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Probabilistic Linkage of Assisted Reproductive Technology Information with Vital Records, Massachusetts 1997–2000

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Abstract

To assess the validity of probabilistic linkage (PL) in combining national surveillance data on assisted reproductive technology (ART) with Massachusetts birth and infant death data, for the purpose of monitoring maternal and child health outcomes of ART. A study conducted in 2006 utilized direct identifiers to match Massachusetts birth records with records on ART procedures performed to Massachusetts residents in fertility clinics located in Massachusetts and Rhode Island, achieving a linkage rate of 87.5%. The present study employed PL using the program Link Plus, without access to direct identifiers. The primary linking variables were maternal and infant dates of birth, and plurality. Ancillary variables such as maternal ZIP code and gravidity helped resolve duplicate matches and capture additional matches. PL linked 5,390 (87.8%) of 6,139 deliveries, correctly identifying 96.4% of the matches previously obtained using deterministic linkage methods. PL yielded a high linkage rate with satisfactory validity; this method may be applied in other states to help monitor the maternal and child health outcomes of ART.

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Acknowledgments

The authors thank Massachusetts Department of Public Health for their support of birth and infant death data and the Society for Assisted Reproductive Technology (SART) and the American Society for Reproductive Medicine (ASRM) for their support of ART data, their contributions are essential to the completion of the research.

Conflict of interest

None.

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Authors and Affiliations

  1. Division of Reproductive Health, Centers for Disease Control and Prevention, 4770 Buford Highway NE, MS k34, Atlanta, GA, 30341-3717, USA

    Yujia Zhang, Maurizio Macaluso & Tonji Durant

  2. Massachusetts Department of Public Health, Boston, MA, USA

    Bruce Cohen, Zi Zhang & Angela Nannini

  3. University of Massachusetts Medical School, Shrewsbury, MA, USA

    Zi Zhang

  4. Division of HIV/AIDS Prevention, Centers for Disease Control and Prevention, Atlanta, GA, USA

    Tonji Durant

  5. University of Massachusetts, Lowell, MA, USA

    Angela Nannini

  6. Division of Biostatistics and Epidemiology, Cincinnati Children’s Hospital Medical Center, Cincinnati, OH, USA

    Maurizio Macaluso

Authors
  1. Yujia Zhang
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  2. Bruce Cohen
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  3. Maurizio Macaluso
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  4. Zi Zhang
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  5. Tonji Durant
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  6. Angela Nannini
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Corresponding author

Correspondence to Yujia Zhang.

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Disclaimer : The findings and conclusions in this report are those of the authors and do not necessarily represent the official position of the Centers for Disease Control and Prevention.

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Zhang, Y., Cohen, B., Macaluso, M. et al. Probabilistic Linkage of Assisted Reproductive Technology Information with Vital Records, Massachusetts 1997–2000. Matern Child Health J 16, 1703–1708 (2012). https://doi.org/10.1007/s10995-011-0877-7

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  • DOI: https://doi.org/10.1007/s10995-011-0877-7

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