TY - JOUR
T1 - Estimation of vaccination coverage from electronic healthcare records; methods performance evaluation - A contribution of the ADVANCE-project
AU - Braeye, Toon
AU - Bauchau, Vincent
AU - Sturkenboom, Miriam
AU - Emborg, Hanne-Dorthe
AU - García, Ana Llorente
AU - Huerta, Consuelo
AU - Merino, Elisa Martin
AU - Bollaerts, Kaatje
N1 - Funding Information:
The research leading to these results has received support from the Innovative Medicines Initiative Joint Undertaking under ADVANCE grant agreement no. 115557, resources of which are composed of financial contribution from the European Union?s Seventh Framework Programme (FP7/2007-2013) and EFPIA companies? in kind contribution. Co-author V.B received a salary from GSK during the period in which this study was performed. The study sponsors had no role in study design, in the collection, analysis and interpretation of data, in the writing of the report, or in the decision to submit the report for publication. The specific roles of these authors are articulated in the ?author contributions? section. This work was carried out as part of the ?Accelerated development of vaccine benefit-risk collaboration in Europe? (ADVANCE) project, launched in 2013, funded by the Innovative Medicines Initiative (http://www.advance-vaccines.eu). The aim of ADVANCE is to help health professionals, regulatory agencies, public health institutions, vaccine manufacturers, and the general public make well-informed and timely decisions on benefits and risks of marketed vaccines by establishing a framework and toolbox to enable rapid delivery of reliable data on vaccine benefits and risks.
Publisher Copyright:
© 2019 Braeye et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
PY - 2019/9/1
Y1 - 2019/9/1
N2 - INTRODUCTION: The Accelerated Development of VAccine beNefit-risk Collaboration in Europe (ADVANCE) is a public private collaboration aiming to develop and test a system for rapid benefit-risk (B/R) monitoring of vaccines, using existing electronic healthcare record (eHR) databases in Europe. Part of the data in such sources is missing due to incomplete follow-up hampering the accurate estimation of vaccination coverage. We compared different methods for coverage estimation from eHR databases; naïve period prevalence, complete case period prevalence, period prevalence adjusted for follow-up time, Kaplan-Meier (KM) analysis and (adjusted) inverse probability weighing (IPW).METHODS: We created simulation scenarios with different proportions of completeness of follow-up. Both completeness independent and dependent from vaccination date and status were considered. The root mean squared error (RMSE) and relative difference between the estimated and true coverage were used to assess the performance of the different methods for each of the scenarios. We included data examples on the vaccination coverage of human papilloma virus and pertussis component containing vaccines from the Spanish BIFAP database.RESULTS: Under completeness independent from vaccination date or status, several methods provided estimates with bias close to zero. However, when dependence between completeness of follow-up and vaccination date or status was present, all methods generated biased estimates. The IPW/CDF methods were generally the least biased. Preference for a specific method should be based on the type of censoring and type of dependence between completeness of follow-up and vaccination. Additional insights into these aspects, might be gained by applying several methods.
AB - INTRODUCTION: The Accelerated Development of VAccine beNefit-risk Collaboration in Europe (ADVANCE) is a public private collaboration aiming to develop and test a system for rapid benefit-risk (B/R) monitoring of vaccines, using existing electronic healthcare record (eHR) databases in Europe. Part of the data in such sources is missing due to incomplete follow-up hampering the accurate estimation of vaccination coverage. We compared different methods for coverage estimation from eHR databases; naïve period prevalence, complete case period prevalence, period prevalence adjusted for follow-up time, Kaplan-Meier (KM) analysis and (adjusted) inverse probability weighing (IPW).METHODS: We created simulation scenarios with different proportions of completeness of follow-up. Both completeness independent and dependent from vaccination date and status were considered. The root mean squared error (RMSE) and relative difference between the estimated and true coverage were used to assess the performance of the different methods for each of the scenarios. We included data examples on the vaccination coverage of human papilloma virus and pertussis component containing vaccines from the Spanish BIFAP database.RESULTS: Under completeness independent from vaccination date or status, several methods provided estimates with bias close to zero. However, when dependence between completeness of follow-up and vaccination date or status was present, all methods generated biased estimates. The IPW/CDF methods were generally the least biased. Preference for a specific method should be based on the type of censoring and type of dependence between completeness of follow-up and vaccination. Additional insights into these aspects, might be gained by applying several methods.
UR - https://www.scopus.com/pages/publications/85072380346
U2 - 10.1371/journal.pone.0222296
DO - 10.1371/journal.pone.0222296
M3 - Article
C2 - 31532806
SN - 1932-6203
VL - 14
JO - PLoS ONE
JF - PLoS ONE
IS - 9
M1 - e0222296
ER -