Advanced Clinical Decision Support for Vaccine Adverse Event Detection and Reporting

Details

• Alternative Title:
  Clin Infect Dis
• Personal Author:
  Baker, Meghan A. ; Kaelber, David C. ; Bar-Shain, David S. ; Moro, Pedro L. ; Zambarano, Bob ; Mazza, Megan ; Garcia, Crystal ; Henry, Adam ; Platt, Richard ; Klompas, Michael
• 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.
  
  
• Subjects:
  Adolescent Adult Adverse Drug Reaction Reporting Systems Aged Aged, 80 And Over Article Child Child, Preschool Decision Support Systems, Clinical Drug-Related Side Effects And Adverse Reactions Female Health Services Research Humans Infant Infant, Newborn Male Middle Aged Ohio Risk Management Vaccines Young Adult

  More +
• Source:
  Clin Infect Dis. 61(6):864-870
• Pubmed ID:
  26060294
• Pubmed Central ID:
  PMC6642796
• Document Type:
  Journal Article
• Funding:
  CC999999/Intramural CDC HHS/United States ; 200-2011-42037/PHS HHS/United States
• Volume:
  61
• Issue:
  6
• Collection(s):
  CDC Public Access
• Main Document Checksum:
  urn:sha256:fea483b1aa351053bf57aefc81a72bb97142c31add9bf51e26ac4a1bd8287db0
• Download URL:
  https://stacks.cdc.gov/view/cdc/80052/cdc_80052_DS1.pdf
• File Type:
  [PDF - 235.66 KB ]