Evaluation of clinical coding data to determine causes of critical bleeding in patients receiving massive transfusion: a bi‐national, multicentre, cross‐sectional study
Previous local and international population‐based studies investigating clinical indications for red cell (RBC) transfusion have chiefly used International Classification of Diseases primary codes (Titlestad et al., 2001) or the diagnosis‐related groups (DRGs) (Syrjälä et al., 2001; Allden et al., 2011) as a source of clinical information to link with transfusion data. Good to excellent coding quality has been demonstrated for the principal procedure and principal diagnosis code (Campbell et al.2001; Quan et al., 2004; Henderson et al., 2006). However, as expected, these individual codes alone do not always reflect the indication for transfusion (Llewelyn et al., 2009). For example, studies examining indication for RBC transfusion using DRG data identified that patients with high transfusion requirements are often assigned the tracheostomy DRG (Whyte & Brook, 1998; Syrjälä et al., 2001). Recent studies using algorithms with combinations of diagnosis codes and the principal procedure code to determine reasons for transfusion are promising (Llewelyn et al., 2009; Wells et al., 2009). However, their ability to identify causes of critical bleeding in patients who receive MT is unknown, and previous transfusion validation studies have not been performed in ANZ.
Extending the methods used by Llewelyn et al (2009), we developed a novel algorithm based on diagnostic codes classified according to the Australian modification of the International Statistical Classification of Diseases and Related Health Problems, Tenth Revision (ICD‐10‐AM) and Australian Classification of Health Interventions (ACHI). The aim of this study was to examine the accuracy and reliability of this algorithm for determining causes of critical bleeding in patients who receive MT using expert chart review as the reference standard.