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JHQ 174--Lean Six Sigma in Healthcare
Henk de Koning, John P. S. Verver, Jaap van den Heuvel, Soren Bisgaard, Ronald J. M. M. Does
Keywords:
Cost reduction, Efficiency, Innovation, Quality improvement, Service management
March/April 2006
| Healthcare, as with any other service operation, requires systematic innovation efforts to remain competitive, cost efficient, and up-to-date. This article outlines a methodology and presents examples to illustrate how principles of Lean Thinking and Six Sigma can be combined to provide an effective framework for producing systematic innovation efforts in healthcare. Controlling healthcare cost increases, improving quality, and providing better healthcare are some of the benefits of this approach. |
The cost of medical care is increasing at an alarming and
unsustainable rate worldwide. Admittedly, a significant percentage of
these cost increases can be attributed to an aging population and
technological advances. These two factors, inevitable because of the
technological and demographic developments of modern society, are
largely beyond control. However, another significant source of
healthcare cost increases can be broadly characterized as unnecessary
operational inefficiency. Healthcare professionals have more control
over this factor. Inefficiency can be measured and changes implemented
to improve quality. These efforts provide more affordable and better
healthcare for a large percentage of the population.
Some operational inefficiencies are associated with the direct
medical service delivery process. Others are associated with the
administrative, logistical, and operational side of the healthcare
delivery system. Both areas can benefit from systematic process
innovation activities.
It is not surprising that some object to the notion of
industrialized healthcare delivery. However, industrialization is
essentially a conversion of artisan methods to more efficient,
cost-effective, streamlined systems for the delivery of products or
services (Heskett, Sasser, & Schlesinger, 1997; Levitt, 1976). For
example, the industrializing of shoe making made it possible for most
citizens of modern industrialized societies to own more shoes of higher
quality than royal families had a century ago.
During the past century, industry deployed a large arsenal of tools
and innovation approaches to achieve high levels of operational
efficiency. Economic history indicates that efficiencies in industry
were obtained primarily as the cumulative effect of a large number of
incremental improvements (Rosenberg, 1982). Lean Thinking and Six Sigma
are two process-innovation approaches that are currently popular in
industry (De Koning & De Mast, 2006; George, 2003; Robinson, 1990;
Smith, 2003; Stalk & Hout, 1990). Both provide a systematic
approach to facilitate incremental process innovations. Lean Thinking
emerged within the Japanese automobile industry after World War II
(Ohno, 1988) but can be traced back to the early days of the Ford Motor
Company (Ford & Crowther, 1926). Similarly, Six Sigma, originally
introduced by Motorola, is the culmination and synthesis of a series of
century-long developments in quality improvement (QI) (Box &
Bisgaard, 1987; Garvin, 1988; Snee, 2004) building on a number of other
approaches, in particular, Juran’s Trilogy (Juran, 1989). Lean Thinking
and Six Sigma have gone through parallel developments in recent years.
Both approaches are now also used widely in administration and service
areas, although they were originally applied to the manufacturing
environment (Snee & Hoerl, 2004). The latest development is a
synthesis of these two approaches (Hoerl, 2004). This article explores
their integration in the healthcare setting of a Dutch hospital.
Lean Thinking
The proliferation of Lean Thinking was facilitated by the
publication of Womack, Jones, and Roos (1990). Lean, as it is often
abbreviated, represents a fundamental break with Western manufacturing
traditions. Stated somewhat simplistically, the traditional mass
manufacturing concept of the West was based on the following
assumptions:
- A separation of “thinking” from “doing” is most effective.
- Defects are unavoidable.
- Organizations should be designed as a hierarchical chain of command.
- Inventories are necessary evils used to buffer production from fluctuations in market demand.
Toyota and other Japanese companies developed Lean Thinking as an
alternative paradigm. Lean is an integrated system of principles,
practices, tools, and techniques focused on reducing waste,
synchronizing work flows, and managing variability in production flows.
An important distinction in Lean is between value- and non-value-added
activities. Value-added activities contribute to what the customer
wants from a product or service (George, 2003). Everything else is a
non-value-added activity. The primary analytical tool in Lean is the
value-stream map, an extended process flowchart with information about
speed, continuity of flow, and work in progress. This tool highlights
non-value-added steps and bottlenecks and is used to guide QI
activities. The value-stream map provides a holistic picture of the
entire value chain in an organization.
Lean offers a number of standard solutions to common organizational
problems. Visual management, complexity reduction, 5S (a method for
organizing the workplace: sort, straighten, scrub, standardize,
sustain), cellular production, pull systems, line balancing, one-piece
flow, and single-minute exchange of dies are some of the more familiar
solutions (Shingo, 1989; Womack & Jones, 2003). The principles of
Lean are described in detail in the literature (George, 2003; Standard
& Davis, 1999).
Lean’s strength lies in its set of standard solutions to common
problems and its focus on the customer. Lean seeks to prevent
suboptimization by its focus on the entire value chain. However, Lean
is weak on organizational infrastructure, deployment plans, analytical
tools, QI, and control.
Six Sigma
Six Sigma was originally a concept for company-wide QI introduced by
Motorola in 1987. It was further developed by General Electric in the
late 1990s (Breyfogle, 1999; De Koning & De Mast, 2006; Harry,
1997; Pyzdek, 2001). The program is characterized by its
customer-driven approach, emphasis on decision making based on careful
analysis of quantitative data, and a priority on cost reduction
(Bisgaard & Freiesleben, 2004).
Six Sigma is deployed by carrying out improvement projects. Project
selection is usually based on a translation of the company strategy
into operational goals (Pyzdek, 2004). Six Sigma provides an
organizational structure of project leaders and project owners. Project
leaders are called Black Belts (BBs) and Green Belts (GBs). Members of
upper management play the role of project owners, or Champions.
Six Sigma’s approach is similar to that of good medical practice
used since the time of Hippocrates—relevant information is assembled
followed by careful diagnosis. After a thorough diagnosis is completed,
a treatment is proposed and implemented. Finally, checks are applied to
see if the treatment was effective. To operationalize this
problem-solving strategy, Six Sigma deploys five phases—define,
measure, analyze, improve, and control (DMAIC)—that are rigorously
followed whenever a problem, large or small, is approached. In the
define phase, a charter is drafted that includes a cost-benefit
analysis. If the cost-benefit analysis meets the company-established
thresholds, the charter will be accepted, and the project will continue
through the DMAIC process (i.e., the project becomes scheduled for
solution and assigned to a team headed by a GB or BB reporting to a
Champion). In the subsequent measure phase, baseline data are
assembled, and the diagnosis is started in earnest. The problem is
translated into quantifiable terms using critical-to-quality (CTQ)
characteristics. The analysis phase continues the diagnosis and
involves an identification of possible causal relationships between
inputs and the CTQs. After the diagnosis is completed, the team
proceeds to the improve phase and suggests a solution to the problem.
The GB or BB designs and implements process changes or adjustments to
improve the performance of the CTQ. Finally, in the control phase,
control systems are developed to ensure that improvements are
maintained and the new improved process can be handed over to the
day-to-day operations staff. Each of the five DMAIC phases involves
detailed plans that help to guide project leaders through the execution
of the QI project (De Koning & De Mast, 2006).
To secure a successful launch and deployment of Six Sigma, an
organizational infrastructure is created. For example, a deployment
plan for strategically relevant projects ensures an alignment of
project goals with the long-term organizational objectives. Further,
Six Sigma uses a stage-gate approach to project management whereby
projects are monitored carefully by Champions and appropriate actions
are taken if a project does not meet specified completion dates.
One perceived weakness of Six Sigma methods is its complexity. In
the case of simple problems with obvious and easy-to-implement
solutions, rigorous adherence to the Six Sigma problem-solving process
may be considered “overkill” and inefficient (George, 2003).
Furthermore, Six Sigma typically does not resort to standard solutions
to common problems as does Lean. Finally, the danger of suboptimizing a
process, while failing to take into account the entire value chain, is
ever present. Nevertheless, Six Sigma offers a structured, analytic,
and logically sound approach to problem solving, as well as a strong
organizational framework for its deployment.
Synthesis of Lean Thinking and Six Sigma
Lean provides a total system approach but is short on details,
organizational structures, and analytic tools for diagnosis. Six Sigma,
on the other hand, offers fewer standard solutions but provides a
general analytic framework for problem solving and an organizational
infrastructure. The ideal solution is to combine the two approaches.
Many practitioners have done so tacitly for quite some time. An
integrated framework for Lean Six Sigma consists of the following
elements:
- a structured approach: The deployment infrastructure is based on
Six Sigma organizational mechanisms consisting of a task force
deployment strategy using BBs, GBs, and Champions.
- project-based deployment: A project is a chronic problem scheduled
for solution (Juran, 1989). Nonstandard problems are solved only
project by project (Juran). Projects are classified as either “quick
wins” (Lean) or “advanced” (Six Sigma). Lean projects apply best
practices and focus on implementing standard solutions. Such projects
typically involve speed, reduction of lead time, inventory, and
processing time. Six Sigma projects apply to more general and complex
problems and involve solid, data-based analytic methods and statistics,
including QI and control methods. The problem-solving algorithm of
DMAIC is always used, and projects are monitored after each phase is
completed. Typical Six Sigma projects involve increasing quality,
decreasing defects, reducing variation, and increasing yield but more
generally involve systematic process innovation (Bisgaard & De
Mast, 2005).
- organizational competency development: A dedicated workforce of
Lean Six Sigma project leaders (Champions, GBs, and BBs) are trained in
a curriculum that resembles that of Six Sigma with additional Lean
components.
- organizational anchoring of solutions: To secure the implementation
of solutions and guard against backsliding, tasks and responsibilities
are clearly defined, procedures are standardized, and process controls
are imposed as part of an improvement project.
- linking strategy with project selection: Strategic objectives are
translated into performance indicators and tactical goals. These are
then used as a basis for project selection and help secure an alignment
of projects with the overall organizational strategy.
Lean Six Sigma Healthcare
Lean Six Sigma has recently also been applied in the healthcare
sector. George (2003), for example, describes pioneering work on Lean
Six Sigma at Stanford Hospital and Clinics. In this section our own
experience with Lean Six Sigma at the Red Cross Hospital in the
Netherlands is discussed. Of course, as is often the case, elements of
Lean Six Sigma were applied at the hospital years before the term
itself was used (Van den Heuvel, Does, & Vermaat, 2004).
The Red Cross Hospital in Beverwijk is a 384-bed, medium-sized
general hospital employing a staff of 966 with a yearly budget of 72.1
million. In addition to being a general healthcare provider, the Red
Cross Hospital also houses a national burn care center with 25 beds
that provides specialized services to all of the Netherlands. In 2004,
the Red Cross Hospital had 12,669 admissions, performed 11,064
outpatient treatments, and received 198,591 visits to its outpatient
units, of which 78,832 were first contacts.
The Red Cross Hospital began to use Six Sigma in 2002. However, the
hospital management had already introduced a basic quality assurance
system and obtained an International Organization for Standardization
9002 certification in 2000. Prior to the implementation of Six Sigma,
management also deployed a number of teams to work on specific QI
projects. At the time, management believed that these pre–Six Sigma
projects worked well. Indeed, a number of the projects were completed
with good results. However, over time, management discovered that an
organizational framework and programs for project management,
coordination, tracking, and support were necessary. Specifically, upper
management identified the following problems:
- Projects were not necessarily of strategic relevance.
- Projects did not always have a significant business case.
- A systematic project-tracking system was missing.
- There was no uniform method for project management and control.
- Too many projects were not completed.
At the end of 2001, the hospital management was introduced to Six
Sigma and found that this methodology provided solutions to many of
these problems. The initial implementation of Six Sigma at the Red
Cross Hospital is described in the literature (Van den Heuvel, Does,
& Bisgaard, 2005; Van den Heuvel, Does, & Verver, in press). In
addition to outlining Six Sigma’s management framework and lessons
learned relevant to healthcare, these articles also describe selected
examples of projects. A sampling will provide an impression of the
range of problems tackled:
- shortening the length of stay in chronic obstructive pulmonary disease patients
- reducing errors in invoices received from temporary agencies
- revising the terms of payment
- allowing parents to room in with their children
- reducing the number of patients requiring intravenous antibiotics
- shortening the preparation time of intravenous medication
- reducing the number of mistakes in invoices.
This list illustrates the important point that Six Sigma projects in
healthcare typically include both medical and administrative problems.
Indeed, some healthcare professionals think QI methods should address
only defects, such as medication errors. Our experience is that
significant gains can be made by widening the field of applications to
all processes and all operational inefficiency and waste.
The list above also shows that several of the Six Sigma projects
could just as well be characterized as Lean projects. For example,
reducing the length of stay and shortening the preparation time for
medication would be typical Lean objectives. On the other hand, the
Lean approach would come up short in projects involving reducing errors
in invoices received from temporary agencies, revising payment terms,
and correcting the number of mistakes in invoices. The distinction
between Lean and Six Sigma is artificial and often not helpful. An
integration of the two approaches and a general focus on process
innovation regardless of the origin of the tools and approaches would
be more productive.
Introducing Six Sigma
Six Sigma was implemented in earnest at the Red Cross Hospital in
September 2002 with the first wave of GB training. As is standard for
Six Sigma, the training was provided in two separate periods of 3 days,
2 months apart. The GBs were required to complete a project in
conjunction with their training. The financial threshold for initiating
a project was an estimated minimum saving of 20,000. GBs typically
worked 1 or 2 days a week on their projects. As part of the
project-management system, teams were carefully monitored and allowed
to proceed to the next phase of the DMAIC sequence only after
presenting the Champion with a report providing evidence that the
preceding phase had been completed. Teams were required to present
their results twice in front of the entire class. The second
presentation served as the GB graduation examination.
The first wave was followed by additional GB training waves
scheduled every 6 months thereafter. The Six Sigma approach was well
received. The GBs believed the Six Sigma training and
project-management system supported them well throughout the process of
a project. The data-driven approach was regarded as helpful in
establishing support of the teams during the implementation of the
results. The data-based analysis and decision making seemed to minimize
resistance to change.
After completing the training of the fourth group of GBs, it was
decided that the training process needed revision. The experience from
the previous waves of GB training indicated that many healthcare
problems involved various forms of wasted time. It was decided to
experiment with combining Lean with the DMAIC methodology. Materials on
time-value maps, value-stream maps, and the six standard forms of waste
were added to the curriculum in the analysis phase. Furthermore, the
curriculum for the improve phase was expanded to include complexity
reduction, cellular production, pull systems, line balancing, and the
5S method to reduce inefficiencies due to clutter and poor
organization. The total length of this revised training program was
expanded to 8 days, divided into two periods of 3 days and an
additional section of 2 days. The first Lean Six Sigma GB training
program started in September 2004 with 18 participants distributed in
teams of two or three GBs.
The Red Cross Hospital experience illustrates the key elements of
the Lean Six Sigma approach. First, the hospital applied the
organizational infrastructure typical of Six Sigma. Second, deployment
of QI was project by project. Third, the Lean Six Sigma approach was
based on developing organizational competency for innovation by
training a dedicated force of Lean Six Sigma project leaders and GBs.
Fourth, project selection had a strategic focus. In the present case
the Dutch Ministry of Welfare and Health had imposed serious budget
cuts on the Red Cross Hospital. This necessitated a strict focus on
cost reductions while maintaining or possibly improving quality.
Potential projects were suggested by Champions, all hospital department
heads. The final word to proceed was given by the general manager,
based on an evaluation of the project’s strategic relevance.
Lean Six Sigma Project Cases
Complexity Reduction in Hiring Personnel The Red
Cross Hospital spends yearly more than 1 million on temporary
personnel. Upper management suspected that the cost of hiring temporary
personnel was unnecessarily high. A preliminary investigation indicated
that errors on invoices was a problem resulting in significant
non-value-added rework and unnecessary readministration. Thus, the
project charter drafted by the GB and the project Champion stated that
the objective of this project was to reduce the number of mistakes on
invoices. The CTQ was the percentage of correct invoices received from
the temporary agencies.
A baseline study performed in the measure phase showed that only 15%
of the invoices were correct on first pass. The goal was set to improve
the CTQ to 100%. If this ambitious goal was achieved, the financial
saving was projected to be 36,000 per year. In the subsequent analysis
phase, a number of influential factors and causes were identified. The
most important were these:
- The signature of the department head was missing.
- A check on the hours worked was missing.
- Breaks were not registered.
- Mistakes occurred in the reported hours worked and time for travel.
- There was no check on the number of the temporary worker’s years of experience.
- The hourly wage was incorrectly stated on the invoice.
Although a large number of mistakes were recorded, this initial
analysis failed to unearth any single dominant type of mistake.
However, further analysis showed that the errors were symptoms of a
more significant problem. The root cause turned out to be that each of
the temporary agencies used a different worksheet. Moreover, no single
uniform standard for hiring and invoicing temporary workers was
followed. Each department had its own forms and procedures. From a Lean
perspective, having different worksheets for the same purpose is a
non-value-added complexity that should be eliminated. This led to the
following proposed improvements:
- A standardized worksheet was introduced.
- Requests for temporary personnel were centralized.
- The number of temporary agencies was reduced.
- A new administrative system for checking invoices was introduced.
In addition to these complexity-reduction measures, a visual
management system to signal mistakes was introduced. A new procedure
was introduced for hiring temporary personnel, requiring heads of
departments to use a single standardized worksheet. This worksheet
incorporated a “check invoice” feature designed to make it easy to
compare invoices submitted by the temporary agency with internal
documents, which made it easy to spot discrepancies. All of these
incremental changes resulted in reduced rework and significant cost
savings.
Reducing Operating Theater Starting Times Operating
theaters (OTs) are expensive and capacity-limiting facilities. Their
optimal utilization is paramount to efficient hospital management. The
general manager of the Red Cross Hospital suspected that the
utilization of the OTs was far from optimal, so a GB team was assigned
to increase the efficiency of the OTs. The GB team focused on the
starting times of the OTs. The official starting time was 8 am.
Baseline data collected in the measure phase showed that the average
starting time was 8:35 am, which suggested a significant loss of
capacity. As a realistic goal, it was decided to aim for an average
starting time of 8:15 am.
During the analysis phase the GB team discovered several factors that affected the starting time:
- Patients had not been administered the prescribed medication.
- Patients were brought in late by the referring department.
- The OT had insufficient manpower.
- Specialists had to make rounds prior to performing procedures in the OT.
- Anesthesiologists and other specialists were late.
While diagnosing these problems, the GB team found that the
underlying problem was a poorly defined process. This made planning
difficult. Tools were needed to manage this operational process.
Designing a new admissions process based on the following simple
principles was the solution:
- Patients must be present at the OT facility no later than 7:35 am.
- Before arriving at the OT, patients must receive preoperative preparation.
- The referring department and the anesthesiologists must be informed
about the planned OT treatment for the patient 1 day in advance of a
procedure.
To control this new process, visual management was introduced. At
the weekly staff meeting, a specially designed graph was reviewed,
showing the OT start times for the previous week. The feedback from
this control system was used to continually monitor the OT starting
times and provide valuable input on how to improve processes even
further.
Maintenance The Red Cross Hospital has a system in
place to manage mechanical breakdowns and irregularities. This system
registers a problem and assigns a maintenance person a “blue coupon”
with a description of the issue. After diagnosing the situation and
solving the problem, the maintenance person reports that the problem
has been solved. Although the system itself seemed efficient, the
resolution of problems often took an excessive amount of time. A
project team was chartered with the task of improving the process. The
CTQs were the number of active, not yet resolved blue coupons and the
lead time per blue coupon.
The first CTQ represents the overall cost in system downtime,
whereas the second provides an indication of the quality of the service
rendered. The following discussion will be limited to the first CTQ.
Analysis showed that the dominant problem was defective lights. It
was further discovered that the maintenance department did not have
standard operating procedures. Malfunctions were handled in an ad hoc
fashion with no accounting for urgency or priority. A number of
solutions were put into place to deal with this problem.
- prevention: Lights were turned off at night to extend the life of light bulbs.
- standard operating procedure: Guidelines were developed for dealing with breakdowns and failures.
- work planning system: Problems were divided into urgency categories.
- performance monitoring and visual management: Norms for fixing standard malfunctions were instituted and monitored.
The result of these simple systems changes was a significant
decrease in the number of blue coupons. The related financial saving of
this project was approximately 200,000.
These projects illustrate the benefits of combining Lean with Six
Sigma. In all cases a thorough quantitative diagnosis was made before
starting improvements. This is typical of Six Sigma. In all cases it
was possible to use off-the-shelf solutions to solve the problems. The
solutions were firmly anchored in the organizational infrastructure.
Managers can keep track of the performance of CTQs using visual
management systems and ensure that an organization does not revert to
old habits and past performance standards. The gains are maintained.
Conclusions
Unless healthcare leaders deal with spiraling healthcare costs, a
decreasing proportion of the citizens of industrialized societies will
be able to afford high-quality healthcare. If healthcare services are
inefficient, they cost more, and fewer can benefit from the technical
advances of modern medicine. A persistence of traditional service
practices will drain our economy. Continuous and relentless pursuits of
innovations in the service delivery process are necessary. The
industrialization of healthcare offers a viable alternative that can
provide better economy, greater efficiency, and better service.
Industrializing healthcare does not mean that healthcare becomes
less personal and that quality standards are compromised. For example,
a modern car, objectively speaking, is far cheaper and of significantly
higher quality than a handcrafted car manufactured 100 years ago.
Prepackaged vacations typically offer better deals with higher levels
of service than individually planned tours. Industrialization of
services typically improves quality while making those services much
more cost efficient.
The industrialization of healthcare service will require a large
number of innovations, especially pertaining to the delivery of
services. The popular perception is that innovation, like artistic
expression, is the product of genius. However, in today’s competitive
economic environment, this process must not remain a mystery. Indeed,
it need not be. Pianists and painters attend conservatories and art
schools to receive intensive training in their profession. Innovation,
like artistic performance, can be learned. The combination of Six Sigma
and Lean—with their tools, road maps, and management processes—is
essentially a carefully managed process for systematically scheduling
and carrying out innovation projects that can be taught, learned, and
performed with a high degree of success.
Lean and Six Sigma have strongly complementary strengths that are
particularly useful for systematically developing healthcare service
innovations. Synthesizing these approaches leads to an integrated
program combining the best of both programs. Lean Six Sigma
incorporates the organizational infrastructure and the thorough
diagnosis and analysis tools of Six Sigma with Lean analysis tools and
best-practice solutions for problems dealing with waste and unnecessary
time consumption.
The application at the Red Cross Hospital provides an illustration
of the significant benefits of the Lean Six Sigma approach. The
management of the hospital adopted the Lean Six Sigma organizational
infrastructure, developed organizational competencies, and instituted a
process for selecting strategically aligned projects combined with
rigorous project management. The net result was a process for
institutionalized systematic innovation that consistently delivers the
intended end results (Drucker, 1985). The adoption of similar programs
will make possible the successful replication of the outstanding
results obtained by the Red Cross Hospital in Beverwijk, the
Netherlands.
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Author's Biography Henk de Koning, MSc, studied physics and psychology at the University of Utrecht, the Netherlands. He is a consultant at the Institute for Business and Industrial Statistics (IBIS UvA), teaching courses in Six Sigma and supervising improvement projects in Dutch industry. His PhD thesis will present the results of a scientific study of Six Sigma methodology.
John P. S. Verver, MSc, studied mechanics at the University of Twente, the Netherlands. He worked as a Black Belt at DAF Trucks (a Paccar company). Currently, he works as a Master Black Belt at the Red Cross Hospital in Beverwijk and at the Canisius Wilhelmina Hospital in Nijmegen.
Jaap van den Heuvel, MD MBA, studied medicine at the University of Leiden and business administration at the University of Rotterdam, the Netherlands. For 7 years he was CEO at the Red Cross Hospital in Beverwijk. Currently, he is CEO at the Canisius Wilhelmina Hospital in Nijmegen.
Soren Bisgaard, PhD, earned a doctorate in statistics from the University of Wisconsin–Madison. Currently he is a professor of technology management at the University of Massachusetts, Amherst.
Ronald J. M. M. Does, PhD, earned a doctorate in mathematical statistics from the University of Leiden, the Netherlands. Currently he is a professor in industrial statistics at the University of Amsterdam and general manager of the Institute for Business and Industrial Statistics (IBIS UvA).
For more information on this article, contact Henk de Koning by e-mail at hkoning@science.uva.nl.
Acknowledgements The authors acknowledge Sue Ellen Bisgaard and Selena Kaplan for their editorial assistance and helpful comments on a previous version of this manuscript. Soren Bisgaard was supported by the Isenberg Program for Technology Management, the Isenberg School of Management, University of Massachusetts, Amherst.
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