Spatial analysis using interactive heat maps for optimizing the intrahospital patient transportation system

Patients visit multiple units for tests and therapy that are scheduled as a part of their treatment plan. The transporters move the patients between departments. Typically, every patient transportation process requires one transporter but there are certain situations when two transporters are required to complete the task, especially when critical patients must be transported in bed. As these types of transport jobs increase, it creates a deficiency of transporters during peak hours. The few successful approaches allow the user to observe the variation in patient flow and transport turnaround time between departments by the month, week, day, hour of the day, transport mode used, etc. This will help the user tackle problems efficiently and optimize the transportation process between certain units. This study uses a structured data mining framework and creates an interactive visualization, that will help the user at the hospital determine the problem, analyze the influencing factors, and improve the process. The dataset for this study was obtained from EPIC. The data was mined with specific process characteristics, which influence the transport turnaround time. The novel approach used tools available in Microsoft Excel to create two IHM to visualize the patient flow and the transport time, respectively. With the help of the IHM we can observe that there are certain units that have the highest patient movement and have a corresponding high transport time. Based on the visual representation, the transport manager can localize the delays to specific units and make significant improvements.