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Use of telephone helpline data for syndromic surveillance of adverse events following immunization in Australia: A retrospective study, 2009 to 2017.
Mesfin, Yonatan M; Cheng, Allen C; Enticott, Joanne; Lawrie, Jock; Buttery, Jim P.
Afiliação
  • Mesfin YM; Monash Centre for Health Research and Implementation, Monash University, Australia. Electronic address: Yonatan.Mesfin@monash.edu/mogesyoni@gmail.com.
  • Cheng AC; Infection Prevention and Healthcare Epidemiology Unit, Alfred Health Melbourne, Australia.
  • Enticott J; Monash Centre for Health Research and Implementation, Monash University, Australia; School of Primary and Allied Health Care, Monash University, Melbourne, Australia.
  • Lawrie J; Monash Centre for Health Research and Implementation, Monash University, Australia.
  • Buttery JP; Monash Centre for Health Research and Implementation, Monash University, Australia; Department of Paediatrics, Monash University, Australia; Monash Children Hospital, Monash Health, Melbourne, Australia.
Vaccine ; 38(34): 5525-5531, 2020 07 22.
Article em En | MEDLINE | ID: mdl-32593607
ABSTRACT

BACKGROUND:

The increasing availability of electronic healthcare data offers an opportunity to enhance adverse events following immunisation (AEFI) signal monitoring in near real-time.

AIM:

To evaluate the potential use of telephone helpline data to augment the existing AEFI surveillance system in Victoria, Australia.

METHODS:

Anonymised telephone helpline call data were extracted between 2009 and 2017. For comparison, we included AEFI reports to the Victorian enhanced passive surveillance system, SAEFVIC-"Surveillance of Adverse Events Following Vaccination In the Community". The temporal pattern cross-correlation coefficient at different time lags was estimated as a measure of timeliness evaluation. Historically known AEFI signals in 2010 and 2015 were examined using the Farrington statistical signal detection algorithm.

RESULT:

During the study period, overall, the telephone helpline centre received 2,005,226 calls. Of these, 0.68% (13,719) were AEFI-related. In the same period, SAEFVIC received 10,367 AEFI related reports. Cross-correlation analysis, generally, showed that the two datasets were moderately correlated (r = 0.4) at a negative lag of 1 week. For individual years, the cross-correlation coefficient was highest (r = 0.66) in 2010 with the telephone helpline data leading by 2 weeks. Our analysis indicated the 2010 reported incidence of febrile convulsions and the 2015 reported increased allergic-related reactions following seasonal influenza vaccination three weeks and one week earlier respectively.

CONCLUSION:

Telephone helpline data was able to detect an increased rate of AEFI earlier than the enhanced passive AEFI surveillance system. This dataset offers a valuable and near real-time component of an integrated AEFI early signal detection system in Australia.
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Texto completo: 1 Base de dados: MEDLINE Assunto principal: Sistemas de Notificação de Reações Adversas a Medicamentos / Vigilância de Evento Sentinela Tipo de estudo: Observational_studies / Screening_studies País/Região como assunto: Oceania Idioma: En Revista: Vaccine Ano de publicação: 2020 Tipo de documento: Article

Texto completo: 1 Base de dados: MEDLINE Assunto principal: Sistemas de Notificação de Reações Adversas a Medicamentos / Vigilância de Evento Sentinela Tipo de estudo: Observational_studies / Screening_studies País/Região como assunto: Oceania Idioma: En Revista: Vaccine Ano de publicação: 2020 Tipo de documento: Article