Information systems for vaccine safety surveillance

Area of Science:

• Public Health
• Pharmacovigilance
• Data Science

Background:

• Post-licensure vaccine safety surveillance is crucial for maintaining safe vaccination programs.
• Electronic health data and internet-based information have transformed healthcare information accessibility.
• Detecting rare adverse events following immunization (AEFI) requires diverse data sources.

Purpose of the Study:

• To explore the utilization of varied electronic health data and internet-based media for vaccine safety surveillance.
• To assess the advantages and disadvantages of different surveillance methods.
• To highlight the complementary nature of various AEFI detection strategies.

Main Methods:

• Utilizing electronic spontaneous reporting systems.
• Implementing automated solicited surveillance.
• Screening diverse electronic health record (EHR) types.
• Applying natural language processing (NLP) to internet-based data for AEFI mentions.
• Employing vaccine safety datalinking for hypothesis testing.

Main Results:

• Various electronic data sources and internet media offer potential for AEFI surveillance.
• Methods range from hypothesis-generating signal detection to hypothesis-testing verification.
• Different surveillance approaches possess unique strengths and weaknesses.
• Vaccine safety datalinking can serve to verify potential safety signals.

Conclusions:

• Multiple electronic data streams and internet sources can enhance vaccine safety surveillance.
• A combination of surveillance methods provides a more comprehensive approach to detecting and verifying AEFI.
• Leveraging diverse data sources is key to maintaining the safety and effectiveness of vaccination programs.