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.

The Modified Direct Analysis Method: an Extension of the Direct Analysis Method

The purpose of this research project is to study an innovative method for the stability assessment of structural steel systems, namely the Modified Direct Analysis Method (MDM). This method is intended to simplify an existing design method, the Direct Analysis Method (DM), by assuming a sophisticated second-order elastic structural analysis will be employed that can account for member and system instability, and thereby allow the design process to be reduced to confirming the capacity of member cross-sections. This last check can be easily completed by substituting an effective length of KL = 0 into existing member design equations. This simplification will be particularly useful for structural systems in which it is not clear how to define the member slenderness L/r when the laterally unbraced length L is not apparent, such as arches and the compression chord of an unbraced truss. To study the feasibility and accuracy of this new method, a set of 12 benchmark steel structural systems previously designed and analyzed by former Bucknell graduate student Jose Martinez-Garcia and a single column were modeled and analyzed using the nonlinear structural analysis software MASTAN2. A series of Matlab-based programs were prepared by the author to provide the code checking requirements for investigating the MDM. By comparing MDM and DM results against the more advanced distributed plasticity analysis results, it is concluded that the stability of structural systems can be adequately assessed in most cases using MDM, and that MDM often appears to be a more accurate but less conservative method in assessing stability.