Optimizing Emergency Services with Lean Six Sigma

ISE Magazine -Volume 49: Number 02
By Casey Bedgood

Black belt project levels staffing, cuts response time and answers more calls

In 2013, Navicent Health’s emergency medical services was a well-established provider in the state of Georgia with a strong focus and reputation for clinical excellence. However, it was experiencing a variety of operational inefficiencies, including an outdated pay system and a mismatch between staffing levels and call volume. This let the local competitor snap up numerous calls per month, costing Navicent revenue.

Navicent’s management decided to tackle the EMS service problem by deploying a lean Six Sigma team for a black belt project, adding administrative changes to optimize the system. In 2014, Navicent Health’s first black belt led this interdisciplinary group of EMS leaders, administrators and human resources leaders down the path of continuous improvement by way of DMAIC (define, measure, analyze, improve, control) to reduce variation and optimize other operational key performance indicators (KPIs).

The emergency services optimization black belt project Sigma to improve critical-to-quality elements drastically, including emergency response times, turnaround times, customer satisfaction, cost of poor quality and wasted motion. This black belt project saved a significant amount of money and optimized the system. The project positively impacted tens of thousands of customers across the multicounty service area, significantly reduced operational costs, improved employee satisfaction and reduced various types of unwarranted variation.


Navicent’s deployment plan was flawed, continuously pulling and pushing ambulances among the four-county service area. This resulted in excessive fatigue, prolonged emergency response times, wasted motion, reworks and excessive fleet expenses.

These inefficiencies, of course, came with a financial cost. Navicent’s EMS system gave away dozens of emergency calls per month to the local competitor due to these problems. The suboptimal staffing capacity across the system delayed service, lost revenue and resulted in unfavorable public relations.

The black belt team set out to improve emergency response times by 10 percent, optimize utilization (namely unit hour utilization) of resources to industry standards, eliminate paying excessive wages, improve the quality of care and provide safer services to the communities served – all within six months.

The project scope related to staffing redesign was focused on the urban service area of Bibb County, and the pay system conversion was intended to be applied to staff in all service areas. The critical-to-quality focus was on emergency response times, unit hour utilization per unit and cost savings.


To measure the current state and future improvements, the team focused on the following operational KPIs: emergency response times, turnaround times, unit hour utilization, out-of-chute times and the hourly call volume demand analysis.

The response, turnaround and out- of- chute times were measured on a fractile basis, with 90 percent considered the minimum acceptable standard. Also, due to state-imposed zoning requirements, Navicent Health EMS was required to give emergency calls to the local competitor if no ambulances were available within two minutes of receiving the emergency request.

These calls given to the competitor represent reworks and revenue loss for the service. The figure also indicates that the actual KPI measures were underperforming to Navicent Health’s goal in all categories.


After the actual KPIs were measured and compared to goal, control charts and a histogram were configured to analyze whether the overall processes related to emergency response times and calls given to the local competitor were in or out of control and capable. The process for calls given to the local competitor was out of control and not capable (i.e., sigma level < 3). This resulted in delayed service, reworks, revenue loss and dissatisfied patients.

In order to analyze the hourly call volume demand for ambulances, a demand analysis was built to measure hourly demand for each hour of the day each day of the week using the 90th percentile and averages.

The process map shows that under the current call-taking/call assignment process required by state zoning rules, nearly 50 percent of the process steps are nonvalue-added. Thus, when calls were given to local competitors the current process was riddled with delays, waste and reworks, which added layers of inefficiencies between the supplier and consumer. The takeaway is that if the system was optimized and staffed properly, then the nonvalue-added steps would become nonfactors as fewer calls would be given away to the competitor.


The team focused on several initiatives that were designed to improve the situation. All EMS staff members were converted to the 40-hour pay system, which paid fair market rates competitive with EMS industry standards. Overtime was paid only after 40 hours of work in a workweek for all areas.

Urban staff members were provided alternate rural pay rates so they would be paid properly if they chose to work overtime shifts with lower call volumes on 24-hour shifts.

Geographical software analysis was conducted to determine the best place to locate EMS substations in all counties in the service area. This determination was based on historical call volume data and risk analysis. This statistically placed the on-duty ambulances in areas with the greatest probability of call locations, which contributed to faster response times and higher levels of service.

The summary of results after implementation, shows significant improvements system wide in emergency response times (12 percent improvement), unit hour utilization (30 percent reduction in the urban area), call volume variation per ambulance (50 percent improvement), out-of-chute times (40 percent improvement) and employee call outs (70 percent reduction).

The improvements saved more than 37,000 minutes in emergency response times, and in this industry, time equals lives. The lean Six Sigma team used test of hypothesis (paired comparison small sample) to test the improvement of emergency response times post-implementation.


After implementation and verification of the successful results, the changes have been controlled by monitoring real-time dashboards and analytics for emergency response times per county, out-of-chute times per crew, turnaround times per crew, unit hour utilization per crew and hourly call volume demand analysis to ensure optimization is achieved and maintained.

Lessons learned

The Navicent Health lean Six Sigma black belt team learned a number of great lessons that can be applied in any enterprise. First, designing real-time dashboards and utilization reports were essential to implementing and sustaining positive change, as these statistics guided the team each step of the process. Next, the team learned early on that change is much easier and more likely to be sustained if customers (both external and internal) are engaged and have a voice in the process from inception through implementation. Finally, well-defined goals and key performance indicators (KPIs) that can be measured in real time are essential to realizing long-term sustainable change over large geographic areas.