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Michigan Newborn Screening & Live Births Records Linkage and Follow-Up of Potentially Un-Screened Infants

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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.,

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Presentation Transcript
slide1

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.,

Michigan Department of Community Health

outline
Outline

Background/Intent of linkage

Methods (software, data management, algorithm)

Results

Discussion

Public Health Implications

background
Background

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

methods
Methods

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

methods1
Methods

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

Free $$

methods2
Methods

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

methods3
Methods

Blocking variables - used to ‘block’ (or partition) the two files

Matching variables are compared between records matching on the blocking variable.

methods4
Methods

Follow-up

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

discussion
Discussion

Probabilistic linkage is subjective………. & useful

Linkage success is a function of

Cutoff selection

Data quality

Strategy

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.

discussion1
Discussion

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.)

public health implications
Public Health Implications

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

acknowledgements
Acknowledgements

Co-investigators: Violanda Grigorescu, MD, MSPH, Glenn E. Copeland, BS, William I. Young, Ph.D.,

NBS Follow-up Staff

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