The present study advocates the application of statistical process control (SPC) as a performance monitoring tool for a PACS. The objective of statistical process control (SPC) differs significantly from the traditional QC/QA process. In the traditional process, the QC/QA tests are used to generate a datum point and this datum point is compared to a standard. If the point is out of specification, then action is taken on the product and action may be taken on the process. To move from the traditional QC/QA process to SPC, a process control plan should be developed, implemented, and followed. Implementing SPC in the PACS environment need not be a complex process. However, if the maximum effect is to be achieved and sustained, PACSSPC must be implemented in a systematic manner with the active involvement of all employees from line associates to executive management. SPC involves the use of mathematics, graphics, and statistical techniques, such as control charts, to analyze the PACS process and its output, so as to take appropriate actions to achieve and maintain a state of statistical control. While SPC is extensively used in the healthcare industry, especially in patient monitoring, it is rarely applied in the PACS environment. One may refer to a recent SPC application that Mercy Hospital (Alegent Health System) initiated after it implemented a PACS in November 2003 (Stockman & Krishnan, 2006). The anticipated benefits characteristic to PACS through the use of SPC include: • Reduced image retake and diagnostic expenditure associated with better process control. • Reduced operating costs by optimizing the maintenance and replacement of PACS equipment components. • Increased productivity by identification and elimination of variation and outof- control conditions in the imaging and retrieval processes. • Enhanced level of quality by controlled applications. SPC involves using statistical techniques to measure and analyze the variation in processes. Most often used for manufacturing processes, the intent of SPC is to monitor product quality and maintain processes to fixed targets. Hence besides the HSSH techniques, the proposed TQM approach would include the use of SPC. Although SPC will not improve the reliability of a poorly designed PACS, it can be used to maintain the consistency of how the individual process is provided and, therefore, of the entire PACS process. A primary tool used for SPC is the control chart, a graphical representation of certain descriptive statistics for specific quantitative measurements of the PACS process. These descriptive statistics are displayed in the control chart in comparison to their “in-control” sampling distributions. The comparison detects any unusual variation in the PACS delivery process, which could indicate a problem with the process. Several different descriptive statistics can be used in control charts and there are several different types of control charts that can test for different causes, such as how quickly major vs. minor shifts in process means are detected. These control charts are also used with service level measurements to analyze process capability and for continuous process improvement efforts.
A Study of Cumulative Quantity Control Chart for a Mixture of Rayleigh Model under a Bayesian Framework
