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Advanced Clinical Decision Support for Vaccine Adverse Event Detection and Reporting
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June 09 2015
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Source: Clin Infect Dis. 61(6):864-870
Details:
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Alternative Title:Clin Infect Dis
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Personal Author:
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Description:Importance:
Reporting of adverse events (AEs) following vaccination can help identify rare or unexpected complications of immunizations and aid in characterizing potential vaccine safety signals.
Objective:
To create an electronic health record (EHR) module to assist clinicians with AE detection and reporting.
Design:
We developed an open-source, generalizable clinical decision system called Electronic Support for Public Health–Vaccine Adverse Event Reporting System (ESP-VAERS) to facilitate automated AE detection and reporting using EHRs. ESP-VAERS prospectively monitors patients’ electronic records for new diagnoses, changes in laboratory values and new allergies for up to 6 weeks following vaccinations. When suggestive events are found, ESP-VAERS sends a secure electronic message to the patient’s clinician. The clinician is invited to affirm or refute the event, add comments, and if they wish, submit an automated, pre-populated electronic case report to the national VAERS. High probability AEs following vaccination are reported automatically even if the clinician does not respond.
Setting:
We implemented ESP-VAERS in December 2012 at the MetroHealth System, an inpatient and outpatient integrated healthcare system in Ohio with nearly 1 million encounters per year. We queried the VAERS database to determine MetroHealth’s baseline reporting rates from 1/2009–3/2012 and then assessed changes in reporting rates with ESP-VAERS.
Participants:
All patients receiving vaccinations between 12/04/2012 and 08/03/2013 and their clinicians.
Exposure:
ESP-VAERS
Main outcome and measure:
The odds ratio of a VAERS report submission during the intervention period compared to the comparable pre-intervention period.
Results:
In the 8 months following implementation, 91,622 vaccinations were given. ESP-VAERS sent 1,385 messages to responsible clinicians describing potential AEs (15 per 1000 vaccinations, mean 0.4 alerts per clinician per month (range 0–8)). Clinicians reviewed 1,304 (94%) messages, responded to 209 (15%), and confirmed 16 for transmission to VAERS. An additional 16 high probability AEs were sent automatically. Reported events included seizure, pleural effusion, and lymphocytopenia. The odds of a VAERS report submission during the pilot period were 30.2 (95% CI, 9.52–95.5) times greater than the odds during the comparable pre-pilot period.
Conclusion and relevance:
An open-source EHR-based clinical decision support system can increase AE detection and reporting rates in VAERS.
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Source:
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Pubmed ID:26060294
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Pubmed Central ID:PMC6642796
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