In the past 2-3 years we’ve done multiple columns (see list at the end of this column) highlighting
some of the detrimental effects related to red blood cell transfusions and the
trend toward more restrictive transfusion strategies in many different
scenarios. Unnecessary transfusions
have not only clinical untoward effects but add to health care costs.
Our focus, however,
has always been on transfusions themselves. But even when actual transfusions
are not given there may be costs and other potential consequences resulting
from the blood ordering process. Ordering type-and-screen or
type-and-crossmatch before surgical procedures creates a lot of work for blood
banks and may result in delay in usage of those blood products for other
patients or even wastage of blood products. Moreover, the workload burden on
the blood bank may lead to delays in starting surgical cases or delays in
responding to other emergencies.
It turns out that
such blood ordering is part science and part guesswork and part habit. In fact,
back in the 1970’s there was a Maximum Surgical Blood Order Schedule (MSBOS)
developed that estimated how many units of blood should be ordered for each
type of surgical procedure. But a lot has changed since the 1970’s! The number
of different surgical procedures being performed has increased substantially
and advances in surgical techniques and equipment have changed the likelihood
that blood will be needed.
So researchers at
Johns Hopkins (Frank
2013) analyzed data from their Anesthesia Information Management System
(AIMS) on over 50,000 patients and over 1600 different surgical procedures at
their institution for both blood ordering practices and actual transfusions.
Not surprisingly they found that many patients not needing transfusions had
either type-and-screen (32.7%) or type-and-crossmatch (9.5%) done. Also, about
a third of patients who only needed type-and-screen had a type-and-crossmatch
ordered. They calculated that a potential cost savings of $43,000 per year
could be achieved at their institution by a new MSBOS which they developed.
They used variables from the 1970’s MSBOS and data from their AIMS to develop
an algorithm that could be used to improve blood ordering prior to surgery.
They were able to group 135 categories of surgical procedures and assign them
to one of 5 blood order groups.
Their algorithm
could be used by other healthcare organizations to develop
institution-specific, procedure-specific, and maybe even surgeon-specific blood
ordering recommendations.
The next step will be to apply their MSBOS algorithm prospectively to see how it works in actual practice and to identify any unintended consequences of its use. But this is a very timely contribution to our evolving systems for managing blood products. Even if you don’t apply the algorithm prospectively in your organization, just doing the exercise on data from your own AIMS should be a worthwhile exercise that may identify practice patterns that might be improved. But the algorithm has the potential to improve efficiency in both the blood bank and the OR while reducing costs and even improving patient safety.
Also, in addition to those studies mentioned in our previous columns on the move toward more restrictive transfusion policies, there have been a few new papers worth reading. One study (Ferraris 2013) found an association between intraoperative blood transfusions and development of the systemic inflammatory response syndrome (SIRS). Mortality for patients who developed postoperative SIRS had mortality rates 13-fold higher than those who did not develop SIRS. A recent issue of The Lancet also had a series of excellent articles on blood product management and alternatives (Goodnough 2013, Spahn 2013, Williamson 2013).
Prior columns on potential detrimental effects related to red blood cell transfusions:
· March 2011 “Downside of Transfusions in Surgery”
·
February 2012 “More
Bad News on Transfusions”
·
January 2012 “Need
for New Transfusion Criteria?”
·
April 2012 “New
Transfusion Guidelines from the AABB”
·
February 2013 “More
Evidence Favoring Restriction of Transfusions”
References:
Frank SM, Rothschild JA, Masear CG, et al. Optimizing Preoperative Blood Ordering with Data Acquired from an Anesthesia Information Management System. Anesthesiology 2013; 118(6): 1286-1297, June 2013
Ferraris VA, Ballert EQ, Mahan A. The relationship between intraoperative blood transfusion and postoperative systemic inflammatory response syndrome. The American Journal of Surgery 2013; 205(4): 457-465
http://www.americanjournalofsurgery.com/article/S0002-9610%2813%2900055-X/abstract
Goodnough LT, Levy JH, Murphy MF. Concepts of blood transfusion in adults. The Lancet 2013; 381(9880): 1845-1854, 25 May 2013
http://www.thelancet.com/journals/lancet/article/PIIS0140-6736%2813%2960650-9/abstract
Spahn DR, Goodnough LT. Alternatives to blood transfusion. The Lancet 2013; 381: (9880); 1855-1865, 25 May 2013
http://www.thelancet.com/journals/lancet/article/PIIS0140-6736%2813%2960808-9/abstract
Williamson LM, Devine D. Challenges in the management of the blood supply. The Lancet 2013; 381(9880): 1866-1875, 25 May 2013
http://www.thelancet.com/journals/lancet/article/PIIS0140-6736%2813%2960631-5/abstract
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