Engineering Healthcare: Six Sigma and Computer Simulation in an Emergency Department
Date
2004-05
Authors
Roberts, Lance
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Abstract
<p>This project used a combination of a computer based simulation tool, specifically
the ProModel MedModel healthcare computer simulation tool, and a statistical-based
continuous improvement methodology, Six Sigma, to model/analyze the daily operations
of the Emergency Department (ED) at Central Texas Medical Center (CTMC) in San
Marcos, Texas. The goal was to use these tools in an effort to decrease the variation in the length of stay (LOS) for its patients. By decreasing the variation in LOS the resultant
impact should be a reduction in the number of highly dissatisfied customers and a
reduction in the mean LOS. In addition, there were two business goals - to increase the
quality of care (especially in regards to reducing the number and sources of errors) and to
decrease the amount of time to disposition a patient, especially in cases of admissions to
the hospital.</p>
<p>Over the last seven months the Six Sigma project team used the Six Sigma
DMAIC methodology (Define, Measure, Analyze, Improve, and Control) to identify
several improvement projects that were targeted to address inefficient or ineffective ED
processes. The team used this tool to systematically identify six major process inputs that
needed improvement: the chart system for tracking patients within the ED process, the
personnel that supported these processes, physician communication with patients and
internal support personnel, diagnostic results (both laboratory and radiological
processes), materials, and the equipment/supplies used to support the ED processes. The
hospital is using the results of the Define, Measure, and Analyze phases to begin making
improvements in their business processes. Some of the Improvement phase projects
include the redesign of their materials supply rooms, redesigning the chart system used to
track the progress of patients through the ED, redesigning the process for forwarding
patients in the waiting room into the emergency room area, analyzing the root cause for
variability in laboratory turn-around-times (TAT), writing new operating procedures for
the transportation of patient samples to the laboratory, and using communication
technology to improve the communication between personnel in the department.</p>
<p>Some of the early results show that the new Triage to ED bed process is
dramatically reducing the variation in patient wait time for this portion of the entire
process. This improvement is reducing the variation in patient lengths of stay. And, this
decrease in wait time variability causes a concurrent, downward shift in the mean wait
time. Thus, patients are spending much less time in waiting which has resulted in a
decrease in the number of patients leaving the ED without being seen (LWBS). The
project team found that the new, improved Triage to ED bed process decreased the
number of LWBS patients from 32 to 16. Therefore, based on the average revenue
generated from an ED patient of $505.67, the new process could generate an additional
$97,089 per year! In addition, a root cause analysis of the variability in lab TATs
pinpointed one, specific type of lab order as a culprit for the variability in TAT.
Eliminating this cause of “special variation” in the process will reduce patient length of
stay. Also, the redesign of the supply room and the use of communication technology are
expected to make patient care more efficient. Once the implemented improvements are
stable, the hard-won improvements will be controlled in the Control phase. Simple
control charts, such as the x-bar and p-charts are to be used to keep the new processes
under control.</p>
<p>Additionally, a computer simulation tool was used to explore several alternative
process improvement scenarios. This tool is a great choice for engineers when they need
to explore potential solutions that would be difficult to pilot in any “real” sense. The
level of difficulty associated with a proposed change render solutions that may be too
time intensive, cost prohibitive, or risky to pursue. The level of risk level may prevent
feasible solutions from being tried at all. Conversely, experimentally changing a particular process only to find that the return was less than the investment would be
worse. It would waste valuable time and resources. In this study an “as-is” model of the
current ED system was built and analyzed; then it was compared to several “what-if ’
models to explore the effects of the following business scenarios: the addition of business
hours for the ED’s Minor Emergency Clinic (MEC), the installation of a PACS system to
eliminate the transportation of x-ray film, the addition of a single Hematology Technician
to draw and transport laboratory samples from the ED area to the lab, and new bedside
registration and discharge processes. The computer simulations showed that the addition
of a single Hematology Technician and the addition of the new bedside
registration/discharge process did not significantly reduce patient LOS. However,
computer simulations show that there were statistically significant reductions in the
overall, mean patient LOS in the other two scenarios - the addition of MEC hours and
PACS system installation scenarios. These two simulation models demonstrated a 3.3%
and 3.8% reduction in the overall, mean patient LOS for each scenario respectively. The
time, cost, difficulty, and risk levels are high for these types of proposed process
improvements. Thus, computer simulation is an essential and valuable tool in assessing
the effect of these business changes without actually changing the existing system.</p>
Description
Keywords
Six sigma, Computer simulation, Hospitals
Citation
Roberts, L. (2004). <i>Engineering healthcare: Six sigma and computer simulation in an emergency department</i> (Unpublished thesis). Texas State University-San Marcos, San Marcos, Texas.