title: Optimizing preoperative blood ordering with data acquired from an anesthesia information management system.
abstract: BACKGROUND
  The maximum surgical blood order schedule (MSBOS) is used to determine preoperative blood orders for specific surgical procedures. Because the list was developed in the late 1970s, many new surgical procedures have been introduced and others improved upon, making the original MSBOS obsolete. The authors describe methods to create an updated, institution-specific MSBOS to guide preoperative blood ordering.
  
  
  METHODS
  Blood utilization data for 53,526 patients undergoing 1,632 different surgical procedures were gathered from an anesthesia information management system. A novel algorithm based on previously defined criteria was used to create an MSBOS for each surgical specialty. The economic implications were calculated based on the number of blood orders placed, but not indicated, according to the MSBOS.
  
  
  RESULTS
  Among 27,825 surgical cases that did not require preoperative blood orders as determined by the MSBOS, 9,099 (32.7%) had a type and screen, and 2,643 (9.5%) had a crossmatch ordered. Of 4,644 cases determined to require only a type and screen, 1,509 (32.5%) had a type and crossmatch ordered. By using the MSBOS to eliminate unnecessary blood orders, the authors calculated a potential reduction in hospital charges and actual costs of $211,448 and $43,135 per year, respectively, or $8.89 and $1.81 per surgical patient, respectively.
  
  
  CONCLUSIONS
  An institution-specific MSBOS can be created, using blood utilization data extracted from an anesthesia information management system along with our proposed algorithm. Using these methods to optimize the process of preoperative blood ordering can potentially improve operating room efficiency, increase patient safety, and decrease costs.
authors.affiliation: Department of Anesthesiology/Critical Care Medicine, The Johns Hopkins Medical Institutions, Baltimore, Maryland 21287, USA. sfrank3@jhmi.edu
authors.forename: Steven M
authors.initials: SM
authors.lastname: Frank
authors.forename: James A
authors.initials: JA
authors.lastname: Rothschild
authors.forename: Courtney G
authors.initials: CG
authors.lastname: Masear
authors.forename: Richard J
authors.initials: RJ
authors.lastname: Rivers
authors.forename: William T
authors.initials: WT
authors.lastname: Merritt
authors.forename: Will J
authors.initials: WJ
authors.lastname: Savage
authors.forename: Paul M
authors.initials: PM
authors.lastname: Ness
mesh_terms: D000465:Algorithms; D000704:Analysis of Variance; D000758:Anesthesia; D001788:Blood Grouping and Crossmatching; D001803:Blood Transfusion / Q000191:economics*; D006801:Humans; D009870:Operating Room Information Systems / Q000191:economics* / Q000458:organization & administration*; D057234:Preoperative Period; D013514:Surgical Procedures, Operative