1. healthcarequalitymanagement certification
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• qualitymanagement123.com/86-quality-management-interview-questions-and-answers
I. Contents of healthcare quality management certification
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Online health care quality management certificate programs are available for post-baccalaureate
or master's degree students. These programs focus on improving results in quality and risk
management related to the health care industry.
Essential Information
Fully online graduate certificate programs are available in health care quality management.
These online programs are typically intended for students who already possess a bachelor's
degree or master's degree in a related field. For employment, medical and health services
managers typically need a minimum of a bachelor's degree, although the requirements vary
greatly by employer.
Overview of Online Health Care Quality Management Certificate Programs
These certificate programs are offered entirely online, and some schools also have an in-person
program. Students learn quality process improvement and risk management skills tailored to
the health industry. Students must possess an undergraduate or graduate degree depending on
the school's requirements, typically in a health-related discipline. Credits in these programs
may be transferable towards further degree studies or qualify for continuing education credit.
Program Information and Requirements
Online health care quality and risk management certificate programs consist of 1-5 courses or
about 120 hours of study. Some require a capstone project at the culmination of the program.

2. Students may be able to complete registration and begin classes at their own pace, or may have
to adhere to the sponsoring school's academic calendar.
Requirements for most online programs include a valid e-mail address and access to a
computer equipped with high-speed Internet and a current version of a browser such as
Microsoft Internet Explorer or Mozilla Firefox. Not all browsers will work with some
programs, so technical specifications should be checked before enrollment. Courses are
typically delivered via a course management system such as ANGEL or Blackboard.
List of Common Courses
Online programs in health care quality and risk management are offered as separate courses, or
as one course covering several different topics. Some common courses are listed below.
Process Improvement and Strategic Management Course
Students learn evolving skills in health care quality-improvement applications and methods.
The focus is on effective use of techniques and tools available for health care managers.
Health Care Laws and Regulations Course
The standards, regulations and laws associated with health care management are examined in
this class. Accreditation of health care organizations, patient safety goals, state license
requirements and standards are topics of study.
Information Systems Management in Health Care Course
Students learn to implement, use and maintain different medically-related computer systems.
Systems related to database management, electronic medical records and managerial
transactions are covered.
Career Information for Graduates
According to the U.S. Bureau of Labor Statistics (BLS), employment for medical and health
services managers was projected to grow by 22%, faster than the average for all occupations,
from 2010-2020 (www.bls.gov). This growth is expected to be driven in part by the need to
control costs while improving quality and efficiency due to the accountability demands of
insurance companies and Medicare. As of May 2012 the BLS reported that medical and health
services managers made a median annual income of $88,580. The top industry employing these
managers was medical and surgical hospitals, followed by doctor's offices, outpatient clinics,
home health care centers and nursing homes.
Continuing Education and Certification Information
For those wishing to pursue further education in health care management and administration,
the Commission on Accreditation of Healthcare Management Education (CAHME) reported 72
accredited master's degree programs in this area in 2008. A master's degree in health-related
concentrations or administration can provide more opportunities for employment in the field.
Doctoral degrees in health care administration are also available, and online options are
available for both master's degree and Ph.D. students.
==================

3. 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,
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

4. 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.
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.

5. 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
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

6. 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
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

7.  Environment: The conditions, such as location,
time, temperature, and culture in which the process
operates
6. Histogram method
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]
III. Other topics related to healthcare quality management certification (pdf
download)
quality management systems
quality management courses
quality management tools
iso 9001 quality management system
quality management process
quality management system example
quality system management
quality management techniques

8. quality management standards
quality management policy
quality management strategy
quality management books