+1(978)310-4246 credencewriters@gmail.com
  

Description

Question 1

. Evans & Lindsay offer a quick case study on the application of Six Sigma in reducing medical errors. Singh (2014) offers a more expanded study of an application in medical surgeries. Because both cases involve Six Sigma, we might expect to see similarities in the way the cases involved different stakeholders and use process mapping to understand requirements.

Discuss how these two cases compare to each other, both similarities and differences. How does your general knowledge of Six Sigma make it easier to understand and assimilate the cases? What people, approaches, tools were similar or different across the two cases?

Question 2

: Refer to the following article:

Case Study_Dont Lose Patients.pdf

and summarize it in one page!

Question 3

: Refer to Problem 8 in our text, page 504-505 and provide good answer to the posted question.

Question 4:

In a one-page essay, explain the Taguchi Loss Function, and describe some of the negative consequences that can occur when process managers focus only on staying within specification limits rather than driving toward minimal variation around targets.

combined batches? For each individual batch?
4. Expand Table 9.2 for sigma levels from 3.0 to 6.0 in
increments of 0.1 on a spreadsheet. Construct a chart
showing dpmo as a function of the sigma level.
5. Nanos Electron, Inc. manufactures 75,000 circuit
boards per month. A random sample of 800 boards
is inspected every week for three characteristics.
8. The current process for fulfilling a room service
request at the Luxmark hotel can be described as
follows. After the tray is prepared at the room service
station, the server proceeds to the room, knocks on
the door, sets up the meal, has the customer sign the
check, asks if anything else is needed, and then
returns to the room service station.
Copyright 2017 Camgage Learning. All Rights Reserved. May not be copied, scamad, se deplicated, in whole or in part. Due to electronic rightu, xe third party content may be suppened from the Blood and be hapteris)
ditcial review darmad that any supprewed content des ant materially affect the wall learning experience. Cengage.coming roves the right to see additional comment at any time if subsequent rights restrictices raquine it.
CHAPTER 9 Process Improvement and Six Sigma
505
FIGURE 9.25
Flowchart for a Hospital Pre-Admission Test (PAT) Process (Problem 7)
1. Surgeon’s office
calls OR scheduling
with possible date.
2. OR scheduler
checks date
availability
3. Surgeon and OR
scheduler reach
agreement on
surgery date.
4. OR scheduler
schedules PAT
and surgery date
in hospital system
5. OR scheduler
informs surgeon’s
office of PAT date
9. Beeper signals
patient to come
to registration
8. Patient given
beeper and goes
into waiting room
7. Patient arrives
at hospital at
scheduled
PAT time
6. Surgeon’s office
informs patient of
PAT date and
pertinent information,
10. Registration occurs:
• Contact information
• Family information
• Insurance informatic
Collect payment
11. Registrar
enters patient’s
info into hospital
system
12. Registrar
signals PAT nurse
and takes patient
to waiting room
13. PAT nurse
retrieves chart
and reviews
chart orders
15. Patient
assessment starts:
• Date/time
EKG completed
14. PAT nurse
invites patient to
office for consult
18. Direct and
educated on where
to go in hospital
No
16. Does patient
need labor
X-ray?
20. Patient
goes home.
No
Yes
19. Complete
labs and
X-ray
17. Is lab
X-ray
complete?
Yes
Garage learning
Source: Todd Creasy and Sarah Ramey, “Don’t Lose Patients,” Quality Progress, February 2013, 42-49.
a. Draw a flowchart that describes this process.
b. From the perspective of creating a high level of
customer satisfaction from this experience,
what improvements might you suggest to
enhance this process? Think creatively!
9. Placewrite, Inc., an independent outplacement
service, helps unemployed executives find jobs.
One of the major activities of the service is pre
paring resumes. Three word processors work at
the service typing resumes and cover letters.
Together they handle about 120 individual clients.
Turnaround time for typing is expected to be
24 hours. The word-processing operation begins
with clients placing work in the assigned word
processor’s bin. When the word processor picks
up the work (in batches), it is logged in using a
time clock stamp, and the work is typed and
printed. After the batch is completed, the word
processor returns the work to the clients’ bin,
logs in the time delivered, and picks up new
work. A supervisor tries to balance the workload
for the three word processors. Lately, many of the
QUALITY in PRACTICE
An Application of Six Sigma to Reduce Medical Errors51
Medication administration and laboratory processing laboratory tests were known to be a significant source
results reporting are examples of complex systems in of error at the hospital. It is for these reasons that these
health care that are known to be error prone. As two areas were targeted for initial study.
described in the report of the National Academy of A consortium was created by four Milwaukee-
Sciences Institute of Medicine, medication errors are a based organizations committed to the development
substantial source of preventable errors in hospitals, but of an approach to reduce errors and improve patient
result in part from poorly designed complex systems. At safety. The consortium members include the Medical
Froedtert Hospital in Milwaukee, Wisconsin, errors with College of Wisconsin, Froedtert Memorial Lutheran
Il medication drips and laboratory processing and results Hospital, the American Society for Quality, and Secur-
reporting were well documented. Additionally, errors in Trac, a company formed specifically to develop tech-
ordering, transporting, analyzing, and reporting clinical nologies to improve patient safety. The consortium is
right 2017 Cangage Learning. All Rights Reserved. May st be copied camed, te duplicated, in whole or in part. Due to cladirmie right me third party content may be apped from the clock and be hape
view.domend that any supprewed content does not materially affect the wall learning experience. Cengagel.coming reserves the right to remove additical comerte at any time if sheequent rights restrictions
498
PART 2 Tools and Techniques for Quality
currently addressing three major efforts: (1) improved audits were rated at level 2 and four were rated at
identification and reporting of health care errors, level 3. Root cause analysis was employed to deter-
(2) deployment of the Six Sigma methodology to mine the cause of the discrepancies. Work was then
reduce errors, and (3) testing and implementation of begun to affect the accuracy of infusion rates.
technical solutions to improve patient safety. the Using Six Sigma methods and statistical tools, the
center of this approach is the effort to determine team also examined the hospital’s clinical laboratory
whether the Six Sigma error reduction methodology process. Key elements in the acquisition, laboratory
can be successfully applied in health care.
analysis, and reporting of patient specimens were iden-
Using Six Sigma methods and selected statistical tified. The steps included (1) physician order, (2) order
tools, Froedtert Hospital’s processes for medication deliv- entry, (3) matching the order to the patient, (4) collect-
ery were evaluated with the goal of designing an ing the specimen, (5) labeling the specimen, (6) trans-
approach that would decrease the likelihood of errors. porting the specimen, (7) analyzing the specimen,
The design employed the classic Six Sigma process steps. (8) reporting the results, and (9) entering the results
A multidisciplinary group of physicians, nurses, pharma- into the patient’s chart. Each of these steps is subject
cists, and administrators identified medication delivery to error. Applying Six Sigma analysis, the steps subject
by continuous IV infusions as a process subject to sub- to the most errors were identified. These steps were:
stantial error. Continuous IV infusions are used in many order entry by the unit clerical staff, transportation of
clinical settings and errors can severely impact patient the specimens to the lab, and analysis of specimens in
well-being. Initially, the focus was on five specific the lab. To identify, define, and reduce these errors, a
medications. Soon it was realized that the number was laboratory error reduction task force was established. It
too small to permit quantification of error rates. The included members from administration, lab, nursing,
scope of the project was expanded to 22 medications clerical staff, information systems, and quality manage-
delivered by continuous IV infusion. Team members ment. The task force first developed a process map so
developed a process map (flowchart) to delineate each that all members could appreciate the complexity and
step in the procedure for continuous IV medication infu- vulnerability of the entire process. The process map
sion. The process map revealed nine steps: (1) physician provided the task force with the tools to analyze the
order, (2) order review, (3) pharmacist order entry, clinical laboratory problem in depth. The FMEA tech-
(4) dose preparation, (5) dose dispensing, (6) infusion nique was employed to arrive at a risk priority number
rate calculation, (7) IV pump setup. (8) pump program- (RPN) so that steps in the laboratory analysis process
ming, and (9) pump monitoring
could be prioritized in terms of their vulnerability to
Each of the steps was subjected to a failure modes error. Again, order entry, transportation, and analysis
and effect analysis (FMEA—see Chapter 7) and scored of specimens were identified. Statistical tools, including
on a scale of 1 to 10 for three categories: frequency of correlation and regression, analysis of variance, confi-
occurrence, detectability, and severity. The scores were dence intervals, and hypothesis testing, were employed
multiplied together to yield a risk priority number (RPN) to evaluate the laboratory process further.
for each step. Eighteen months of retrospective medica- The analysis of medication delivery by IV infusions
tion error reports were reviewed to provide additional served as a good example of deployment of Six Sigma
data for the RPN calculation. This review confirmed the methodology to reduce error and improve patient
FMEA results that IV rate calculations and IV pump safety in a health care setting. Significant variability
setup were the two most error-prone steps in the M in the ordering and processing of IV drips was identi-
infusion process. Initial efforts to delineate and reduce fied. Lack of standardization in many steps of the pro-
Each of the steps was subjected to a failure modes error. Again, order entry, transportation, and analysis
and effect analysis (FMEA—see Chapter 7) and scored of specimens were identified. Statistical tools, including
on a scale of 1 to 10 for three categories: frequency of correlation and regression, analysis of variance, confi-
occurrence, detectability, and severity. The scores were dence intervals, and hypothesis testing, were employed
multiplied together to yield a risk priority number (RPN) to evaluate the laboratory process further.
for each step. Eighteen months of retrospective medica- The analysis of medication delivery by IV infusions
tion error reports were reviewed to provide additional served as a good example of deployment of Six Sigma
data for the RPN calculation. This review confirmed the methodology to reduce error and improve patient
FMEA results that IV rate calculations and IV pump safety in a health care setting. Significant variability
setup were the two most error-prone steps in the N in the ordering and processing of IV drips was identi-
infusion process. Initial efforts to delineate and reduce fied. Lack of standardization in many steps of the pro-
errors focused on these two steps.
cess posed the greatest risk for system failure. Those
Because it was not known how often errors went steps with the highest degree of variability and the
unrecognized or unreported, an audit was conducted greatest chance for error were
to determine whether the prescribed dose rate
matched the actual infusion rate. Two weeks of 1. MD ordering practices (ie., lack of standardization in
audit data were collected and the resulting 124 data medication description, dosage, concentration, etc.)
points were rated on a discrepancy scale of 1 to 3 2. IV drip preparation (lack of standardization by
(1 for a 1 ml/hr discrepancy, 2 for a 1-5 ml/hr dis- pharmacy and nursing of IV bag concentrations)
crepancy, 3 for a > 5ml/hr discrepancy). Ten of the 3. RN labeling and documentation of IV concentrations
2017 Cengage Learning. All Rights Reserved. May not be copied, samed, te duplicated in whole or in part. Due to electronic right come find pay content may be approved from the Book and le Chapter
lsdamed that any apprewed content does not materially affect the wall learning experience. Cengagel.coming even the right to remove additional comentat any time if bequent rights restrictions require
CHAPTER 9 Process Improvement and Six Sigma
499
In these three areas, a multidisciplinary task force force identified opportunities to reduce variation in
created standards to reduce variation Specific inter- select steps of the laboratory process. Alternate
ventions included implementation of standardized means of identifying specimens, changes in the
physician order sheets, a policy requiring preparation approach to “point of care” laboratory analysis, decen-
of all IV medications in a standard concentration, and tralization of some laboratory tests, and a revised sys-
use of color-coded labels when nonstandard concen- tem to order and process stat lab tests was put into
trations were in use. Thirty days after implementation, place. Effectiveness monitoring continues as does mea-
measurable improvement was evident. Level 1 discre- surement of sustainable error reductions. These efforts
pancies fell from 47.4 percent to 14 percent. Level 2 marked the beginning of a long laboratory redesign
discrepancies fell from 21.1 percent to 11.8 percent process aimed at driving out error, reducing turn-
and level 3 discrepancies fell from 15.8 percent to around time, and improving patient safety.
2.9 percent. Though far from achieving a six-sigma
level of performance, substantial efforts continue to Key Issues for Discussion
move toward that goal.
1. How did the team use process mapping as a key
The laboratory project proved to be more complex. part of the Six Sigma process? What value did
It was evident early on that the scope of this complex process mapping have?
system was too broad for an initial effort. The project 2. Why were the teams and task forces multidisci-
was broken down into smaller individual steps of the plinary in nature? What benefits does this
larger process. Once refocused, the appointed task approach have?

Purchase answer to see full
attachment

  
error: Content is protected !!