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Analyzing real world data of blood transfusion adverse events: Opportunities and challenges.
Jhaveri, Perrin; Bozkurt, Selen; Moyal, Axel; Belov, Artur; Anderson, Steven; Shan, Hua; Whitaker, Barbee; Hernandez-Boussard, Tina.
Afiliação
  • Jhaveri P; School of Medicine, Stanford University, Stanford, California, USA.
  • Bozkurt S; Stanford Blood Center, Stanford, California, USA.
  • Moyal A; Department of Medicine (Biomedical Informatics), Stanford University School of Medicine, Stanford, California, USA.
  • Belov A; Department of Medicine (Biomedical Informatics), Stanford University School of Medicine, Stanford, California, USA.
  • Anderson S; Center for Biologics Evaluation and Research, Office of Biostatistics and Epidemiology, US FDA, Silver Spring, Maryland, USA.
  • Shan H; Center for Biologics Evaluation and Research, Office of Biostatistics and Epidemiology, US FDA, Silver Spring, Maryland, USA.
  • Whitaker B; School of Medicine, Stanford University, Stanford, California, USA.
  • Hernandez-Boussard T; Stanford Blood Center, Stanford, California, USA.
Transfusion ; 62(5): 1019-1026, 2022 05.
Article em En | MEDLINE | ID: mdl-35437749
ABSTRACT

BACKGROUND:

Blood transfusions are a vital component of modern healthcare, yet adverse reactions to blood product transfusions can cause morbidity, and rarely result in mortality. Therefore, accurate reporting of transfusion related adverse events (TRAEs) is paramount to improved transfusion practice. This study aims to investigate real-world data (RWD) on TRAEs by evaluating differences between ICD 9/10-based electronic health records (EHR) and blood bank-specific reporting. STUDY DESIGN AND

METHODS:

TRAE data were retrospectively collected from a blood bank-specific database between Jan 2015 and June 2019 as the reference data source and compared it to ICD 9/10 diagnostic codes corresponding to various TRAEs. Seven reactions that have corresponding ICD 9/10 diagnostic codes were evaluated Transfusion related circulatory overload (TACO), transfusion related acute lung injury (TRALI), febrile non-hemolytic reaction (FNHTR), transfusion-related anaphylactic reaction (TRA), acute hemolytic transfusion reaction (AHTR), delayed hemolytic transfusion reaction (DHTR), and delayed serologic reaction (DSTR). These accounted for 33% of the TRAEs at an academic institution during the study period.

RESULTS:

Among 18637 adult blood transfusion recipients, there were 229 unique patients with 263 TRAE related ICD codes in the EHR, while there were 191 unique patients with 287 TRAEs identified in the blood bank database. None of the categories of reaction we investigated had perfect alignment between ICD 9/10 codes and blood bank specific diagnoses.

DISCUSSION:

Multiple systemic challenges were identified that hinder effective reporting of TRAEs. Identifying factors causing inconsistent reporting between blood banks and EHRs is paramount to developing effective workability between these electronic systems, as well as across clinical and laboratory teams.
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Reação Transfusional / Lesão Pulmonar Aguda Relacionada à Transfusão Tipo de estudo: Diagnostic_studies / Etiology_studies / Observational_studies / Prognostic_studies Limite: Adult / Humans Idioma: En Revista: Transfusion Ano de publicação: 2022 Tipo de documento: Article País de afiliação: Estados Unidos

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Reação Transfusional / Lesão Pulmonar Aguda Relacionada à Transfusão Tipo de estudo: Diagnostic_studies / Etiology_studies / Observational_studies / Prognostic_studies Limite: Adult / Humans Idioma: En Revista: Transfusion Ano de publicação: 2022 Tipo de documento: Article País de afiliação: Estados Unidos