| Hospital blood bank information systems accurately reflect patient transfusion: results of a validation study. | |
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MedLine Citation:
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PMID: 21077908 Owner: NLM Status: In-Data-Review |
Abstract/OtherAbstract:
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BACKGROUND: Hospital transfusion laboratories collect information regarding blood transfusion and some registries gather clinical outcomes data without transfusion information, providing an opportunity to integrate these two sources to explore effects of transfusion on clinical outcomes. However, the use of laboratory information system (LIS) data for this purpose has not been validated previously. STUDY DESIGN AND METHODS: Validation of LIS data against individual patient records was undertaken at two major centers. Data regarding all transfusion episodes were analyzed over seven 24-hour periods. RESULTS: Data regarding 596 units were captured including 399 red blood cell (RBC), 95 platelet (PLT), 72 plasma, and 30 cryoprecipitate units. They were issued to: inpatient 221 (37.1%), intensive care 109 (18.3%), outpatient 95 (15.9%), operating theater 45 (7.6%), emergency department 27 (4.5%), and unrecorded 99 (16.6%). All products recorded by LIS as issued were documented as transfused to intended patients. Median time from issue to transfusion initiation could be calculated for 535 (89.8%) components: RBCs 16 minutes (95% confidence interval [CI], 15-18 min; interquartile range [IQR], 7-30 min), PLTs 20 minutes (95% CI, 15-22 min; IQR, 10-37 min), fresh-frozen plasma 33 minutes (95% CI, 14-83 min; IQR, 11-134 min), and cryoprecipitate 3 minutes (95% CI, -10 to 42 min; IQR, -15 to 116 min). CONCLUSIONS: Across a range of blood component types and destinations comparison of LIS data with clinical records demonstrated concordance. The difference between LIS timing data and patient clinical records reflects expected time to transport, check, and prepare transfusion but does not affect the validity of linkage for most research purposes. Linkage of clinical registries with LIS data can therefore provide robust information regarding individual patient transfusion. This enables analysis of joint data sets to determine the impact of transfusion on clinical outcomes. |
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Authors:
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Zoe K McQuilten; Nikita Schembri; Mark N Polizzotto; Christine Akers; Melissa Wills; Merrole F Cole-Sinclair; Susan Whitehead; Erica M Wood; Louise E Phillips |
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Publication Detail:
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Type: Journal Article Date: 2010-11-15 |
Journal Detail:
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Title: Transfusion Volume: 51 ISSN: 1537-2995 ISO Abbreviation: Transfusion Publication Date: 2011 May |
Date Detail:
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Created Date: 2011-05-06 Completed Date: - Revised Date: - |
Medline Journal Info:
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Nlm Unique ID: 0417360 Medline TA: Transfusion Country: United States |
Other Details:
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Languages: eng Pagination: 943-8 Citation Subset: IM |
Copyright Information:
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© 2010 American Association of Blood Banks. |
Affiliation:
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From the Transfusion Medicine Services, Australian Red Cross Blood Service, Melbourne, Victoria; the Department of Epidemiology and Preventive Medicine, Monash University, Melbourne, Victoria; Diagnostic Haematology, Alfred Hospital, Melbourne, Victoria; and the Haematology Department, St Vincent's Hospital, Fitzroy, Victoria, Australia. |
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From MEDLINE®/PubMed®, a database of the U.S. National Library of Medicine
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