129
Chapter 16
Six Sigma
Cristina Daccarett
In statistical terms, Six Sigma means that a process produces no more than 3.4 defects per million
opportunities. In broader terms, Six Sigma is a highly structured data-driven methodology for
problem solving and variation reduction. When following Six Sigma improvement projects, two
separate processes can be followed, DMAIC (dene, measure, analyze, improve, and control) and
DMADV (dene, measure, analyze, design, verify). e DMAIC process is used when an existing
process needs to be improved, while the DMADV process is utilized when a new process needs to
be developed. Although this chapter focuses on the DMAIC ow, the DMADV process is slightly
similar with the dierence being that the focus of the various phases is on understanding what is
needed and developing a new process. DMAIC focuses on understanding the current state and
improving it.
Dene
e dene phase is one of the most critical stages in the DMAIC ow. e focus of this phase
is to understand the problem and build the foundations to ensure a successful outcome. It is
important that this phase remains problem oriented. Root causes and solutions are identied
later in the process.
During this phase, a project charter is developed. is document summarizes the ndings from
the dene phase and serves as a reference tool in other phases of the project. An example can be seen
in Figure16.1. A typical charter includes a project title, a project plan, the team structure, problem
Contents
Dene ......................................................................................................................................129
Measure ....................................................................................................................................131
Analyze.....................................................................................................................................133
Improve ................................................................................................................................... 134
Control ................................................................................................................................... 134
130 ◾ Cristina Daccarett
and goal statements, the business case, scope, and stakeholders. e title should be short but should
describe the project. e project plan includes dates for milestones and a targeted completion date.
A Six Sigma project team includes, at minimum, a sponsor, a champion, a leader, and team mem-
bers. e sponsor has an executive leadership role and is responsible for selecting the project and
supporting the team by eliminating barriers and solving cross-functional issues. e champion owns
the process and has the ability to mediate issues across the organization and can create support
systems. e leader is a black belt (a professional with thorough understanding of the Six Sigma phi-
losophies, principles, and tools) who directs and guides the team throughout the DMAIC process.
e team members are active participants in the process and have rsthand knowledge of the various
stages of the process. e problem statement is a brief description of the problem while the goal
statement is a brief denition of the target. Both of these statements should be specic, measurable,
achievable, relevant, and time bound. An easy way to remember how to state the goal is to use the
acronym SMART. e business case describes why the current situation is important or is no longer
acceptable and details the nancial justication for the project. e scope denes the boundaries for
the project. e stakeholders are all those individuals who will be impacted by the project.
Six Sigma projects focus on the customer, and as such, it is important to keep in mind the
customer’s wants, expectations, and values throughout the project. During the dene phase it is
Project Charter
Project Title: Preventing avoidable utilization of acute care services
Project Team
Sponsor: David Fonseca
Champion: Cecilia Forero
Leader: Sarah Cliord
Team Members: Marcos Yaar
Catherine Smith
Brad Johnson
Angelina Braun
Project Plan
Milestone Target Actual
Start of Project 1/9/2012 1/13/2012
End of Dene 1/20/2012 1/19/2012
End of Measure 2/2/2012 2/6/2012
End of Analyze 2/24/2012 2/23/2012
End of Improve 3/16/2012 3/23/2012
End of Control 4/6/2012 4/11/2012
Problem Statement: Chart audits of patients discharged between 7/1/11 and 9/30/11 demonstrate
that 35% of patients who used acute care services postdischarge (emergency room or/and
hospitalization) could have been prevented.
Goal Statement: Reduce the percentage of patients who experience a decompensation
postdischarge that results in the utilization of acute care services. From 15% to 10% by 3/16/12.
Business Case: Designing targeted and eective interventions that aid in preventing
decompensations can improve quality of life for patients and reduce healthcare costs.
Scope: All patients discharged from the hospital excluding those who have transitioned to hospice
care or are in a transplant registry.
Customers and Stakeholders: Patients, family, providers, insurance
Signatures:
Sponsor _____________________________________________________________________________
Champion ___________________________________________________________________________
Leader ______________________________________________________________________________
Figure 16.1 Project charter.
Six Sigma ◾ 131
important to gather the voice of the customer. Collecting the customer’s input through direct
contact, focus groups, surveys, phone calls, and so on, provides an understanding of what the
customer wants, expects, and values.
To clarify stakeholder involvement, a stakeholder analysis is developed during the dene phase.
e analysis rst identies the individuals who will be impacted or have control over the project,
followed by categorizing their level of involvement as an (a)pprover, (r)esource, (a)ctive member,
or (i)nterested party (ARMI worksheet). e last stage of the analysis is to determine each stake-
holder’s support toward the project, and the type of support they will need to provide to ensure
the project’s success. Refer to Figure16.2 for an illustration.
Another important component of the dene phase is to ensure everyone has the same under-
standing of the process. To achieve this, a high-level process map or SIPOC diagram is developed.
An example is shown in Figure16. 3. SIPOC refers to suppliers, inputs, processes, outputs, and
customers. e SIPOC starts by listing the 4–6 key steps of the process. e inputs and their sup-
pliers for each process step are then identied. Lastly, the outcome and their customers are listed
for each process step.
Measure
e focus of the measure phase is to develop measurement systems to set a baseline for how the
process is performing. To determine the primary metrics or key performance indicators (KPIs), it is
important to review the voice of the customer. Based on what customers identify as being critical to
Clinic Director
Clinic Physicians
Clinic Nurses
Specialty Physicians
Hospitalists
Unit Nurses
Case Managers
Inpatient Pharmacy
Outpatient Pharmacy
Home Health
Skilled Nursing Facilities
(A)pprover: Approves team decision prior to moving forward
(R)esource: Individual whose expertise may be needed on an ad-hoc basis
(M)ember: Active participant of the team
(I)nterested party: Person who needs to be kept informed and whose support might be needed in the future
Emergency Department
Physicians
Emergency Department Nurses
A
M
M
I
R
R
R
I
M
I
I
M
M
XX
X
X
X
XX
X
X
X
X
X
X
XX
XX
X
X
X
X
X
X
X
XX
NamesARMINeutral
Strongly
Against
Moderately
Against
Moderately
Supportive
Strongly
Supportive
Figure 16.2 ARMI.
132 ◾ Cristina Daccarett
quality, a measurable metric is dened and the data to be collected is then developed. For example,
if patients desire to be seen by a physician within 10 minutes of arrival at a clinic, a KPI would be
the percentage of patients who are seen by their physician within 10 minutes of arrival. e data
to collect is the time between patient arrival at the clinic and rst encounter with their physician.
Despite the important role data plays in measuring baseline and improvements, it can be very
expensive and time consuming to gather the volume of data needed to draw statistically signicant
conclusions. ere are guidelines to calculate the minimum data needed based on the variability
in the data being collected and the precision required. However, if the minimum sample size
seems dicult to obtain, evaluate other potential metrics with smaller sample size requirements
that would still measure the performance of the process.
Another component of data collection is to ensure that the data being collected is valid and
accurate. To evaluate potential bias or precision errors in the data, a measurement system anal-
ysis (MSA) should be completed. To guarantee that the data collection tool consistently mea-
sures the process, a gauge repeatability and reproducibility study (GR&R) should be completed.
Calculating repeatability ensures consistent measurements regardless of the number of times the
same person measures the process, while reproducibility ensures consistent data regardless of who
is measuring the process.
Depending on the type of data being collected (continuous, count, or attribute) and the sample
size, there are various methods to summarize and graphically represent the data. Continuous data
measures a characteristic such as wait time and usually follows a normal distribution (although
this assumption must be checked). Count data, as its name implies, counts things such as defects
and follows a Poisson distribution if the process is in control. Attribute data classies things such
as pass/fail and follows a binomial distribution if the process is in control. To graphically represent
these data, histograms or time series plots tend to be more useful with continuous or count data,
while Pareto charts or 100% stacked bar charts work best for attribute data. Continuous data
Supplier Input Process StepsOutput Customer
SUPPLIER INPUT PROCESS STEPS OUTPUT CUSTOMER
Providers
Radiology
Laboratory
Patient
Family
Providers
Medical Records
Medical Records
Patient
Family
Patient
Family / Care Givers
Medical History
Diagnostic Testing
Clinical Assessment
Diagnostic Reports
Clinical Assessment
Treatment Plan
Provider Visit
Non Adherence to
treatment plan
Disease progression
Lack of Education
Develop and Evidenced
Based Treatment Plan
Patient Discharged
from the Hospital
Patient Receives
Ongoing Care
Decompensating Event
(Seek Acute
Care Services)
Test and Procedures
Medication
Consults
Education
Rec. Lifestyle Changes
Follow-Up visits
Education
Medication
Optimization
Alterations to treatment
plan and medications
Education
Discharge home
Admit to hospital
Patients
Providers
Family
Inpatient Units
Patients
Family
PCP / Specialists
Insurance
Patients
Family / Care Givers
Patients
Family / Care Givers
Providers
Figure 16.3 SIPOC.
Six Sigma ◾ 133
tends to be summarized using the average and standard deviation, while count data is summarized
by defects per unit and attribute data by a percentage. Control charts are also commonly used in
Six Sigma projects to track metrics over time. Data are plotted in time series, with a central line
representing the average, and an upper and lower line representing the upper and lower control
limits. Conclusions regarding the process variation can be drawn based on where the current data
falls in relation to the control limits. Figure16.4 contains the graph of a process pre- and postint-
ervention. Improvements in the process can be seen by the decrease in the average and the decrease
in the variation between the upper and lower control limits.
To further understand how the process is performing, a process capability analysis assesses
the process’s ability to deliver the customer’s expectations. Depending on the distribution of the
data, statistical software such as Minitab® can complete a capability analysis. e Six Sigma level
is a common capability metric that generates a statistic that applies to all data and environments.
e Six Sigma level is the Z value in the Z-table, and converts the percent defective of a process
into a sigma level. Another common metric is Cp, a metric used to reect the potential capability:
the ratio between the width of the upper and lower customer specication and the width of the
upper and lower process performance. Since the distribution of the actual process might not be
centrally positioned to the specication of the customer, the actual capability metric, Cpk, is used
to measure the position to the closest specication: the ratio of the dierence between the process
average and the nearest specication and three times the sigma. A Cp and Cpk value above 1.33 is
acceptable while a value above 2 is excellent.
Analyze
During the analyze phase, critical factors and root causes are identied. As part of this phase, a
process map or owchart is drawn illustrating how the process currently performs. Once the team
50%
45%
40%
35%
30%
25%
20%
15%
10%
5%
0%
12/4/11
12/11/11
12/18/11
12/25/11
1/1/12
1/8/12
1/15/12
1/22/12
1/29/12
2/5/12
2/12/12
2/19/12
2/26/12
3/4/12
3/11/12
3/18/12
3/25/12
4/11/12
4/8/12
4/15/12
4/22/12
4/29/12
5/6/12
5/13/12
5/20/12
Date of Index Discharge by Week
Control Chart: Preventing Avoidable Utilization of Acute Care Service
Baseline Post Improve
Value
Average
Upper Control Limit
Lower Control Limit
% of patients with Acute Care Service Usage post-Discharge
Figure 16.4 Control chart.
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