Evidence-based red cell transfusion in the critically ill: Quality improvement using computerized physician order entry

Rimki Rana, Bekele Afessa, Mark T. Keegan, Francis X. Whalen, Gregory A. Nuttall, Laura K. Evenson, Steve G. Peters, Jeffrey L. Winters, Rolf D. Hubmayr, S. Breanndan Moore, Ognjen Gajic

Research output: Contribution to journalArticle

76 Citations (Scopus)

Abstract

OBJECTIVE: 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. DESIGN: We compared processes of care and outcomes during the two 3-month periods before and after the introduction of a multidisciplinary quality improvement intervention. SETTING: Multidisciplinary intensive care units-medical, surgical, and mixed-in a tertiary academic center. PATIENTS: Consecutive critically ill patients with anemia (hemoglobin of <10 g/dL). INTERVENTION: Using the computerized provider order entry, we developed an evidence-based decision algorithm for red cell transfusion in adult intensive care units. MEASUREMENTS AND MAIN RESULTS: 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). CONCLUSIONS: The implementation of an institutional protocol and decision support through a computerized provider order entry effectively decreased inappropriate red cell transfusions.

Original languageEnglish (US)
Pages (from-to)1892-1897
Number of pages6
JournalCritical Care Medicine
Volume34
Issue number7
DOIs
StatePublished - Jul 2006

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Medical Order Entry Systems
Quality Improvement
Critical Illness
Intensive Care Units
Hospital Mortality
Odds Ratio
Confidence Intervals
Evidence-Based Practice
Anemia
Hemoglobins
Multivariate Analysis
Cell Count
Demography
Outcome Assessment (Health Care)

ASJC Scopus subject areas

  • Critical Care and Intensive Care Medicine

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Evidence-based red cell transfusion in the critically ill : Quality improvement using computerized physician order entry. / Rana, Rimki; Afessa, Bekele; Keegan, Mark T.; Whalen, Francis X.; Nuttall, Gregory A.; Evenson, Laura K.; Peters, Steve G.; Winters, Jeffrey L.; Hubmayr, Rolf D.; Moore, S. Breanndan; Gajic, Ognjen.

In: Critical Care Medicine, Vol. 34, No. 7, 07.2006, p. 1892-1897.

Research output: Contribution to journalArticle

Rana, R, Afessa, B, Keegan, MT, Whalen, FX, Nuttall, GA, Evenson, LK, Peters, SG, Winters, JL, Hubmayr, RD, Moore, SB & Gajic, O 2006, 'Evidence-based red cell transfusion in the critically ill: Quality improvement using computerized physician order entry', Critical Care Medicine, vol. 34, no. 7, pp. 1892-1897. https://doi.org/10.1097/01.CCM.0000220766.13623.FE
Rana, Rimki ; Afessa, Bekele ; Keegan, Mark T. ; Whalen, Francis X. ; Nuttall, Gregory A. ; Evenson, Laura K. ; Peters, Steve G. ; Winters, Jeffrey L. ; Hubmayr, Rolf D. ; Moore, S. Breanndan ; Gajic, Ognjen. / Evidence-based red cell transfusion in the critically ill : Quality improvement using computerized physician order entry. In: Critical Care Medicine. 2006 ; Vol. 34, No. 7. pp. 1892-1897.
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abstract = "OBJECTIVE: 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. DESIGN: We compared processes of care and outcomes during the two 3-month periods before and after the introduction of a multidisciplinary quality improvement intervention. SETTING: Multidisciplinary intensive care units-medical, surgical, and mixed-in a tertiary academic center. PATIENTS: Consecutive critically ill patients with anemia (hemoglobin of <10 g/dL). INTERVENTION: Using the computerized provider order entry, we developed an evidence-based decision algorithm for red cell transfusion in adult intensive care units. MEASUREMENTS AND MAIN RESULTS: 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). CONCLUSIONS: 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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AU - Rana, Rimki

AU - Afessa, Bekele

AU - Keegan, Mark T.

AU - Whalen, Francis X.

AU - Nuttall, Gregory A.

AU - Evenson, Laura K.

AU - Peters, Steve G.

AU - Winters, Jeffrey L.

AU - Hubmayr, Rolf D.

AU - Moore, S. Breanndan

AU - Gajic, Ognjen

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N2 - OBJECTIVE: 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. DESIGN: We compared processes of care and outcomes during the two 3-month periods before and after the introduction of a multidisciplinary quality improvement intervention. SETTING: Multidisciplinary intensive care units-medical, surgical, and mixed-in a tertiary academic center. PATIENTS: Consecutive critically ill patients with anemia (hemoglobin of <10 g/dL). INTERVENTION: Using the computerized provider order entry, we developed an evidence-based decision algorithm for red cell transfusion in adult intensive care units. MEASUREMENTS AND MAIN RESULTS: 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). CONCLUSIONS: 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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