Identification of International Society on Thrombosis and Haemostasis major and clinically relevant non-major bleed events from electronic health records: a novel algorithm to enhance data utilisation from real-world sources.

algorithms electronic health records hemorrhage

Journal

International journal of population data science
ISSN: 2399-4908
Titre abrégé: Int J Popul Data Sci
Pays: Wales
ID NLM: 101737740

Informations de publication

Date de publication:
2023
Historique:
medline: 28 2 2024
pubmed: 28 2 2024
entrez: 28 2 2024
Statut: epublish

Résumé

In randomised controlled trials (RCTs), bleeding outcomes are often assessed using definitions provided by the International Society on Thrombosis and Haemostasis (ISTH). Information relating to bleeding events in real-world evidence (RWE) sources are not identified using these definitions. To assist with accurate comparisons between clinical trials and real-world studies, algorithms are required for the identification of ISTH-defined bleeding events in RWE sources. To present a novel algorithm to identify ISTH-defined major and clinically-relevant non-major (CRNM) bleeding events in a US Electronic Health Record (EHR) database. The ISTH definition for major bleeding was divided into three subclauses: fatal bleeds, critical organ bleeds and symptomatic bleeds associated with haemoglobin reductions. Data elements from EHRs required to identify patients fulfilling these subclauses (algorithm components) were defined according to International Classification of Diseases, 9th and 10th Revisions, Clinical Modification disease codes that describe key bleeding events. Other data providing context to bleeding severity included in the algorithm were: 'interaction type' (diagnosis in the inpatient or outpatient setting), 'position' (primary/discharge or secondary diagnosis), haemoglobin values from laboratory tests, blood transfusion codes and mortality data. In the final algorithm, the components were combined to align with the subclauses of ISTH definitions for major and CRNM bleeds. A matrix was proposed to guide identification of ISTH bleeding events in the EHR database. The matrix categorises bleeding events by combining data from algorithm components, including: diagnosis codes, 'interaction type', 'position', decreases in haemoglobin concentrations ( The novel algorithm proposed here identifies ISTH major and CRNM bleeding events that are commonly investigated in RCTs in a real-world EHR data source. This algorithm could facilitate comparison between the frequency of bleeding outcomes recorded in clinical trials and RWE. Validation of algorithm performance is in progress.

Identifiants

pubmed: 38414540
doi: 10.23889/ijpds.v8i1.2144
pii: 8:1:21
pmc: PMC10898215
doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Pagination

2144

Déclaration de conflit d'intérêts

Statement on conflicts of interest: All authors are employees of Bayer AG.

Auteurs

Alexander Hartenstein (A)

Medical Affairs and Pharmacovigilance, Bayer AG, Berlin, Germany.

Khaled Abdelgawwad (K)

Medical Affairs and Pharmacovigilance, Bayer AG, Berlin, Germany.

Frank Kleinjung (F)

Medical Affairs and Pharmacovigilance, Bayer AG, Berlin, Germany.

Stephen Privitera (S)

Medical Affairs and Pharmacovigilance, Bayer AG, Berlin, Germany.

Thomas Viethen (T)

Research and Development, Bayer AG, Wuppertal, Germany.

Tatsiana Vaitsiakhovich (T)

Medical Affairs and Pharmacovigilance, Bayer AG, Berlin, Germany.

Classifications MeSH