D469 Task 1 Quality Improvement Presentation Example

Fewer Wrong Labels, Fewer Late Totes: A Lean Six Sigma Improvement Presentation for a Composite Regional Pharmacy Chain's Central Fill Center

Student Name

School of Business, Western Governors University

D469: Quality, Continuous Improvement, and Lean Six Sigma, Task 1

Course Instructor

Month Day, Year

Slide 1: Define the Problem

Central fill center serves 60 stores

Labeling errors caught at store: 0.9% of prescriptions

Totes arriving late: 12% of deliveries

Speaker notes: Our central fill center fills about 14,000 prescriptions a day for 60 stores. Two problems have grown this year. Pharmacists at stores catch labeling errors, such as the wrong directions or the wrong patient name on the label, on 0.9% of prescriptions, about 126 a day, and 12% of delivery totes arrive after the 9 a.m. promise. Every caught error costs store pharmacist time, and any error that is not caught is a safety risk to a patient. Our goal is to cut caught labeling errors by 60% and late totes to under 4% within six months.

Slide 2: Why It Matters

Dispensing errors are a national problem

About 1.7% error rate in a 50-pharmacy study

Each error costs pharmacist time and risks harm

Speaker notes: This is not unique to us. A national observational study of 50 pharmacies found a dispensing accuracy rate of 98.3%, or 77 errors in 4,481 prescriptions, and estimated about four errors a day in a pharmacy filling 250 prescriptions (Flynn et al., 2003). Most errors are not clinically important, but some are. Our errors are caught by store pharmacists, which works, but it means our quality depends on inspection at the end rather than on getting it right in the process. Six Sigma aims to change that by reducing variation at its source.

Slide 3: Measure the Current State

Six weeks of error and delivery data

Errors tracked by type, shift, station and drug

Process mapped from order to tote

Speaker notes: In the measure phase, we collected six weeks of data on every error reported by stores, classified by type, shift, filling station and drug, and timed each step of the process from order release to tote loading. We also mapped the process, which revealed that labels are printed in batches at the start of each hour and matched to vials by hand at the packing station, a step no one had seen as risky.

Slide 4: Analyze With a Pareto Chart

Three error types cause 78% of errors

Label-to-vial mismatch: 44%

Wrong directions text: 21%; wrong quantity: 13%

Speaker notes: A Pareto chart ranks error types by frequency. Three types account for 78% of all errors: labels attached to the wrong vial, 44%; wrong directions text, 21%; and wrong quantity, 13%. Focusing on these three will address most of the problem. The data also showed that mismatches spike in the last hour of each shift and at the two packing stations nearest the printer, where batches of labels pile up.

Slide 5: Analyze Root Causes With a Fishbone Diagram

Methods: batch label printing

Machines: no scan to confirm label matches vial

People: end-of-shift fatigue; Materials: look-alike vials

Speaker notes: A fishbone diagram organizes possible causes by category. For mismatches, the root causes are clear: labels are printed in batches rather than one at a time, there is no scan confirming that the label and vial match, staff are tired and rushed in the last hour, and similar vial sizes make mix-ups easy. Wrong directions trace to free-text directions typed by prescribers that our system does not standardize. Late totes trace to a bottleneck at the packing station, the same place where mismatches occur, and to totes being loaded in the order they are finished rather than in route order.

Slide 6: Improve

Print-on-demand labels with scan-to-verify

Standard directions library for common drugs

Load totes by route; add a packer on peak hours

Speaker notes: We tested four improvements in a two-week pilot at two stations. First, labels now print one at a time when a vial reaches the packing station, and the packer scans both the vial and the label; the system blocks a mismatch. Second, a library of standardized directions covers the 200 most common drugs, and pharmacists review any free-text directions before printing. Third, totes are loaded in route order. Fourth, one additional packer works the two busiest hours and the last hour of the shift. In the pilot, mismatches at the two stations fell from 41 to 3, and late totes fell to 5%. Lean thinking also removed waste: packers no longer walk to the printer, which saved time that helped absorb the scanning step.

Slide 7: Control

Control chart of daily error rate

Weekly review of any out-of-control points

Scan compliance tracked by station

Speaker notes: To keep the gains, we will track the daily error rate on a control chart, the standard statistical process control tool for separating ordinary variation from signals that a process has changed (Montgomery, 2019). Points outside control limits or runs of rising errors trigger an investigation within 24 hours. Scan compliance is monitored by station, and the directions library is updated monthly. Research on Six Sigma describes its effectiveness as coming partly from specific, challenging goals combined with a structured method and measurement (Linderman et al., 2003), which is why we set clear targets and will report progress to store pharmacy managers every month.

Slide 8: Results and Next Steps

Pilot: mismatches down 93% at pilot stations

Rollout to all 14 stations over six weeks

Target: 60% fewer caught errors, under 4% late totes

Speaker notes: The pilot results are strong, but two stations for two weeks is a small sample, so we will confirm results as we roll out to all 14 stations over six weeks. The expected cost is about $48,000 for scanners and label printers and $62,000 a year for the additional packer hours, against savings in store pharmacist time and, most importantly, lower risk to patients. We will report results at 30, 60 and 90 days after full rollout. Thank you.

References

Flynn, E. A., Barker, K. N., & Carnahan, B. J. (2003). National observational study of prescription dispensing accuracy and safety in 50 pharmacies. Journal of the American Pharmaceutical Association, 43(2), 191-200. https://doi.org/10.1331/108658003321480731

Linderman, K., Schroeder, R. G., Zaheer, S., & Choo, A. S. (2003). Six Sigma: A goal-theoretic perspective. Journal of Operations Management, 21(2), 193-203. https://doi.org/10.1016/S0272-6963(02)00087-6

Montgomery, D. C. (2019). Introduction to statistical quality control (8th ed.). Wiley.