Meghan A Baker1, David C Kaelber2, David S Bar-Shain2, Pedro L Moro3, Bob Zambarano4, Megan Mazza5, Crystal Garcia5, Adam Henry5, Richard Platt5, Michael Klompas1. 1. Department of Population Medicine, Harvard Medical School and Harvard Pilgrim Health Care Institute Division of Infectious Diseases, Department of Medicine, Brigham and Women's Hospital, Boston, Massachusetts. 2. Center for Clinical Informatics Research and Education, MetroHealth System School of Medicine, Case Western Reserve University, Cleveland, Ohio. 3. Immunization Safety Office, Division of Healthcare Quality Promotion, Centers for Disease Control and Prevention, Atlanta, Georgia. 4. Commonwealth Informatics Inc, Waltham, Massachusetts. 5. Department of Population Medicine, Harvard Medical School and Harvard Pilgrim Health Care Institute.
Abstract
BACKGROUND: Reporting of adverse events (AEs) following vaccination can help identify rare or unexpected complications of immunizations and aid in characterizing potential vaccine safety signals. We developed an open-source, generalizable clinical decision support system called Electronic Support for Public Health-Vaccine Adverse Event Reporting System (ESP-VAERS) to assist clinicians with AE detection and reporting. METHODS: ESP-VAERS monitors patients' electronic health records for new diagnoses, changes in laboratory values, and new allergies following vaccinations. When suggestive events are found, ESP-VAERS sends the patient's clinician a secure electronic message with an invitation to affirm or refute the message, add comments, and submit an automated, prepopulated electronic report to VAERS. High-probability AEs are reported automatically if the clinician does not respond. We implemented ESP-VAERS in December 2012 throughout the MetroHealth System, an integrated healthcare system in Ohio. We queried the VAERS database to determine MetroHealth's baseline reporting rates from January 2009 to March 2012 and then assessed changes in reporting rates with ESP-VAERS. RESULTS: In the 8 months following implementation, 91 622 vaccinations were given. ESP-VAERS sent 1385 messages to responsible clinicians describing potential AEs. Clinicians opened 1304 (94.2%) messages, responded to 209 (15.1%), 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 implementation period were 30.2 (95% confidence interval, 9.52-95.5) times greater than the odds during the comparable preimplementation period. CONCLUSIONS: An open-source, electronic health record-based clinical decision support system can increase AE detection and reporting rates in VAERS.
BACKGROUND: Reporting of adverse events (AEs) following vaccination can help identify rare or unexpected complications of immunizations and aid in characterizing potential vaccine safety signals. We developed an open-source, generalizable clinical decision support system called Electronic Support for Public Health-Vaccine Adverse Event Reporting System (ESP-VAERS) to assist clinicians with AE detection and reporting. METHODS:ESP-VAERS monitors patients' electronic health records for new diagnoses, changes in laboratory values, and new allergies following vaccinations. When suggestive events are found, ESP-VAERS sends the patient's clinician a secure electronic message with an invitation to affirm or refute the message, add comments, and submit an automated, prepopulated electronic report to VAERS. High-probability AEs are reported automatically if the clinician does not respond. We implemented ESP-VAERS in December 2012 throughout the MetroHealth System, an integrated healthcare system in Ohio. We queried the VAERS database to determine MetroHealth's baseline reporting rates from January 2009 to March 2012 and then assessed changes in reporting rates with ESP-VAERS. RESULTS: In the 8 months following implementation, 91 622 vaccinations were given. ESP-VAERS sent 1385 messages to responsible clinicians describing potential AEs. Clinicians opened 1304 (94.2%) messages, responded to 209 (15.1%), 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 implementation period were 30.2 (95% confidence interval, 9.52-95.5) times greater than the odds during the comparable preimplementation period. CONCLUSIONS: An open-source, electronic health record-based clinical decision support system can increase AE detection and reporting rates in VAERS.
Authors: Christian Hoppe; Patrick Obermeier; Susann Muehlhans; Maren Alchikh; Lea Seeber; Franziska Tief; Katharina Karsch; Xi Chen; Sindy Boettcher; Sabine Diedrich; Tim Conrad; Bron Kisler; Barbara Rath Journal: Drug Saf Date: 2016-10 Impact factor: 5.606
Authors: Anna Lewandowska; Tomasz Lewandowski; Grzegorz Rudzki; Sławomir Rudzki; Barbara Laskowska Journal: Int J Environ Res Public Health Date: 2020-05-24 Impact factor: 3.390