PROJECT NAME: Reducing Blood Draws In Critically
Ill Patients
Institution: The University of Texas M.D. Anderson Cancer Center
Primary Author: Melissa McLenon, DNP, APRN, ACNP-BC
Secondary Author: Gregory Botz, MD
Course Participants: Natalie Clanton, RN, CCRN, Latoi Tatum, MHA, Blake
Brookshire, MD
Project Category: Efficiency
Overview
Several studies have shown that diagnostic laboratory testing is a significant
contributor to anemia in critically ill patients. Phlebotomy practices also contribute to
the frequency of red blood cell transfusions, and research has proven the transfusion
of blood products is associated with higher mortality and longer intensive care unit
(ICU) length of stay. We recognized the need to decrease the frequency of blood draws
among critically ill patients in our ICU. Our team collected 4 weeks of baseline data to
determine the frequency and volume of blood draws per 24 hours, per critically ill
patient (figure 1)in a 10 bed medical ICU pod. We enlisted key stakeholders, including
members of the multidisciplinary ICU team, the clinical laboratory, information
technology, and administrative staff to determine the factors associated with the high
frequency of blood draws. Through the alignment of our goal with the institutional
goals, we strived to improve operating efficiency, both at the departmental and
institutional level.
Aim Statement
To reduce the frequency of blood draw events, per 24 hours, per critically ill patient,
by 20% by June 10, 2012.
Measures of Success
Pre-intervention data was collected for 4 weeks, including the volume and frequency
of blood draw events on each patient in a 10 bed medical ICU pod. We also collected
data on the number of lab tests ordered as well as the number of ordering providers.
We then collected an additional 3 months of data. The goal was to reduce the
frequency of blood draw events per ICU patient per 24 hours by 20%.
Use of Quality Tools
We used a brainstorming session with key stakeholders to identify factors that were
important to blood draws in the ICU. We then created an affinity diagram to
consolidate ideas which became the elements of our Ishikawa diagram (figure 2).
Next, we developed a process chart (figure 3) to determine where potential
interventions may have the greatest impact. Once data was being collected, we
generated run charts (figure 4, 5) to reflect the data over time.
Interventions
To focus on potential interventions, the ICU staff completed a survey on their
perceptions about blood draws in the ICU, and provided feedback on efforts to
minimize blood draws in critically ill patients. The most common factor identified in
excessive blood draws was related to inadequate communication. Therefore, our
primary intervention was aimed at improving communication about lab testing and
blood draw frequency among the healthcare team. We added a lab testing and blood
draw item to our ICU daily rounding checklist to focus a multidisciplinary discussion
among the ICU team.
We also formalized a discussion between the licensed laboratory technicians (LLTs)
to reduce the redundancy of ordered tests and frequency of one-off blood draw
events, and to reduce scheduled blood draws during blood products or electrolyte
administration (figure 6). This increased the ICU nurse and LLT autonomy to
reschedule non-emergent blood draws until blood products and electrolyte
replacements were completed. We also formalized a process to allow non-emergent
interval lab tests to be clustered with the next scheduled lab draw event, unless
specifically needed at that time.
In addition, the baseline data were shown to the ICU physicians and midlevel
providers (MLP) during staff meetings as an education strategy. Discussion included
attention to provider variation in lab ordering practices, lab testing redundancy, serial
labs order frequency and duration, and laboratory order set utilization. This was
followed by additional brainstorming on our current practices and the potential
impact on our patients.
Results
Baseline data showed a wide practice variation among providers. The number of
blood draw events ranged from 2-14 per patient per 24 hours, with an average of 3.99
per patient. Post implementation, the number of blood draw events ranged from 0-12
and the average number of blood draws per patient per 24 hours decreased to 2.97.
Pre-intervention, blood volume collected with each blood draw event ranged from 6cc
to 250cc per patient per 24 hours, with an average of 46.79cc per patient. Post
implementation, the volume of blood collected with each blood draw ranged from 0165cc, with an average of 36.84cc per patient per 24 hours.
Overall, there was a 25% reduction in the number of blood draws and a 21%
reduction in the volume of blood drawn with each blood draw following the
interventions. Also, the median and mode of the two variables decreased over the 3
month post-implementation period.
Revenue Enhancement /Cost Avoidance / Generalizability
The return on investment for this project is multifaceted. It is difficult to assign costs
to blood draw events due to our current charge system. This has made us aware of
another opportunity for improvement as this project moves forward. The charge for
our routine laboratory tests (chemistry panel, complete blood count, arterial blood
gas) is estimated at $620. That does not include the personnel and equipment that is
necessary to complete the testing.
Another potential cost savings associated with a decrease in the volume of blood
draws is a decrease in the frequency of blood transfusions. The average ICU length of
stay (LOS) is 5 days. However, the LOS varies from days to months in the medical ICU.
By reducing the daily frequency and volume of blood draws, there will be a decrease
in the degree of anemia associated with the blood draws. Ultimately, this will result in
a decrease in the number of blood transfusions, as well as the costs and complications
associated with blood transfusions. The charge for an uncomplicated unit of packed
red blood cells is approximately $1400. However, that does not include the
preparation nor the monitoring required to transfuse the blood. Nor does this charge
account for complicated transfusions, pre-medications, or transfusion reactions.
Several studies have shown complications associated with blood transfusions include
an increase in ICU LOS, mortality, and ventilator days, transfusion related acute lung
injury, and other adverse reactions.
Another potential cost savings associated with a decrease in the frequency of blood
draws is a decrease in the incidence of central line associated blood stream infections
(CLABSI). Because most of our critically ill oncological patients have central venous
catheters, the blood is drawn from these catheters or arterial catheters. Each time
these lines are accessed for a blood draw, there is a risk of contamination and line
infection. The cost associated with a CLABSI is estimated at $14,000 per critically ill
patient.
Due to the potential complications associated with excessive blood draws, decreasing
the frequency potentially results in improved ICU throughput. This will allow for
more timely transfer of patients out of the ICU to provide access and availability for
critically ill patients who require ICU services.
Reducing the frequency of blood draws results in quality outcomes as well as clinical
and financial outcomes. Patient and provider satisfaction is difficult to measure in
terms of cost, but the quality of care is greatly improved. Our patients have the right
to care that is safe, efficient, equitable, effective, timely, and patient centered.
Conclusions and Next Steps
Studies have shown that excessive blood draws in the ICU results in increased
mortality, LOS, and need for blood transfusions. Our team identified that our patients
were experiencing frequent blood draws and redundant laboratory testing, mostly
related to a lack of communication among the ICU multidisciplinary team. Our
interventions to reduce the frequency and volume of blood draws per critically ill
patient per day were successful.
We want to expand the scope of our project to include critically ill surgical patients,
who will also benefit from a reduction in the frequency of laboratory testing. The
surgical teams will be included in this process. We will also focus our attention on
other factors identified in the process map and Ishikawa diagram which contributes
to the frequency and redundancy of laboratory testing.
Another goal is to meet with representatives from information technology and
laboratory medicine to evaluate methods of order entry modification in an effort to
cluster lab orders, alert notifications for redundant labs, automatic discontinuation of
serial labs at 24 hours, and other technology issues that may be modifiable. Also, we
will evaluate alternates to improve our charge system in an effort for departments to
receive feedback on the costs associated with the laboratory testing.
We hope to see our efforts to minimize the frequency and volume of blood draws and
laboratory testing spread throughout the institution. We will continue to reinforce our
education and training and seek support from departmental and institutional
leadership.
Data Collection Tools
6am-12pm
12pm-6pm
6pm-12am
12am-6am
Number of vials
Bed
1
cc of blood
Number of draws
Number of vials
Bed
2
cc of blood
Number of draws
Number of vials
Bed
3
cc of blood
Number of draws
Number of vials
Bed
4
cc of blood
Number of draws
Figure 1: Data collection tool
Ishikawa Diagram
Errors
System
Equipment
lack of blood
conserving system
2 different systems
clotted blood
delay in stat orders
lost labs
lack of pedi tubes
inability for add-ons
lack of computer prompts
order entry error
unable to view
redundant labs
scheduled serial labs
acuity
order set
Process
read only access
unaware of scheduled labs
nurses/RT
lack of
communication
lack of awareness
.
different providers ordering labs
tube system
heirarchial issues
provider preferences
People
Figure 2: Ishikawa (cause and effect) diagram
Problem
Statement
Excess volume
and frequency of
lab draws among
critically ill
patients.
order is
placed in
Clinic
Station
Multiple
providers
ordering labs
without
discussion
Order is
placed in
que for PSC
PSC
acknowledges
order for labs
Process for Lab Ordering
Request for lab
is generated in
clinic station
STAT
lab?
No
Request processed
from Clinic station
to Cerner
(approx. 15 min)
Lab requisition
generated
Yes
System does
not
automatically
time with other
scheduled labs
No
coordination of
timing w/other
scheduled labs
ICU team
reviews lab
results
Results are
placed in Clinic
station
No
Critical
results
Lab is
processed
Page LLT to
draw lab
Lab is received
and logged
into system
Multiple labs on
multiple patients
sent to lab via
pneumatic tube
system
Yes
Lab calls
ICU team
Lack of
available
tubes
No
Action
needed
Yes
Intervention
Monitor
patient
Figure 3: Process Map
Affect on
Patient
LLT draws lab
No contact
with RN
prior to
drawing
labs
70
Pre-intervention MEAN = 3.99
Pre-intervention MEAN = 46.79
5/14
5/15
5/16
5/17
5/18
5/19
5/20
5/21
5/22
5/23
5/24
5/25
5/26
5/27
5/28
5/29
5/30
5/31
6/1
6/2
6/3
6/4
6/5
6/6
6/7
6/8
6/9
6/10
2/13
2/14
2/15
2/16
2/17
2/18
2/19
2/20
2/21
2/22
2/23
2/24
2/25
2/26
2/27
2/28
2/29
3/1
3/2
3/3
3/4
3/5
3/6
3/7
3/8
3/9
3/10
3/11
Frequency of Draws (per pt per day)
7
5/14
5/15
5/16
5/17
5/18
5/19
5/20
5/21
5/22
5/23
5/24
5/25
5/26
5/27
5/28
5/29
5/30
5/31
6/1
6/2
6/3
6/4
6/5
6/6
6/7
6/8
6/9
6/10
2/13
2/14
2/15
2/16
2/17
2/18
2/19
2/20
2/21
2/22
2/23
2/24
2/25
2/26
2/27
2/28
2/29
3/1
3/2
3/3
3/4
3/5
3/6
3/7
3/8
3/9
3/10
3/11
ml of Blood Drawn (per pt per day)
Average Frequency of ICU Blood Draws
6.5
Post-Intervention MEAN = 2.97
5.5
6
5
4.5
4
3.5
3
2.5
2
1.5
1
0.5
0
Figure 4: Frequency of blood draws pre- and post-intervention
Average Daily Volume of Blood Draws
Post- intervention MEAN = 36.84
60
50
40
30
20
10
0
Figure 5: Daily volume of blood pre- and post-intervention
Process for Lab Ordering
order is
placed in
Clinic
Station
Multiple
providers
ordering labs
without
discussion
Order is
placed in
que for PSC
PSC
acknowledges
order for labs
Request for lab
is generated in
clinic station
System does
not
automatically
time with
other
scheduled labs
No
coordination of
timing w/other
scheduled labs
ICU team
reviews lab
results
Results are
placed in Clinic
station
No
Critical
results
Lab is
processed
STAT
lab?
No
Request processed
from Clinic station
to Cerner
(approx. 15 min)
Yes
Page LLT to
draw lab
Lab is received
and logged
into system
Multiple labs on
multiple patients
sent to lab via
pneumatic tube
system
Yes
Lab calls
ICU team
Lack of
available
tubes
No
Action
needed
Yes
Intervention
Monitor
patient
Affect on
Patient
Figure 6: Process map post-intervention
Lab requisition
generated
Interventions
LLT draws lab
No contact
with RN
prior to
drawing
labs