Evidence-based red cell transfusion in the critically ill: Quality improvement using computerized physician order entry
ABSTRACT The implementation of evidence-based practice poses a significant challenge in the intensive care unit. In this quality improvement intervention we assessed the effect of an institutional protocol and computerized decision support for red cell transfusion in the critically ill.
We compared processes of care and outcomes during the two 3-month periods before and after the introduction of a multidisciplinary quality improvement intervention.
Multidisciplinary intensive care units--medical, surgical, and mixed--in a tertiary academic center.
Consecutive critically ill patients with anemia (hemoglobin of <10 g/dL).
Using the computerized provider order entry, we developed an evidence-based decision algorithm for red cell transfusion in adult intensive care units.
We collected information on demographics, diagnosis, severity of illness, transfusion complications, and laboratory values. The main outcome measures were number of transfusions, proportion of patients who were transfused outside evidence-based indications, transfusion complications, and adjusted hospital mortality. The mean number of red cell transfusions per intensive care unit admission decreased from 1.08 +/- 2.3 units before to 0.86 +/- 2.3 units after the protocol (p<.001). We observed a marked decrease in the percentage of patients receiving inappropriate transfusions (17.7% vs. 4.5%, p< .001). The rate of transfusion complications was also lower in the period after the protocol (6.1% vs. 2.7%, p = .015). In the multivariate analysis, protocol introduction was associated with decreased likelihood of red cell transfusion (odds ratio, 0.43; 95% confidence interval, 0.30 to 0.62). Adjusted hospital mortality did not differ before and after protocol implementation (odds ratio, 1.12; 95% confidence interval, 0.69 to 1.8).
The implementation of an institutional protocol and decision support through a computerized provider order entry effectively decreased inappropriate red cell transfusions.
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ABSTRACT: To explore the effect of various adverse hospital events on short- and long-term outcomes in a cohort of acutely ill hospitalized patients. In a secondary analysis of a retrospective cohort of acutely ill hospitalized patients with sepsis, shock, or pneumonia or undergoing high-risk surgery who were at risk for or had developed acute respiratory distress syndrome between 2001 and 2010, the effects of potentially preventable hospital exposures and adverse events (AEs) on in-hospital and intensive care unit (ICU) mortality, length of stay, and long-term survival were analyzed. Adverse effects chosen for inclusion were inadequate empiric antimicrobial coverage, hospital-acquired aspiration, medical or surgical misadventure, inappropriate blood product transfusion, and injurious tidal volume while on mechanical ventilation. In 828 patients analyzed, the distribution of 0, 1, 2, and 3 or more cumulative AEs was 521 (63%), 126 (15%), 135 (16%), and 46 (6%) patients, respectively. The adjusted odds ratios (95% CI) for in-hospital mortality in patients who had 1, 2, and 3 or more AEs were 0.9 (0.5-1.7), 0.9 (0.5-1.6), and 1.4 (0.6-3.3), respectively. One AE increased the length of stay, difference between means (95% CI), in the hospital by 8.7 (3.8-13.7) days and in the ICU by 2.4 (0.6-4.2) days. Potentially preventable hospital exposure to AEs is associated with prolonged ICU and hospital lengths of stay. Implementation of effective patient safety interventions is of utmost priority in acute care hospitals. Copyright © 2015 Mayo Foundation for Medical Education and Research. Published by Elsevier Inc. All rights reserved.Mayo Clinic Proceedings 01/2015; 90(3). DOI:10.1016/j.mayocp.2014.12.015 · 5.81 Impact Factor
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ABSTRACT: National blood use patterns in sub-Saharan Africa are poorly described. Although malaria and maternal hemorrhage remain important drivers of blood demand across Africa, economic growth and changes in malaria, HIV/AIDS, and noncommunicable disease epidemiology may contribute to changes in blood demand. We evaluated indications for blood use in Namibia, a country in southern Africa, using a nationally representative sample and discuss implications for the region. Clinical and demographic data related to the issuance of blood component units in Namibia were reviewed for a 4-year period (August 1, 2007-July 31, 2011). Variables included blood component type, recipient age and sex, and diagnosis. Diagnoses reported by clinicians were reclassified into International Statistical Classification of Diseases, 10th Revision categories. Multiple imputation methods were used to complete a data set missing age, sex or diagnosis data. Descriptive analyses were conducted to describe indications for transfusions and use of red blood cells (RBCs), platelets, and plasma. A total of 39 313 records accounting for 91 207 blood component units were analyzed. The median age of Namibian transfusion recipients was 45 years (SD, ±19). A total of 78 660 RBC units were issued in Namibia during the study period. Red blood cells transfused for "unspecified anemia" accounted for the single largest category of blood issued (24 798 units). Of the overall total, 38.9% were for diseases of the blood and blood-forming organs (D50-D89). Infectious disease (A00-B99), pregnancy (O00-O99), and gastrointestinal (K20-K93) accounted for 14.8%, 11.1%, and 6.1% of RBC units issued, respectively. Although a specific diagnosis of malaria accounted for only 2.7% of pediatric transfusions, an unknown number of additional transfusions for malaria may have been categorized by requesting physicians as unspecified anemia and counted under diseases of blood forming organs. During the study period, 9751 units of fresh-frozen plasma were issued. Nearly one-quarter of these units (23.1%) were issued for gastrointestinal (K20-K93) diagnoses. Malignant neoplasms (C00-C97) accounted for 38.1% of 2978 platelet units issued. Blood use in Namibia reflects changes in the health care system due to economic development, improvement in HIV/AIDS and malaria epidemiology, high rates of health care facility-based childbirth, and access to noncommunicable disease treatment. However, better documentation of the indications for transfusion is needed to confirm these observations. Changing patterns of health care will result in changing demands for blood components. Improved methods to evaluate blood use patterns in sub-Saharan Africa may help set realistic national blood collection goals. Published by Elsevier Inc.Transfusion Medicine Reviews 11/2014; 29(1). DOI:10.1016/j.tmrv.2014.11.003 · 4.54 Impact Factor
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ABSTRACT: Decision support systems (DSSs) provide clinicians with tailored treatment recommendations by combining individual patient information and local guidelines. The objective of this systematic review was to assess the effects of electronic DSS on blood product ordering practices. Eligible studies were identified from searches of MEDLINE, Embase, CINAHL, The Cochrane Library, PubMed, and the Transfusion Evidence Library from January 2000 to April 2014. Of these, 23 articles were eligible, resulting in the inclusion of 20 independent studies in this systematic review. There was a significant variation in study population, the type of DSS used, and outcome reporting. All but one study used a before-after design without any element of randomization. Overall, there is good evidence that implementation of a DSS improves red blood cell usage. The effect of a DSS on plasma, platelets, and cryoprecipitate usage is less clear probably because fewer studies have been conducted focusing on these products. In addition, the introduction of a DSS resulted in cost savings in the 7 studies that reported financial outcomes. Patient outcomes were generally not studied in detail, and there were few data on the sustainability of the effect of DSS. Further data are needed to assess the effect of a DSS on blood products other than red blood cell, and future studies should standardize reporting of outcomes. Copyright © 2014 Elsevier Inc. All rights reserved.Transfusion Medicine Reviews 11/2014; 29(1). DOI:10.1016/j.tmrv.2014.10.002 · 4.54 Impact Factor