CRIT Research Protocol
1. Study Team
PI:
Co-investigator:
Research Coordinators:
Research Associate:
2. Project Title
Impact of a decision support rule on appropriate transfusion of red blood cells
3. Introduction
Background/Significance
Transfusion of red blood cells may be life-saving in the event of acute hemorrhage or other lifethreatening condition. Transfusion, however, is not without risk to the patient. Potential for
transmission of infectious agents or development of non-infectious complications such as
transfusion related acute lung injury (TRALI) argues for thoughtful consideration of each
transfusion.
In light of this balance between transfusion risk and benefit, the transfusion committee of
Children’s Hospitals and Clinics of Minnesota has maintained a set of guidelines for appropriate
transfusion of blood products, including red blood cells. These guidelines, which have been in
place for over 20 years, are regularly updated based on periodic literature review.
All transfusions at Children’s are reviewed for compliance with these guidelines. Those which fall
outside of guideline parameters undergo chart review as part of the quality assurance process of
the institution. The current process requires manual review of laboratory parameters (e.g.,
hemoglobin level) at the time of the transfusion order.
Since the installation of the Cerner electronic medical record, several “rules” have been developed
to assist providers with clinical decision-making. For example, if an order for a nephrotoxic drug is
placed, laboratory values for patient renal function are automatically evaluated and, if an
abnormality exists, the provider is notified of a need for alteration in drug dosing via a “pop-up”
screen before the order may be signed.
A recent article described the impact of a decision-support tool on blood transfusion in children
[1]. This tool decreased the number of transfusions in a general ward setting, but did not reach
significance in their intensive care unit. This tool was based on a recently published article
recommending optimal hemoglobin for patients in the critical care unit [2].
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A similar decision-support “rule” may be developed at [Insert Institution name] based on data
already in the electronic medical record as part of routine patient care. This rule may be built to
“pop-up” on screen to notify the provider that the child’s laboratory and hemodynamic
parameters are outside of Children’s transfusion guidelines. The provider will then be forced to
choose to continue prior to signing the transfusion order.
Significance
Limiting inappropriate transfusion of blood products will also minimize risk of transfusion-related
complications including transfusion reaction, transmission of infectious diseases, and TRALI.
Research Question
Will the implementation of an automated decision-support “rule” regarding patients that are
being considered for red blood cell transfusions have an effect on the number of patients who
receive transfusions?
4. Study Design and Methodology
Hypothesis
Implementation an automated decision-support “rule” will significantly decrease the number of
red cell transfusions that fall outside of guideline parameters at Children’s Hospitals and Clinics of
Minnesota.
Overview/Scope
Study Design
This will be a both a retrospective and prospective, observational study.
Time Frame/Duration
Information from all transfusions at Children’s Hospitals and Clinics of MN for one year prior to
implementation of the decision support tool will be used retrospectively to compare to
prospective transfusion information for one year after initiation of the tool.
Analysis
Sample Size
The data for this current project will consist of the total number of hospital admissions along with
patient characteristics, average pre transfusion hemoglobin, transfusions per patient day, and
alert frequency. All data will be de-identified and no personal health information will be gathered
or analyzed. When the data has been gathered it will be analyzed in two parts. First the preintervention cohort will be compared to the post-intervention cohort. Second the institutions
randomized to the early start group will be compared to the institutions randomized to the late
start group. The statistical analysis will be managed with the assistance and collaboration with
biostatisticians provided by Stanford University School of Medicine.
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5. Subjects
Subjects
All patients who meet inclusion criteria will be included. We will limit the time period to one year
prior to the implementation of the decision tool and one year after.
Enrollment
We will be seeking a waiver of consent for this study. All eligible patients will be included.
Inclusion Criteria
Packed red blood cell transfusion information on
 Patients age 1 month to 18 years of age
 Inpatient admission > 24 hours duration
Exclusion Criteria
 Age <1 month
 Age < 18 years
 Active history of congenital heart disease
 History of sickle cell, thalassemia
 Transfusions administered in the operating room
 Patients on ECMO
6. Study Procedures
Data Requirements
Data will be collected retrospectively from patient charts by the study staff. We will not contact
patients for information regarding this study.
Baseline data to be collected (for calendar year 2011 prior to alert implementation):
-Total number of inpatient admissions
-Packed red blood cell transfusions per patient day
-Average pre-transfusion Hgb (Defined as the most recent Hgb level drawn prior to
transfusion)
Post-alert implementation data
-Same as above (time period to be determined)
Follow-Up
There will be no follow-up for this study.
Patient Withdrawal, Completion, Death
Because we are asking for a waiver of consent, there will be no withdrawal for this study. Patients
who are deceased will be included.
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7. Risks/Benefits
Potential Risks
The only foreseen risk for this study is loss of confidentiality.
Methods to Minimize Risks
To minimize loss of confidentiality, all identifying information will be removed prior to analysis. All
data will be kept in a secure, password-protected computer or locked cabinet in the research office.
Potential Benefits
There are no direct benefits for participating in this study. Future patients may benefit from
knowledge gained by this study by having a safer decision-making process for patients who are
considered for transfusions.
8. Administrative Procedures
Patient Confidentiality
Only authorized research staff will have access to data. Identifying information will be removed
prior to data analysis. All data will be kept in a password-protected computer or in a locked file
cabinet in the research office.
Data Management
Data will be stored on a password-protected computer or in a locked cabinet in the research
office. It will be transferred to Stanford University School of Medicine through a secure email and
will be stored confidentially as long as the CRIT collaboration exists. Data will be confidentially
destroyed one year following study completion.
9. References
1. Adams ES, et al. Computerized physician order entry with decision support decreases blood
transfusions in children. Pediatrics 2011;127:e112.
2. Lacroix J, et al. Transfusion strategies for patients in pediatric intensive care units. NEJM
2007; 356: 1609-1619.
10. Appendix
Include all additional, relative materials in the Appendix. This might include the following: Data
Collection Forms (DCFs), including abstract sheets, questionnaires, interview questions, phone
screenings, solicitation letters, surveys, etc. If you are using an existing instrument, you need to
document the validity of that instrument.
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