LAS VEGAS – Lean Six Sigma, a method for improving quality and efficiency that originated in automotive and semiconductor manufacturing, can also bring impressive results to community oncology practices, according to a physician who has applied the method in the nation’s largest private cancer care network.
"We have shown – and we are convinced – that continuous improvement with Lean Six Sigma can be successfully applied to an oncology clinic, and we can see real benefits as a result," said Dr. David C. Fryefield, medical director of the Practice Quality and Efficiency (PQE) program created in 2006 that implements Lean Six Sigma at US Oncology’s member practices.
Between 2007 and 2010, those practices that participated in the program added $80 million to their bottom line, Dr. Fryefield said, stressing that the program is comprehensive and includes quality assessments, such as patient surveys, as well as improvements in efficiency.
The initiative began with a study of the day-to-day workings of two practices in Oregon and Texas. Results showed that on average, various processes had some kind of defect or breakdown about 20% of the time, according to Dr. Fryefield, also medical director of the Willamette Valley Cancer Institute in Eugene, Ore. For example, lab reports were available on time for physicians in just 44% of cases, and complete physician orders for admixtures were available when needed in 71% of cases.
This is "the dirty laundry part," Dr. Fryefield told attendees. "But if you are honest, I bet you’ll know that these kinds of things are happening in your practice as well."
Further analyses showed that staff, especially medical assistants, had substantial amounts of what is called "non–value-added time," or time not spent in direct or supportive patient care activities.
"Essentially, these [employees] are work-around bees," Dr. Fryefield said. "We have a defective process, and we hire a medical assistant to work around that process, to make that extra phone call" to track down a missing lab report.
The flawed processes were causing increased wait times in the clinic. For most types of encounters, more than half of a patient’s visit was spent waiting.
Finally, the practices had a distortion in capacity, according to Dr. Fryefield. Their labs’ target capacity was 60%, but the labs were actually operating at 115%. Meanwhile, exam rooms and chemotherapy chairs were well under their target capacity, which wasted resources as patients sat and sat.
Clearly, oncology practices had plenty of room for improvement, and Lean Six Sigma was chosen to bring that about, he said. "Lean" shortens the time required to complete a task by reducing steps and improving handoffs between people, Dr. Fryefield, explained at the annual Community Oncology Conference. "Six Sigma" is a systematic approach to reducing defects in a process by controlling the causative factors.
The method’s steps are summed up by the acronym DMAIC, which stands for define, measure, analyze, improve, and control.
"Define" refers to the establishment of agreed-on expectations for a given process; for example, the steps involved in patient scheduling or drug preparation.
"Measure" can be implemented by simple means, such as having observers use a stopwatch and clipboard to tally performance for each metric.
"Analysis" entails crunching the numbers to find the root cause of problems.
In "Improve," the findings are applied in a focused way that addresses the defective processes.
Finally, "Control" pertains to sustaining the improvement. For example, display results where staff can see them, and periodically remeasure to prevent any backsliding.
Each part of the process – no matter how seemingly small or obvious – is important to the whole, Dr. Fryefield said. He introduced the following four case studies:
• Case 1. Practice leaders thought they had insufficient exam rooms for their physicians, but Lean Six Sigma showed that "the exam rooms were the least of the problems," Dr. Fryefield said. The practice had long wait times to first appointments, whereas its oncologists had as few as 11 patient slots per day. After focused improvements in these areas, including the addition of many fewer rooms than planned, new patient volume rose by 6% and the labor cost per visit fell by 4%.
• Case 2. An oncology practice had excess capacity in its radiation therapy clinic, with relatively poor productivity for the number of radiation therapists employed. Computer modeling indicated that with flexible staff scheduling and other measures, the practice could get by with just two of its three linear accelerators. Therefore, the oldest was mothballed, and staff was reduced, resulting in a cost savings of nearly $500,000.