RightSource

RightSource is a state-of-the-art mail order pharmacy and the fifth largest pharmacy benefits provider in the United States. Like their parent company Humana, they are always looking for ways to fulfill their mission of lifelong well-being. This commitment drove their decision to migrate to a new operating platform that offered valuable customer-centric tools and advanced workflow processes.

But their decision seemed to backfire. Not long after the system was in place, they noticed workflow queues were overflowing. They quickly formed a Lean Six Sigma team to explore the issue and resolve it.

The team took a closer look at the process and found that employees were able to easily fill prescriptions moving through the “clean path”—the standard workflow when no additional steps were needed. The delays were occurring in the “exceptions path,” a more labor-intensive process necessary when a prescription required an intervention with the provider, member, or a third-party payer.

Now they had to find out why.

They also discovered that many of the members calling about prescription delays had orders in the provider outreach queue. Further analysis showed that provider outreach productivity had dropped 39% after the new system was implemented.

It appeared as if transitioning to the new PMS had slowed employees’ ability to process orders that required outreach to the provider, and that these delays were causing out-of-tolerance metrics for WIP inventory and turnaround time (TAT).

Armed with this knowledge, the team established three goals:

• Reduce by 40% WIP inventory that has spent 10 or more days in the provider outreach queue.
• Improve provider outreach productivity by 20%.
• Reduce costs by 20%.

To examine the underlying issues related to WIP inventory, the team accessed provider outreach data and turned to Minitab’s Pareto chart again—this time to identify four possible root causes for the delays: incorrect address, provider response, wrong transfer reasons, and re-looping orders.

To investigate provider outreach productivity and identify variations caused by transitioning to the new PMS, they reviewed productivity data of workers with various levels of experience at multiple locations. The team used boxplots and pie charts to identify four possible root causes: unnecessary outreach to providers, system latency, non-value-added (NVA) steps, and operational inconsistencies.

Once they understood why prescriptions were stalling in the provider outreach queue, the team brainstormed 14 potential solutions. After using an impact matrix to identify the cost, benefits, and effort of each one, they narrowed it down to five solutions:

• Retrain associates regarding correct address entry to prevent orders from being diverted into the exceptions path.
• Retrain associates to correctly identify transfer reasons to reduce the amount of WIP inventory.
• Provide less experienced associates with instruction sheets developed by top performers.
• Remove multiple NVA process steps.
• Reduce the outreach lag time that delayed provider response.

Given what they had learned from the data analysis, the team was confident that implementing these final solutions would improve the inefficiencies they were experiencing.

For example, the problem underlying the NVA process proved to be an IT-related issue, and when the team removed NVA steps in a test environment, Minitab’s 2-sample t test confirmed the changes were statistically significant. And using Minitab’s 2-proportion test, the team also confirmed that provider response delays decreased, and that retraining associates improved their ability to correctly enter addresses and transfer reasons.