Immunization-Safety Monitoring Systems for the 2009 H1N1 Monovalent Influenza Vaccination Program

Salmon, Daniel A.; Akhtar, Aysha; Mergler, Michelle J.; Vannice, Kirsten; Izurieta, Héctor S.; Ball, Robert; Lee, Grace M.; Vellozzi, Claudia; Garman, Patrick M.; Cunningham, Francesca; Gellin, Bruce G.; Koh, Howard K.; Lurie, Nicole

doi:10.1542/peds.2010-1722l

Cited by 44 publications

(32 citation statements)

References 20 publications

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“…19, 25, 26 An added benefit is that the data are held by those who are best able to consult on proper use and interpretation. Both single-use 27, 28 and multi-use networks are possible. Multi-use networks such as the HMO Research Network (HMORN), 29, 30 the CDC-sponsored Vaccine Safety Datalink, 31-33 and the FDA-sponsored Mini-Sentinel 12 build and maintain data and administrative infrastructure to support multiple studies.…”

Section: Introductionmentioning

confidence: 99%

Data Quality Assessment for Comparative Effectiveness Research in Distributed Data Networks

2013

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Background Electronic health information routinely collected during healthcare delivery and reimbursement can help address the need for evidence about the real-world effectiveness, safety, and quality of medical care. Often, distributed networks that combine information from multiple sources are needed to generate this real-world evidence. Objective We provide a set of field-tested best practices and a set of recommendations for data quality checking for comparative effectiveness research (CER) in distributed data networks. Methods Explore the requirements for data quality checking and describe data quality approaches undertaken by several existing multi-site networks. Results There are no established standards regarding how to evaluate the quality of electronic health data for CER within distributed networks. Data checks of increasing complexity are often employed, ranging from consistency with syntactic rules to evaluation of semantics and consistency within and across sites. Temporal trends within and across sites are widely used, as are checks of each data refresh or update. Rates of specific events and exposures by age group, sex, and month are also common. Discussion Secondary use of electronic health data for CER holds promise but is complex, especially in distributed data networks that incorporate periodic data refreshes. The viability of a learning health system is dependent on a robust understanding of the quality, validity, and optimal secondary uses of routinely collected electronic health data within distributed health data networks. Robust data quality checking can strengthen confidence in findings based on distributed data network.

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Section: Introductionmentioning

confidence: 99%

Data Quality Assessment for Comparative Effectiveness Research in Distributed Data Networks

2013

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“…11 The second section of this supplement is focused on identifying and addressing vaccine-safety concerns among parents:…”

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confidence: 99%

Editors' Introduction: Vaccine Safety Throughout the Product Life Cycle

2011

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“…8,9 Two key goals were to distinguish genuine adverse reactions from temporal or coincidental associations and to maintain public confidence. 8 In reviewing this plan, the National Vaccine Advisory Committee recommended expanding real-time active surveillance capacity beyond the Vaccine Safety Datalinkthe only ongoing US system then capable of active surveillance of the general population. 10 …”

Section: The 2009 H1n1 Vaccination Programmentioning

confidence: 99%

Success Of Program Linking Data Sources To Monitor H1N1 Vaccine Safety Points To Potential For Even Broader Safety Surveillance

et al. 2012

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In response to the 2009 H1N1 pandemic and subsequent vaccination program, the Department of Health and Human Services and collaborators developed the Post-Licensure Rapid Immunization Safety Monitoring (PRISM) Program as a demonstration project to detect rare adverse events rapidly. The program monitored three million people who had received the H1N1 vaccine by linking data from large private health plans and from public immunization registries that had originally not been designed to share data, and on a larger scale than had been previously attempted. The program generated safety data in two weeks rather than three to six monty 10ths-the standard time frame achievable using health plan data. PRISM substantially contributed to the understanding of the safety of H1N1 vaccines. Its use in the case of H1N1 highlights the necessity of proactive planning, scalable infrastructure, and public-private partnerships in tracking adverse events after vaccination in epidemics. It also illustrates how data could be integrated to produce policy-relevant information for other medical products.

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Immunization-Safety Monitoring Systems for the 2009 H1N1 Monovalent Influenza Vaccination Program

Cited by 44 publications

References 20 publications

Data Quality Assessment for Comparative Effectiveness Research in Distributed Data Networks

Data Quality Assessment for Comparative Effectiveness Research in Distributed Data Networks

Editors' Introduction: Vaccine Safety Throughout the Product Life Cycle

Success Of Program Linking Data Sources To Monitor H1N1 Vaccine Safety Points To Potential For Even Broader Safety Surveillance

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