1. Iso quality management system
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I. Contents of iso quality management system
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In this article…
Take a step-by-step look at how a multispecialty clinic implemented an ISO 9001 quality
management system and see the benefits the clinic reaped.
Physicians’ Clinic of Iowa (PCI) is a 50-physician multispecialty clinic located in Cedar Rapids,
Iowa. Physician specialties include cardiac surgery, otolaryngology, general surgery, neurology,
orthopedic surgery, podiatry, rheumatology, thoracic surgery, urology, and vascular surgery.
PCI employs 200 staff at five sites of care. PCI physicians manage approximately 98,000 E and
M encounters per year and perform over 52,000 surgical procedures annually. In the spring of
2001, leadership at PCI decided to develop a quality program for the clinic.
After evaluating healthcare options and reviewing industry quality systems, it was decided to
pursue ISO 9001 certification for the clinic. PCI leadership had joined the local chapter of the
American Society for Quality and participated in chapter events. This relationship enabled PCI
leadership to gain insight into quality management systems used in industry, and the information
helped in choosing ISO as the quality system for PCI to pursue.
ISO 9001 background
The International Organization for Standardization (ISO) was founded in Geneva in 1947.1 The
original purpose of the organization was to provide standardization of technical specifications for
products traded in the international marketplace. The term “ISO” is a word derived from the
Greek “isos,” meaning “equal.”
Over 150 countries are members of ISO, and there are more than 10,000 ISO standards used
worldwide. These standards determine how various products and services are produced, and
include standards for film speed, thickness of credit cards, compact disc format, and screw thread
number. Standardization has served an important role in promoting quality and compatibility of
products on a global basis .

2. The work of standardization is performed by ISO technical committees comprised of
representatives from interested member countries to address specific standards. Over the years
the concept of standardization has evolved from specific technical specifications to a broader
concept of generic quality management system standards.
The concept was first brought to the United States by the automobile industry in the late 1980s
because of a need to qualify the thousands of suppliers used by automobile manufacturers. This
effort was a concrete example of competitors working together to develop a quality framework
that would serve them and their customers.
The ISO 9001 family of quality management system standards was first developed in 1987 and
revised in 1994 and 2000.3 The automobile industry described the specific standards for its
suppliers in the QS 9000 system, and other industries have done the same with customized
quality management system standards for the particular industry.
In 2001, a set of preliminary standards for healthcare was published by the American Society for
Quality in partnership with the Automotive Industry Action Group.
Today, more than 500,000 companies are ISO certified internationally, with approximately
38,000 in the United States. Worldwide, 65 percent of certifications are in manufacturing; 90
percent in the U.S. are in manufacturing. Approximately 100 healthcare entities in North
America are certified, including 12 hospitals and 10 medical groups in the U.S.
There are many reasons for a healthcare facility to obtain ISO certification (ISO 9000 is the
family of standards; an entity is certified to ISO 9001:2000). Establishing an ISO 9001 quality
management system:
· Provides for work performance consistency
· Enables the discovery of causes of poor performance
· Stresses the process approach
· Defines goals and objectives for quality
· Provides benchmarks to measure improvements
Quality management requires customer focus and continual improvement. It provides for
accountability within the system and ensures that the most important functions are carried out. It
establishes a clear document system throughout the organization, a common language across the
organization, and common identifiers for customers/patients .
ISO requirements
An organization seeking ISO certification must describe and implement a quality management
system according to the requirements of the American National Standard for quality management
systems.
This initially involves utilizing the standard to write a quality policy, quality manual and quality
objectives, and then using the process approach to address the other requirements of the standard.
The conventional ISO saying is that you:
· Document what you do (“Say what you do”)
· Establish a process for the service
· Perform to your documentation (“Do what you say”)
· Provide the service based on the process
· Record the results of your work (“Record information”)
· Appropriately maintain all recorded information
· Audit the documentation for effectiveness (“Audit effectiveness”)
· Audit using the process approach

3. ISO 9001 requirements are based on eight quality management principles. The principals suggest
the use of a process approach in developing the quality system and are designed to increase
customer/patient satisfaction. The quality system requires continuous improvement. The eight
principles are:
1. Customer focus
2. Leadership
3. Involvement of people
4. Process approach
5. System approach to management
6. Continual improvement
7. Factual approach to decision making
8. Mutually beneficial supplier relationships
The principles are imbedded within the eight clauses of ISO 9001:2000 that comprise the quality
manual for an organization, and together they describe the quality management system.
An organization may seek certification after it has successfully implemented a quality
management system. Certification or registration is awarded after passing an audit by an
accredited registrar. Registrars are independent companies that are qualified by a worldwide
network of governing bodies.
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III. Quality management tools
1. Check sheet
The check sheet is a form (document) used to collect data
in real time at the location where the data is generated.
The data it captures can be quantitative or qualitative.
When the information is quantitative, the check sheet is
sometimes called a tally sheet.
The defining characteristic of a check sheet is that data
are recorded by making marks ("checks") on it. A typical
check sheet is divided into regions, and marks made in
different regions have different significance. Data are
read by observing the location and number of marks on
the sheet.
Check sheets typically employ a heading that answers the
Five Ws:
 Who filled out the check sheet
 What was collected (what each check represents,
an identifying batch or lot number)
 Where the collection took place (facility, room,

4. apparatus)
 When the collection took place (hour, shift, day
of the week)
 Why the data were collected
2. Control chart
Control charts, also known as Shewhart charts
(after Walter A. Shewhart) or process-behavior
charts, in statistical process control are tools used
to determine if a manufacturing or business
process is in a state of statistical control.
If analysis of the control chart indicates that the
process is currently under control (i.e., is stable,
with variation only coming from sources common
to the process), then no corrections or changes to
process control parameters are needed or desired.
In addition, data from the process can be used to
predict the future performance of the process. If
the chart indicates that the monitored process is
not in control, analysis of the chart can help
determine the sources of variation, as this will
result in degraded process performance.[1] A
process that is stable but operating outside of
desired (specification) limits (e.g., scrap rates
may be in statistical control but above desired
limits) needs to be improved through a deliberate
effort to understand the causes of current
performance and fundamentally improve the
process.
The control chart is one of the seven basic tools of
quality control.[3] Typically control charts are
used for time-series data, though they can be used
for data that have logical comparability (i.e. you
want to compare samples that were taken all at
the same time, or the performance of different
individuals), however the type of chart used to do
this requires consideration.

5. 3. Pareto chart
A Pareto chart, named after Vilfredo Pareto, is a type
of chart that contains both bars and a line graph, where
individual values are represented in descending order
by bars, and the cumulative total is represented by the
line.
The left vertical axis is the frequency of occurrence,
but it can alternatively represent cost or another
important unit of measure. The right vertical axis is
the cumulative percentage of the total number of
occurrences, total cost, or total of the particular unit of
measure. Because the reasons are in decreasing order,
the cumulative function is a concave function. To take
the example above, in order to lower the amount of
late arrivals by 78%, it is sufficient to solve the first
three issues.
The purpose of the Pareto chart is to highlight the
most important among a (typically large) set of
factors. In quality control, it often represents the most
common sources of defects, the highest occurring type
of defect, or the most frequent reasons for customer
complaints, and so on. Wilkinson (2006) devised an
algorithm for producing statistically based acceptance
limits (similar to confidence intervals) for each bar in
the Pareto chart.
4. Scatter plot Method

6. A scatter plot, scatterplot, or scattergraph is a type of
mathematical diagram using Cartesian coordinates to
display values for two variables for a set of data.
The data is displayed as a collection of points, each
having the value of one variable determining the position
on the horizontal axis and the value of the other variable
determining the position on the vertical axis.[2] This kind
of plot is also called a scatter chart, scattergram, scatter
diagram,[3] or scatter graph.
A scatter plot is used when a variable exists that is under
the control of the experimenter. If a parameter exists that
is systematically incremented and/or decremented by the
other, it is called the control parameter or independent
variable and is customarily plotted along the horizontal
axis. The measured or dependent variable is customarily
plotted along the vertical axis. If no dependent variable
exists, either type of variable can be plotted on either axis
and a scatter plot will illustrate only the degree of
correlation (not causation) between two variables.
A scatter plot can suggest various kinds of correlations
between variables with a certain confidence interval. For
example, weight and height, weight would be on x axis
and height would be on the y axis. Correlations may be
positive (rising), negative (falling), or null (uncorrelated).
If the pattern of dots slopes from lower left to upper right,
it suggests a positive correlation between the variables
being studied. If the pattern of dots slopes from upper left
to lower right, it suggests a negative correlation. A line of
best fit (alternatively called 'trendline') can be drawn in
order to study the correlation between the variables. An
equation for the correlation between the variables can be
determined by established best-fit procedures. For a linear
correlation, the best-fit procedure is known as linear
regression and is guaranteed to generate a correct solution
in a finite time. No universal best-fit procedure is
guaranteed to generate a correct solution for arbitrary
relationships. A scatter plot is also very useful when we
wish to see how two comparable data sets agree with each
other. In this case, an identity line, i.e., a y=x line, or an
1:1 line, is often drawn as a reference. The more the two
data sets agree, the more the scatters tend to concentrate in
the vicinity of the identity line; if the two data sets are
numerically identical, the scatters fall on the identity line

7. exactly.
5.Ishikawa diagram
Ishikawa diagrams (also called fishbone diagrams,
herringbone diagrams, cause-and-effect diagrams, or
Fishikawa) are causal diagrams created by Kaoru
Ishikawa (1968) that show the causes of a specific
event.[1][2] Common uses of the Ishikawa diagram are
product design and quality defect prevention, to identify
potential factors causing an overall effect. Each cause or
reason for imperfection is a source of variation. Causes
are usually grouped into major categories to identify these
sources of variation. The categories typically include
 People: Anyone involved with the process
 Methods: How the process is performed and the
specific requirements for doing it, such as policies,
procedures, rules, regulations and laws
 Machines: Any equipment, computers, tools, etc.
required to accomplish the job
 Materials: Raw materials, parts, pens, paper, etc.
used to produce the final product
 Measurements: Data generated from the process
that are used to evaluate its quality
 Environment: The conditions, such as location,
time, temperature, and culture in which the process
operates
6. Histogram method

8. A histogram is a graphical representation of the
distribution of data. It is an estimate of the probability
distribution of a continuous variable (quantitative
variable) and was first introduced by Karl Pearson.[1] To
construct a histogram, the first step is to "bin" the range of
values -- that is, divide the entire range of values into a
series of small intervals -- and then count how many
values fall into each interval. A rectangle is drawn with
height proportional to the count and width equal to the bin
size, so that rectangles abut each other. A histogram may
also be normalized displaying relative frequencies. It then
shows the proportion of cases that fall into each of several
categories, with the sum of the heights equaling 1. The
bins are usually specified as consecutive, non-overlapping
intervals of a variable. The bins (intervals) must be
adjacent, and usually equal size.[2] The rectangles of a
histogram are drawn so that they touch each other to
indicate that the original variable is continuous.[3]
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