Improving efficiency of real time locating systems in hospitals

Mobile assets used jointly by several hospital departments affect hospital processes adversely when they are not shared in a systematic manner. Hospitals manage critical events such as patient care so accelerating operations such as searching-finding an asset and tracking an asset in real time is a necessity to meet the departments' needs immediately. To enable this using Real Time Locating System (RTLS) technology can be a good choice. Hospital systems without RTLS suffer from long asset to patient time due to searching an asset and taking the asset from a long distance point. Additionally, hospital departments are reluctant to share their assets even if they have unused ones, thinking that they may need the asset in the near future. In this study we develop asset selection rules which can be integrated to the RTLS technology. The analysis are based on TOBB University of Economics and Technology Hospital. This study aims decreasing asset to patient time, decreasing departments reluctance about sharing assets with other departments and quantifying the benefit of these rules. In the scope of this thesis, we developed three asset selection rules. These rules consider asset number of assets available in departments, asset distance and departments' asset demands while suggesting the asset to be selected. For the rules that use forecasting to calculate the departments' asset demand, seasonal ARIMA models are evaluated. Hospital's current status model and RTLS-integrated asset selection rules are tested in the simulation environment. All selection rules are compared pairwise and the performance measures are examined. The sensitivity of asset selection rules against different demand rates and different demand patterns varying among departments are analyzed. As a result, we observed that proposed asset selection rules gives robust responses to this sensitivity analysis. Keywords: Hospital, Simulation, Seasonal ARIMA Method, Real Time Locating Systems (RTLS).