Michigan Newborn Screening & Live Births Records Linkage and Follow-Up of Potentially Un-Screened Infants. Steven J. Korzeniewski, MA, MSc, Maternal & Child Health Epidemiology Section Manager Violanda Grigorescu, MD, MSPH, Glenn E. Copeland, BS, William I. Young, Ph.D.,
Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author.While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server.
Steven J. Korzeniewski, MA, MSc,
Maternal & Child Health Epidemiology Section Manager
Violanda Grigorescu, MD, MSPH, Glenn E. Copeland, BS, William I. Young, Ph.D.,
Michigan Department of Community Health
Background/Intent of linkage
Methods (software, data management, algorithm)
Public Health Implications
Linkages re-initiated to identify live births potentially unscreened.
Initial efforts were not sustainable
Intended to be mutually beneficial to newborn screening follow-up program and vital records.
Means to assess data quality
Data received from November 2007 through March 2008 were used for this study
2008 transitioned from DOS based to Web based electronic birth certificate system
Newborn screening card number included on birth record
SAS v9.1 (Cary, N.C.) used to create text files
Record linkage and follow-up conducted by NBS Follow-up Program
Newborn screening & Michigan Care Improvement Registry (MCIR) data used for follow-up
Linkage via Link Plus
A probabilistic record linkage program
Developed for cancer registries at the Centers for Disease Control and Prevention’s (CDC) Division of Cancer Prevention and Control in support of CDC's National Program of Cancer Registries (NCPR).
Can be used with any type of data in fixed width or delimited format
Linkage score (probabilistic linkage)
based on the theoretical frame work developed by Fellegi and Sunter (1969)
sum of the logarithm of odds across all matching variables, based on the probability that a matching variable agrees given that a comparison pair is a match and the probability that a matching variable agrees given that a comparison pair is not a match
Blocking variables - used to ‘block’ (or partition) the two files
Matching variables are compared between records matching on the blocking variable.
Methods Follow-Up of Potentially Un-Screened Infants
Unmatched records sent to follow-up staff
Staff search NBS data
Contact birth hospital
Send certified letter to parent requesting screen or signed refusal letter
Probabilistic linkage is subjective………. & useful
Linkage success is a function of
An ability to deal with discordance
Match rates change over time and may require alternations in linkage algorithms
Manual checking of initial linkage results and follow-up results must be used to determine algorithm changes and avoid false matches.
Live Births to NBS data matching is a “best case” scenario given data are collected at virtually the same time, same place, and often by the same person.
Significant investment of time for
Initial data management programming
Understanding how to select algorithm
Determination of borderline matches
Assessment of follow-up results
Benefits beyond identification of potentially unscreened children include
Data quality check
Link to various datasets through vital records (i.e.- birth defects, EHDI, etc.)
Link Plus is applicable to MCH databases
Linkage facilitates data usage with minimal cost investments
Linkage is successful at detecting unscreened infants (we have identified several)
However, linkage should be handled with caution
Co-investigators: Violanda Grigorescu, MD, MSPH, Glenn E. Copeland, BS, William I. Young, Ph.D.,
NBS Follow-up Staff