Inventory Control Methods in a Long-Term Care Pharmacy: Comparisons and Time-Series Analyses

Background: Current inventory theory is based on simulated data and unrealistic formulae. Inventory replenishment processes are therefore commonly disrupted, and out-of-stock (OOS) events are unnecessarily frequent. Objective: OOS events at a large-volume, long-term care pharmacy in North Carolina were compared among 4 sequentially applied methods of inventory control: (a) a manual system without Six Sigma protocol, (b) a manual system with Six Sigma protocol, (c) a computer-assisted system with Six Sigma protocol, and (d) an automated system with Six Sigma protocol. Methods: Daily OOS rates were recorded for 11 weeks during the implementation of each method. Between-group comparisons were performed, and time-series analyses were conducted during each implementation to determine the significance of the change in OOS rates over the evaluation period. Results: In terms of the 2 manual systems, OOS rates were lower for the system to which a Six Sigma protocol was applied. In terms of the 3 Six Sigma systems, ranked differences were significant. The computer-assisted system had a lower OOS rate than did the automated system, and the automated system had a lower OOS rate than did the manual Six Sigma system. OOS rates were significantly reduced over an 11-week period for the computer-assisted and the automated systems. Conclusions: Six Sigma was found to be an effective process improvement strategy in the selected pharmacy setting. The study was the first inventory analysis performed with OOS events used as an empirical measure, in contrast to the simulated data used in prior studies.