear to be a correlation between surgerytime and turnover time across doctors. However, there are statistically significant differences between the mean turnover times across doctors. The final component of our research entails analyzing and explaining the benefits of introducing control charts as a quality control mechanism for monitoring turnover times in hospitals. Although widely instituted in other industries, control charts are notwidely adopted in healthcare environments, despite their potential benefits. A major component of our work is the development of control charts to monitor the stability of turnover times. These charts can be easily instituted in hospitals to reduce the variabilityof turnover times. Overall, our analysis uses operations research techniques to analyze turnover times and identify manners for improvement in lowering the mean turnover time and thevariability in turnover times. We provide valuable insight into a component of the surgery process that has received little attention, but can significantly affect utilization rates in hospitals. Most critically, an ability to more accurately predict turnover timesand a better understanding of the sources of variability can result in improved scheduling and heightened hospital staff and patient satisfaction. We hope that our findings can apply to many other hospital settings.

Transport of Hydraulic Fracturing Water and Wastes in the Susquehanna River Basin, Pennsylvania

The development of the Marcellus Shale gas play in Pennsylvania and the northeastern United States has resulted in significant amounts of water and wastes transported by truck over roadways. This study used geographic information systems (GIS) to quantify truck travel distances via both the preferred routes (minimum distance while also favoring higher-order roads) as well as, where available, the likely actual distances for freshwater and waste transport between pertinent locations (e. g., gas wells, treatment facilities, freshwater sources). Results show that truck travel distances in the Susquehanna River Basin are greater than those used in prior life-cycle assessments of tight shale gas. When compared to likely actual transport distances, if policies were instituted to constrain truck travel to the closest destination and higher-order roads, transport mileage reductions of 40-80% could be realized. Using reasonable assumptions of current practices, greenhouse gas (GHG) emissions associated with water and waste hauling were calculated to be 70-157 MT CO2 eq per gas well. Furthermore, empty so-called backhaul trips, such as to freshwater withdrawal sites or returning from deep well injection sites, were found to increase emissions by an additional 30%, underscoring the importance of including return trips in the analysis. The results should inform future life-cycle assessments of tight shale gases in managed watersheds and help local and regional governments plan for impacts of transportation on local infrastructure. (C) 2013 American Society of Civil Engineers.