Causality assessment of adverse events reported to the Vaccine Adverse Event Reporting System (VAERS)
ABSTRACT Adverse events following immunization (AEFI) reported to the national Vaccine Adverse Event Reporting System (VAERS) represent true causally related events, as well as events that are temporally, but not necessarily causally related to vaccine. OBJECTIVE: We sought to determine if the causal relationships between the vaccine and the AEFI reported to VAERS could be assessed through expert review. DESIGN: A stratified random sample of 100 VAERS reports received in 2004 contained 13 fatal cases, 19 cases with non-fatal disabilities, 39 other serious non-fatal cases and 29 non-serious cases. Experts knowledgeable about vaccines and clinical outcomes, reviewed each VAERS report and available medical records. MAIN OUTCOME MEASURES: Modified World Health Organization criteria were used to classify the causal relationship between vaccines and AEFI as definite, probable, possible, unlikely or unrelated. Five independent reviewers evaluated each report. If they did not reach a majority agreement on causality after initial review, the report was discussed on a telephone conference to achieve agreement. RESULTS: 108 AEFIs were identified in the selected 100 VAERS reports. After initial review majority agreement was achieved for 83% of the AEFI and 17% required further discussion. In the end, only 3 (3%) of the AEFI were classified as definitely causally related to vaccine received. Of the remaining AEFI 22 (20%) were classified as probably and 22 (20%) were classified as possibly related to vaccine received; a majority (53%) were classified as either unlikely or unrelated to a vaccine received. CONCLUSIONS: Using VAERS reports and additional documentation, causality could be assessed by expert review in the majority of VAERS reports. Assessment of VAERS reports identified that causality was thought to be probable or definite in less than one quarter of reports, and these were dominated by local reactions, allergic reactions, or symptoms known to be associated with the vaccine administered.
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ABSTRACT: Comprehensive surveillance of adverse events following immunization (AEFI) is required to detect potential serious adverse events that may not be identified in prelicensure vaccine trials. Surveillance systems have traditionally been passive, relying upon spontaneous reporting, but increasingly active surveillance and supplemental strategies are being incorporated into vaccine safety programs. These include active screening for targeted conditions of interest (e.g., hospitalization), monitoring of new data sources and real-time methodologies to detect changes in vaccine safety data in these sources. The role of improved causality assessment in AEFI surveillance is discussed, with its important role in determining whether a temporal association may have occurred by chance alone. Strong local vaccine safety networks are required to support national immunization programs, with recent progress in developing a framework for low- and middle-income countries. Global collaboration is increasingly required to address challenges in active AEFI surveillance, particularly for rare serious adverse events.Expert Review of Vaccines 12/2013; 13(2). DOI:10.1586/14760584.2014.866895 · 4.22 Impact Factor
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ABSTRACT: To evaluate epidemiological features of post vaccine acute disseminated encephalomyelitis (ADEM) by considering data from different pharmacovigilance surveillance systems. The Vaccine Adverse Event Reporting System (VAERS) database and the EudraVigilance post-authorisation module (EVPM) were searched to identify post vaccine ADEM cases. Epidemiological features including sex and related vaccines were analysed. We retrieved 205 and 236 ADEM cases from the EVPM and VAERS databases, respectively, of which 404 were considered for epidemiological analysis following verification and causality assessment. Half of the patients had less than 18 years and with a slight male predominance. The time interval from vaccination to ADEM onset was 2-30 days in 61% of the cases. Vaccine against seasonal flu and human papilloma virus vaccine were those most frequently associated with ADEM, accounting for almost 30% of the total cases. Mean number of reports per year between 2005 and 2012 in VAERS database was 40±21.7, decreasing after 2010 mainly because of a reduction of reports associated with human papilloma virus and Diphtheria, Pertussis, Tetanus, Polio and Haemophilus Influentiae type B vaccines. This study has a high epidemiological power as it is based on information on adverse events having occurred in over one billion people. It suffers from lack of rigorous case verification due to the weakness intrinsic to the surveillance databases used. At variance with previous reports on a prevalence of ADEM in childhood we demonstrate that it may occur at any age when post vaccination. This study also shows that the diminishing trend in post vaccine ADEM reporting related to Diphtheria, Pertussis, Tetanus, Polio and Haemophilus Influentiae type B and human papilloma virus vaccine groups is most likely due to a decline in vaccine coverage indicative of a reduced attention to this adverse drug reaction.PLoS ONE 12/2013; 8(10):e77766. DOI:10.1371/journal.pone.0077766 · 3.53 Impact Factor
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ABSTRACT: Transitioning between Electronic Medical Records (EMR) can result in patient data being stranded in legacy systems with subsequent failure to provide appropriate patient care. Manual chart abstraction is labor intensive, error-prone, and difficult to institute for immunizations on a systems level in a timely fashion. We sought to transfer immunization data from two of our health system's soon to be replaced EMRs to the future EMR using a single process instead of separate interfaces for each facility. We used scripted data entry, a process where a computer automates manual data entry, to insert data into the future EMR. Using the Center for Disease Control's CVX immunization codes we developed a bridge between immunization identifiers within our system's EMRs. We performed a two-step process evaluation of the data transfer using automated data comparison and manual chart review. We completed the data migration from two facilities in 16.8 hours with no data loss or corruption. We successfully populated the future EMR with 99.16% of our legacy immunization data - 500,906 records - just prior to our EMR transition date. A subset of immunizations, first recognized during clinical care, had not originally been extracted from the legacy systems. Once identified, this data - 1,695 records - was migrated using the same process with minimal additional effort. Scripted data entry for immunizations is more accurate than published estimates for manual data entry and we completed our data transfer in 1.2% of the total time we predicted for manual data entry. Performing this process before EMR conversion helped identify obstacles to data migration. Drawing upon this work, we will reuse this process for other healthcare facilities in our health system as they transition to the future EMR.Applied Clinical Informatics 01/2014; 5(1):284-98. DOI:10.4338/ACI-2013-11-RA-0096 · 0.39 Impact Factor