In our March 2011 What’s New in the Patient Safety World column “Downside of Transfusions in Surgery” we discussed the mounting evidence that transfusions during surgery are associated with increased morbidity and mortality. We also noted that some performance improvement programs were successful in reducing the frequency of transfusions and resulted in considerable cost savings.
A new study in children looked at the impact of clinical decision support tools on transfusions (Adams 2011). The investigators developed evidence-based rules to alert physicians if parameters were outside those recommended for transfusion when a physician ordered RBC transfusions. The rate of RBC transfusions dropped significantly both on the pediatric wards and the PICU after implementation of the CPOE rule compared to historical controls. The rule implemented was fairly simple: when an order for an RBC transfusion was placed, the system checked BP stability over the previous 6 hours and the most recent serum hemoglobin level (within the last 24 hours). If the patient had been normotensive for at least 6 hours and the Hgb was greater than 7, an alert popped up that notes the evidence against transfusion in this scenario. The clinician could still proceed with the order (it was not a hard stop, nor did it require an explanation for overriding the alert). The alert was associated with over a 50% decrease in transfusions on the acute care wards and a lesser decrease in the PICU. Estimated direct savings (on blood costs alone) were greater than $165,000 for this hospital. Indirect savings (eg. from avoiding the unwanted consequences of transfusions) undoubtedly raise the net savings.
Not all attempts to use clinical decision supports within CPOE have been successful in reducing unnecessary transfusions. At Brigham and Women’s Hospital (Scheurer 2010) studied appropriateness of transfusions 2 years after transfusion guidelines were instituted and clinical decision support tools implemented within CPOE. Over half the transfusions ordered were still considered inappropriate 2 years after implementation. It was found that decision support was bypassed altogether in two-thirds of transfusion orders (by indicating “active bleeding” even though chart review failed to substantiate that in almost half the cases) and that over two-thirds of the overrides indicated a superior had instructed the transfusion. The authors conclude that clinical decision support, by itself, is not likely to eliminate inappropriate transfusions and that other front-end interventions aimed at the decision maker are likely needed. The authors felt that this study showed that the decision to transfuse had “already been made” prior to the CPOE so that, in effect, the clinical decision support was rendered too late. In addition, they felt that CPOE targeted the intern or more junior resident in most cases and might be better directed toward the more senior clinicians making the decision to transfuse.
It is not clear why differences were seen in the two populations. In the pediatric study it was not mentioned who was doing the order entry (though this was also an academic hospital). They also specifically excluded some units (eg. hematology/oncology, cardiology, and NICU) and there was a difference in the case mix index between the historical control and study period.
Obviously there are multiple factors in play that are important in the potential success of clinical decision support tools to impact the appropriateness of transfusion.
Adams ES, Longhurst CA, Pageler N. Computerized Physician Order Entry With Decision Support Decreases Blood Transfusions in Children. Pediatrics 2011; 127(5): e1112 -e1119 (doi: 10.1542/peds.2010-3252)
Scheurer DB, Roy CL, McGurk S, Kachalia A. Effectiveness of Computerized Physician Order Entry with Decision Support to Reduce Inappropriate Blood Transfusions. JCOM 2010; 17(1): 17-26