Medical chart validation of inpatient diagnosis codes for transfusion‐related acute lung injury 2013‐2015. Issue 3 (27th January 2021) - Fuller, Candace C.; Nambudiri, Vinod E.; Spencer‐Smith, Caren; Curtis, Lesley H.; Shinde, Mayura; Cosgrove, Austin; Johnson, Margaret; Hickok, Jason; Honda, Stacey; Ismail, Heba; Kaufman, Richard Max; Kennedy, Adee; et al.
Abstract: Introduction: Transfusion‐related acute lung injury (TRALI), an adverse event occurring during or within 6 hours of transfusion, is a leading cause of transfusion‐associated fatalities reported to the US Food and Drug Administration. There is limited information on the validity of diagnosis codes for TRALI recorded in inpatient electronic medical records (EMRs). Study Designs and Methods: We conducted a validation study to establish the positive predictive value (PPV) of TRALI International Classification of Diseases, Ninth Revision, Clinical Modification (ICD‐9‐CM) diagnosis codes recorded within a large hospital system between 2013 and 2015. A physician with critical care expertise confirmed the TRALI diagnosis. As TRALI is likely underdiagnosed, we used the specific code (518.7), and codes for respiratory failure (518.82) in combination with transfusion reaction (999.80, 999.89, E934.7). Results: Among almost four million inpatient stays, we identified 208 potential TRALI cases with ICD‐9‐CM codes and reviewed 195 medical records; 68 (35%) met clinical definitions for TRALI (26 [38%] definitive, 15 [22%] possible, 27 [40%] delayed). Overall, the PPV for all inpatient TRALI diagnoses was 35% (95% confidence interval (CI), 28‐42). The PPV for the TRALI‐specific code was 44% (95% CI, 35‐54). Conclusion: We observed low PPVs (<50%) for TRALI ICD‐9‐CM diagnosis codes as validated by medical charts, which may relate to inconsistent code use, incomplete medical records, or other factors. Future studies using TRALI diagnosis codes in EMR databases may consider confirming diagnoses with medical records, assessing TRALI ICD, Tenth Revision, Clinical Modification codes, or exploring alternative ways for of accurately identifying TRALI in EMR databases. Key Points: In 169 hospitals, we identified 208 potential TRALI cases, reviewed 195 charts, and confirmed 68 (35%) cases met TRALI clinical definitions. As many potential TRALI cases identified with diagnosis codes did not meet clinical definitions, medical record confirmation may be prudent.