At the end of the chapter, the reader will be able to:
Explain the rationale for statistical process control.
Describe and learn how to utilize the following tools for statistical process control:
- Pareto charts;
- scatter diagrams;
- run charts;
- control charts;
Discuss how statistical process control tools can be incorporated into the steps of quality improvement.
Pharmacy is comprised of complex systems. It is important that these systems are reliable in order to deliver quality pharmacy services. Statistical process control (SPC), the use of statistical techniques to measure change in systems, is one method of monitoring quality in pharmacy practice. SPC is particularly useful because a key determinant of quality in products and services is consistency. Statistical analysis can be utilized to improve quality by identifying inconsistency in systems, and SPC tools, such as histograms, Pareto charts, scatter diagrams, and run and control charts, can help distinguish between acceptable and unacceptable inconsistencies in pharmacist services. This chapter will describe the rationale for SPC, commonly used SPC tools, and how to incorporate SPC into the steps of quality improvement.
Repeated measurements of the same process within a system will have variable outcomes over time.1–4 The inherent variability within all systems is the foundation for SPC. Two types of variation exist, common-cause variation and special-cause variation.
Common-cause variation is always present within a system and consists of modest changes that occur randomly. Common-cause variation in a pharmacy can be a result of things such as differences in individual pharmacists and technicians, patient populations, situations, and chance. Despite the myriad of factors that can influence variations in pharmacy practice, over time, a predictable pattern of variation emerges. Think about 100 random measurements repeated over a 3-month period of the time it takes to fill a prescription at a pharmacy. If it takes somewhere between 5 and 25 minutes to fill 95 out of the 100 sampled prescriptions, the variation in fill times due to common cause would be 20 minutes assuming that no major changes to the system have occurred over the 3 months. As long as the system stays the same (e.g., personnel and workflow processes), common-cause variation stays the same. A system is considered to be in a state of statistical control when only common-cause variation is present.1–4 Nevertheless, a state of statistical control is not sufficient if the variation in output does not align with the system goals.1,2,5 Consider a pharmacy that has an average prescription wait time of 1 hour with times ranging from 55 to 65 minutes. Although the wait times may be predictable to within 10 minutes, the pharmacist-in-charge (PIC) may not consider the wait time to be acceptable given that the average wait time is 1 hour. It is also likely that patients would not be satisfied with the 1-hour wait.
In contrast, special-cause variation occurs when there is ...