In the emergency department of a hospital, the amount of wait time is of huge importance to the patient as well as the staff. Using Six Sigma methodology, the nurse director of Providence Hospital in Michigan was able to dramatically cut down on wait times for patients.
Before Providence Hospital in Southfield, MI, embarked on its Six Sigma project, the average wait time for a patient to see a doctor was 64.3 minutes. Admittedly, waiting a little over an hour before getting to see a doctor in a busy emergency department does not sound unreasonable. Unfortunately, this view comes apart a bit when you consider that 64.3 minutes was the average. An average is a number that expresses the central value in a data set. That means that there are numbers both on the lower end and the higher end of that central number in order to reach that average. Put simply, in real wait times, that means that the shortest wait time could be ten minutes and the longest wait time could be nearly two hours to reach an average of 64.3 minutes. In the case of Providence Hospital, before the Six Sigma project, 70% of patients had a 20 to 110-minute wait. This likely would not be a major problem for the patient waiting for twenty minutes, but the patient waiting 110 minutes would not likely be very happy.
Instead of focusing on the average wait time, the staff opted to look at the standard deviation. The standard deviation was 44.7 minutes, which they believed could be improved.
In order to have an idea of how much improvement they needed, the staff decided to explore the Voice of the Customer. This involves a process of gathering feedback from customers and working to understand it in order to provide a better customer experience. This type of feedback comes through a variety of methods, including questionnaires, polls, exit surveys, and so on. In the case of Providence Hospital, the staff conducted a survey to determine what the upper limit of the waiting time that a patient was willing to tolerate was. They found that the bulk of patients deemed it acceptable to wait up to an hour to see a doctor in the ED. This was a lot lower number than the upper spectrum of the wait times experienced. A significant amount of work would need to be done in order to bring the wait time for patients down to an acceptable level across the board. They would have to find a way to get the maximum wait time below an hour.
Providence Hospital Had A Wait Time Problem
In 2002, utilizing Six Sigma in the manufacturing realm was well-established, but it was less common in healthcare. In order to improve its processes across all of its locations, Providence Healthcare began implementing the Six Sigma methodology. Providence was looking for a method for problem identification, solution implementation, and the maintenance of positive results. The organization felt that Six Sigma’s unique, data-driven, statistical, and logical approach could serve the hospital system well.
Fifteen managers throughout the Providence Health System participated in a six-week training course and then individually selected a project to practice the Six Sigma method. One of the projects selected was a reduction in wait times for patients.
A project team almost immediately realized that there was not sufficient data accumulated about accurate wait times. It was well-known that patients were frustrated with their wait times, but there had been no sufficient monitoring that could be referenced in order to determine the scope of the issue.
A manual data collection effort found out how long patients were waiting before seen by a doctor. When surveying patients, it was found that the bulk of the patients felt that the registration process should take less than five minutes before they would be waiting to be seen by a doctor. The current wait time was actually closer to ten minutes and was before a patient was even officially registered and waiting to see someone.
Detailed data was then gathered about each registration. The goal was to understand why one registration might take just a couple of minutes while another would take six. In order to gather this data, registrars were to fill out a form for each patient that listed a number of different factors that could add time to the registration process. The registrar would record the duration of the patient’s registration process as well as any applicable factors that contributed to the length of the process.
The project team analyzed the collected data and found that several factors were contributing to the long registration periods. Some of these factors included talkative patients with a lot of questions, the need for updating patient information, missing orders, and the inability of some patients to quickly find their insurance card.
A brainstorming session was held by the project team in order to address each of these factors. Registrars were trained to close conversations politely with talkative patients. Kiosks would be introduced so that patients could update their personal information independently. An internal tracking system was introduced to reduce missing orders. Signage was posted in waiting rooms to remind patients to have their insurance cards ready.
These changes to processes made using Six Sigma methodology had an impact on wait times for patients across the bulk of Providence Hospital locations. At Providence Hospital in Southfield, however, the emergency department nurse director thought there was still more that could be done.
The Providence Hospital in Southfield Took Six Sigma Success Even Further
With 70% of patients in the emergency department at the Southfield location of Providence Hospital waiting between 20 and 110 minutes to see a doctor, the team there believed that they could take the Six Sigma successes of Providence Healthcare further.
Using the core DMAIC (define, measure, analyze, improve, and control) tool, the team avoided simply using intuition to determine what was best for cutting down on wait times. Instead, they followed DMAIC and took the time to properly measure the process. This led them to find some unexpected but key drivers of variability. These drivers were whether a patient was fast-tracked, whether there was an available bed, and whether a patient had an X-ray.
Of these factors, the most consistent was the fast-track patients, so it was determined that this would be the focus issue to bring under control.
Upon analysis, the major problem with express care for fast-tracked patients was that their care was predominantly not express at all. These patients were generally waiting two-to-three times longer than other patients. The reason for this was that the needs of fast-track patients were less acute than those of other patients in the ED. Acute patients were not going to have the speed of their care altered, so it became clear that speeding up the care of fast-track patients could make an impact.
One measure taken was changing the registration process so that it would instead be done at the bedside for express patients. An assessment of vitals would occur quickly, but the actual registration would be done bedside.
Another change made was making sure that a board-certified physician, a nurse practitioner, and a nurse were all onsite at the time of opening at 11 a.m. Prior to this change, there would only be nurses and floating physicians from other departments on hand until 1 p.m.
Improvements to ergonomics and flow were also implemented. These included adding a refrigerator to make things run smoother and moving a computer. Changing the location of medications increased counter space, and automatic dispensation sped up turnaround.
The Outcome Was Significant
The changes made in the emergency department of the Providence Hospital in Southfield managed to take the improvements made in wait time throughout the Providence Healthcare system significantly further. The left-without-being-seen rate dropped to under 1% while the volume of patients rose seen rose by 5%. Instead of the maximum wait time for 70% of patients to be seen being 110 minutes, patients could now anticipate waiting no longer than just over an hour. The mean door-to-doctor time had a 38.1% improvement, dropping from 64.3 minutes to 39.8 minutes. The standard deviation in wait time had a 38% improvement, dropping from 44.7 minutes to 27.7 minutes.
3 Best Practices When Implementing DMAIC
The Southfield location of Providence Hospital learned some key lessons when improving their processes to cut down on wait times for their patients. These are lessons that could serve you well when running a Six Sigma project in your organization:
1. Follow the steps without jumping ahead
It could be incredibly tempting to just follow your intuition in determining what the root causes are for issues that are affecting your organization. Be sure to thoroughly work the steps of the DMAIC process and correctly define, measure, and analyze to determine what the root causes actually are before jumping ahead to improvement efforts.
2. Listen to your customers
Utilize the Voice of the Customer when sorting out exactly what the issues are and how to best address them.
3. Continuous improvement
Six Sigma methodology had already played a big role in cutting down on wait times at Providence Hospital locations before the team at Southfield decided to take it even further. Just because there have already been improvements made, does not mean that there cannot be more.
Making a Good Thing Even Better
If your organization has already used Six Sigma methods to make improvements to processes, it is worth finding ways to make those improvements continuous. If a problem has been addressed, that does not mean that there is no room for further growth and refinement. There is likely always room to do better.
