Secondary Logo

Journal Logo

Intraoperative Transfusion Guidelines: Promoting Clinician Adherence in the Operating Room

Hagaman, Daniel*; Pilla, Michael A. MD; Ehrenfeld, Jesse M. MD, MPH

doi: 10.1213/ANE.0000000000003472
Editorials: Editorial
Free

From the *East Tennessee State University James H. Quillen College of Medicine, Johnson City, Tennessee

Department of Anesthesiology, Vanderbilt University Medical Center, Nashville, Tennessee.

Accepted for publication April 19, 2018.

Funding: None.

The authors declare no conflicts of interest.

Reprints will not be available from the authors.

Address correspondence to Jesse M. Ehrenfeld, MD, MPH, Department of Anesthesiology, Vanderbilt University Medical Center, 1301 Medical Center Dr, Suite TVC 4648, Nashville, TN 37232. Address e-mail to jesse.ehrenfeld@vandebilt.edu.

Current literature has yet to evaluate the implementation of transfusion guidelines or the use of a decision support tool on intraoperative transfusion behavior. In the accompanying article, Picton et al1 analyze the effect of an intraoperative transfusion guideline on clinical behavior. The authors found that the implementation of a guideline was associated with both an increase in intraoperative hematocrit assessment and an increased use of restrictive transfusion practices. The use of a complementary software decision support tool had no increased effect on clinical practice. This editorial will discuss pretransfusion hematocrit assessment, transfusion guidelines, and clinical decision support tools as they relate to this study.

In the United States, more than 20 million blood components are transfused each year. Evidence has accumulated in recent decades describing both infectious and noninfectious risks associated with blood transfusions, leading many to advocate for hemovigilance strategies and best-practice guidelines with regard to blood product utilization. As a result, efforts have been made to standardize transfusion practices through the use of transfusion guidelines to minimize both morbidity and mortality and reduce the unnecessary use of a limited biological resource.

Beginning with the study of Hébert et al2 and continuing to present, the optimal transfusion threshold has been debated. Multiple studies have aimed to develop a definite hemoglobin or hematocrit target to incorporate into an evidence-based transfusion guideline. Many of the published blood transfusion guidelines and randomized control trials have focused on the distinction between liberal and restrictive transfusion thresholds in relation to patients’ pretransfusion hemoglobin or hematocrit. Liberal transfusion thresholds are generally considered 9–10 g/dL, while restrictive thresholds are considered 7–8 g/dL.3,4 In 2016, the AABB recommended that red blood cell (RBC) transfusion is not indicated until the hemoglobin is ≤7 g/dL in hospitalized hemodynamically stable adult patients.5 This recommendation reflects a push toward restrictive transfusion practices, such as the one incorporated into the study by Picton et al.1

A metanalysis conducted in 2014 suggests that restricting blood transfusion improves overall outcomes.6 However, concern is generated when restrictive transfusion guidelines are applied to specific populations. A 2016 Cochrane Database systematic review found no evidence that a restrictive transfusion strategy increased morbidity or mortality, although it did not comment on the transfusion safety in specific clinical subgroups.3 Another study found that mortality and morbidity improved with restrictive transfusion practices in patients with severe acute upper gastrointestinal bleeding.7 A 2015 study by de Almeida et al8 found that restrictive transfusion practices showed association with worse clinical outcomes in surgical oncology patients when compared to liberal transfusion practices. A suggestion of similar findings emerged from an analysis of patients undergoing cardiac surgery.9 However, it should be noted that mortality was a secondary outcome in what was an overall negative study that was not appropriately adjusted for multiple comparisons and had a P value of .045. While results reported by Picton et al1 show no change in 30-day mortality, myocardial infarction, or renal injury after the adoption of a restrictive transfusion practice, one must be careful not to apply these findings outside of the studied population.1 To account for these specific clinical subgroups, the AABB recommends that a threshold of 8 g/dL be used for those undergoing orthopedic and cardiac surgery, including those with preexisting cardiovascular disease.5 Clinicians must be cognizant of individual clinical subgroups when applying transfusion guidelines.

Limitations surrounding the use of a transfusion threshold may include a multitude of factors, such as failure to evaluate hemoglobin or hematocrit before the transfusion due to insufficient time between assessment and transfusion or the inability to rapidly access venous sites. Active bleeding and hypovolemia might appropriately preempt an intraoperative transfusion trigger. Nonetheless, when hemoglobin or hematocrit is unchecked before a transfusion, there is a risk that the transfusion may be clinically unnecessary. One study found that 9.2% of intraoperative transfusions failed to meet a physiological indication (mean arterial pressure or heart rate) or a hemoglobin threshold <10 g/dL10 and advocated for a decrease in extraneous intraoperative transfusions. The current article by Picton et al1 directly addresses this limitation by evaluating an educational intervention aimed at increasing the clinicians’ adherence to measure pretransfusion hemoglobin. The study shows an increase in compliance of pretransfusion hemoglobin assessment after implementation of their transfusion guideline.1

Electronic health systems increasingly utilize clinical decision support tools, including within the perioperative environment.11 This technology can be applied in the hopes of improving blood transfusion practices, with intraoperative decision support already proving effective in areas such as deep venous thrombosis and pulmonary embolus prophylaxis, among many others.12 Various studies reveal that implementation of a clinical decision support tool effectively reduces multiunit transfusions in a nonoperative setting,13,14 while use of these tools in the operative arena may have similar benefits. Razavi et al15 showed that reduced RBC transfusions after implementation of a novel clinical decision support tool in patients undergoing cardiothoracic surgery decreased RBC transfusions. In this study, incorporation of the clinical decision support tool led to lower pretransfusion hemoglobin levels, although the authors did not report overall changes in units transfused per patient—a measure of true blood utilization. Picton et al1 did not find that the use of a software tool influenced clinical behavior, likely due to its optional status and the timing of its rollout, but posits that a more intrusive alert system may have been more effective. Nevertheless, this area holds promise for ongoing research. Future analysis should be conducted to evaluate whether stratification by training status changes adoption rates. The hypothesis predicts that decision support tools are used more by trainees, who are more likely to adopt a new clinical behavior. Past literature has shown that the rate of adoption of clinical decision support tools is highest among entry-level trainees and lowest among attending physicians.16–19

Back to Top | Article Outline

DISCLOSURES

Name: Daniel Hagaman.

Contribution: This author helped draft the initial manuscript.

Name: Michael A. Pilla, MD.

Contribution: This author helped edit and critically review the manuscript.

Name: Jesse M. Ehrenfeld, MD, MPH.

Contribution: This author helped edit and critically review the manuscript.

This manuscript was handled by: Marisa B. Marques, MD.

Back to Top | Article Outline

REFERENCES

1. Picton P, Starr J, Kheterpal S, et al. Promoting a restrictive intraoperative transfusion strategy: the influence of a transfusion guideline and a novel software tool. Anesth Analg. 2018;127:744–752.
2. Hébert PC, Wells G, Blajchman MA, et al. A multicenter, randomized, controlled clinical trial of transfusion requirements in critical care. Transfusion Requirements in Critical Care Investigators, Canadian Critical Care Trials Group. N Engl J Med. 1999;340:409–417.
3. Carson JL, Stanworth SJ, Roubinian N, et al. Transfusion thresholds and other strategies for guiding allogeneic red blood cell transfusion. Cochrane Database Syst Rev. 2016;10:CD002042.
4. Franchini M, Marano G, Mengoli C, et al. Red blood cell transfusion policy: a critical literature review. Blood Transfus. 2017;15:307–317.
5. Carson JL, Guyatt G, Heddle NM, et al. Clinical practice guidelines from the AABB: red blood cell transfusion thresholds and storage. JAMA. 2016;316:2025–2035.
6. Salpeter SR, Buckley JS, Chatterjee S. Impact of more restrictive blood transfusion strategies on clinical outcomes: a meta-analysis and systematic review. Am J Med. 2014;127:124–131.e3.
7. Villanueva C, Colomo A, Bosch A, et al. Transfusion strategies for acute upper gastrointestinal bleeding. N Engl J Med. 2013;368:11–21.
8. de Almeida JP, Vincent JL, Galas FR, et al. Transfusion requirements in surgical oncology patients: a prospective, randomized controlled trial. Anesthesiology. 2015;122:29–38.
9. Murphy GJ, Pike K, Rogers CA, et al.; TITRe2 Investigators. Liberal or restrictive transfusion after cardiac surgery. N Engl J Med. 2015;372:997–1008.
10. Cerullo M, Gani F, Chen SY, et al. Physiologic correlates of intraoperative blood transfusion among patients undergoing major gastrointestinal operations. Surgery. 2017;162:211–222.
11. Ehrenfeld JM, Wanderer JP, Terekhov M, Rothman BS, Sandberg WS. A perioperative systems design to improve intraoperative glucose monitoring is associated with a reduction in surgical site infections in a diabetic patient population. Anesthesiology. 2017;126:431–440.
12. Agharezaei Z, Bahaadinbeigy K, Tofighi S, Agharezaei L, Nemati A. Attitude of Iranian physicians and nurses toward a clinical decision support system for pulmonary embolism and deep vein thrombosis. Comput Methods Programs Biomed. 2014;115:95–101.
13. Jenkins I, Doucet JJ, Clay B, et al. Transfusing wisely: clinical decision support improves blood transfusion practices. Jt Comm J Qual Patient Saf. 2017;43:389–395.
14. Kassakian SZ, Yackel TR, Deloughery T, Dorr DA. Clinical decision support reduces overuse of red blood cell transfusions: interrupted time series analysis. Am J Med. 2016;129:636.e13–636.e20.
15. Razavi SA, Carter AB, Puskas JD, Gregg SR, Aziz IF, Buchman TG. Reduced red blood cell transfusion in cardiothoracic surgery after implementation of a novel clinical decision support tool. J Am Coll Surg. 2014;219:1028–1036.
16. McCullagh LJ, Sofianou A, Kannry J, Mann DM, McGinn TG. User centered clinical decision support tools: adoption across clinician training level. Appl Clin Inform. 2014;5:1015–1025.
17. Sheibani R, Sheibani M, Heidari-Bakavoli A, Abu-Hanna A, Eslami S. The effect of a clinical decision support system on improving adherence to guideline in the treatment of atrial fibrillation: an interrupted time series study. J Med Syst. 2017;42:26.
18. Sharma S, Martijn Bos J, Tarrell RF, et al. Providers’ response to clinical decision support for QT prolonging drugs. J Med Syst. 2017;41:161.
19. Baypinar F, Kingma HJ, van der Hoeven RTM, Becker ML. Physicians’ compliance with a clinical decision support system alerting during the prescribing process. J Med Syst. 2017;41:96.
Copyright © 2018 International Anesthesia Research Society