title: Relative impact of a patient blood management program on utilization of all three major blood components.
abstract: Although patient blood management (PBM) programs clearly reduce transfusion overuse, the relative impact on red blood cell (RBC), plasma, and platelet (PLT) utilization is unclear.
  
  
  
  A retrospective analysis of electronic records was conducted at a medium-sized academic hospital to assess blood utilization for all inpatients admitted during 1-year periods before (n = 20,531) and after (n = 19,477) PBM efforts began in September 2014. Transfusion guideline compliance and overall utilization were assessed for RBCs, plasma, and PLTs. The primary PBM efforts included education on evidence-based transfusion guidelines, decision support in the computerized provider order entry system, and distribution of provider-specific reports showing comparison to peers for guideline compliance. Cost avoidance was determined by two methods (acquisition cost and activity-based cost), and clinical outcomes were compared during the two periods.
  
  
  
  For RBCs, orders outside hospital guidelines decreased (from 23.9% to 17.1%, p < 0.001), and utilization decreased by 12% (p < 0.035). For plasma and PLTs, both orders outside guidelines and utilization changed minimally. Overall cost avoidance was $181,887/year by acquisition cost (and from $582,039 to $873,058/year by activity-based cost), 93% of which was attributed to reduction in RBC utilization. Length of stay, morbidity, and mortality were unchanged.
  
  
  
  Our findings demonstrate a greater opportunity for reducing RBC compared to plasma and PLT utilization. A properly implemented PBM program has potential to reduce unnecessary transfusions and their associated risk and costs, without compromising clinical outcomes.
authors.affiliation: Department of Medicine, The Johns Hopkins Medical Institutions, Baltimore, Maryland.
authors.forename: Rajiv N
authors.initials: RN
authors.lastname: Thakkar
authors.affiliation: Armstrong Institute of Patient Safety and Quality, The Johns Hopkins Medical Institutions, Baltimore, Maryland.
authors.forename: K H Ken
authors.initials: KH
authors.lastname: Lee
authors.affiliation: Department of Pathology (Transfusion Medicine), The Johns Hopkins Medical Institutions, Baltimore, Maryland.
authors.forename: Paul M
authors.initials: PM
authors.lastname: Ness
authors.affiliation: Department of Clinical Analytics, The Johns Hopkins Medical Institutions, Baltimore, Maryland.
authors.forename: Tyler L
authors.initials: TL
authors.lastname: Wintermeyer
authors.affiliation: Department of Anesthesiology/Critical Care Medicine, The Johns Hopkins Medical Institutions, Baltimore, Maryland.
authors.forename: Daniel J
authors.initials: DJ
authors.lastname: Johnson
authors.affiliation: Department of Pathology (Transfusion Medicine), The Johns Hopkins Medical Institutions, Baltimore, Maryland.
authors.forename: Emily
authors.initials: E
authors.lastname: Liu
authors.affiliation: Armstrong Institute of Patient Safety and Quality, The Johns Hopkins Medical Institutions, Baltimore, Maryland.
authors.forename: Anjuli
authors.initials: A
authors.lastname: Rajprasad
authors.affiliation: Department of Medicine, The Johns Hopkins Medical Institutions, Baltimore, Maryland.
authors.forename: Amy M
authors.initials: AM
authors.lastname: Knight
authors.affiliation: Armstrong Institute of Patient Safety and Quality, The Johns Hopkins Medical Institutions, Baltimore, Maryland.
authors.forename: Pat A
authors.initials: PA
authors.lastname: Wachter
authors.affiliation: Armstrong Institute of Patient Safety and Quality, The Johns Hopkins Medical Institutions, Baltimore, Maryland.
authors.forename: Renee
authors.initials: R
authors.lastname: Demski
authors.affiliation: Department of Anesthesiology/Critical Care Medicine, The Johns Hopkins Medical Institutions, Baltimore, Maryland. sfrank3@jhmi.edu.
authors.forename: Steven M
authors.initials: SM
authors.lastname: Frank
mesh_terms: D000328:Adult; D000368:Aged; D000465:Algorithms; D016913:Blood Component Transfusion / Q000191:economics / Q000379:methods* / Q000706:statistics & numerical data*; D016009:Chi-Square Distribution; D017707:Erythrocyte Transfusion / Q000191:economics / Q000379:methods / Q000706:statistics & numerical data; D005260:Female; D006801:Humans; D008297:Male; D008875:Middle Aged; D017713:Platelet Transfusion / Q000191:economics / Q000379:methods / Q000706:statistics & numerical data; D012189:Retrospective Studies; D012737:Sex Factors