Strengthening spontaneous reporting-based signal detection during a pandemic with cases from electronic health records using a natural language processing tool.

ingentiumby ingentium

In Computing Literature.

Publication date: Jul 25, 2025

During the COVID-19 pandemic, vaccines were rapidly developed, but some potential adverse drug reactions (ADRs) were still undetected at the time of market authorization. The analysis of ADR reports received through the spontaneous reporting system (SRS) remains the cornerstone for safety signal detection. A limitation is that reporting ADRs is voluntary. In this study the added value of electronic health records (EHRs) was explored as an additional source to spontaneous reports, to strengthen safety signal detection concerning COVID-19 vaccines. The electronic health record adverse event (EHR-AE) search method was developed to enable targeted searches in EHRs using a natural language processing (NLP) tool with text-mining functionalities to identify additional potential cases. Searches were performed in EHRs of two Dutch hospitals concerning several established and non-established (potential) ADRs associated with COVID-19 vaccines. Identified cases were reported to Lareb and analyzed in addition to spontaneous reports for safety signal detection. Thirteen searches were conducted between January 1, 2023, and December 1, 2023, concerning different (potential) ADRs associated with COVID-19 vaccines. For 6 associations at least 1 case was identified, resulting in a total of 41 additional cases reported to Lareb. These cases contributed to the detection of two safety signals concerning COVID-19 vaccines. Two safety signals could have been detected approximately 18 and 2 months earlier, if the EHR-AE method had been implemented during the COVID-19 pandemic. The EHR-AE search method can strengthen and accelerate the signal detection process for potential ADRs associated with COVID-19 vaccination. Future studies should expand to more hospitals, aiming to further evaluate the added value of the method, including for which drug-ADR associations the EHR-AE search method is most beneficial.

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Concepts Keywords
December Electronic health records
Dutch Natural language processing
Mining Pharmacovigilance
Vaccines Safety signal detection
Spontaneous report system

Semantics

Type Source Name
disease MESH COVID-19 pandemic
disease MESH adverse drug reactions
disease IDO process
disease IDO protein
disease MESH Thrombosis
disease MESH Thrombocytopenia
disease MESH Syndrome
drug DRUGBANK Coenzyme M
drug DRUGBANK Methionine
drug DRUGBANK Aspartame
disease MESH Antiphospholipid syndrome
disease MESH Antisynthetase syndrome
disease MESH anemia
disease MESH Minimal change nephropathy
disease MESH Postural orthostatic tachycardia syndrome
disease MESH Sudden deafness
disease MESH Susac syndrome
disease MESH Capillary leak syndrome
disease MESH Guillain Barre syndrome
disease MESH Immune thrombocytopenic purpura
disease MESH Myelitis
disease MESH hemolytic anemia
disease MESH hearing loss
drug DRUGBANK Adenosine 5′-phosphosulfate
disease MESH autoimmune hemolytic anemia
drug DRUGBANK Hyaluronic acid
disease MESH sensorineural hearing loss
disease MESH tinnitus
disease IDO intervention
drug DRUGBANK D-Alanine
disease MESH melanoma
pathway KEGG Melanoma
disease MESH Cancers
disease MESH renal carcinoma

Original Article

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