Validation of mother-infant linkage using Medicaid Case ID variable within the Medicaid Analytic eXtract (MAX) database

Caitlin A. Knox, Christian Hampp, Kristin Palmsten, Yanmin Zhu, Soko Setoguchi Iwata, Babette Brumback, Richard Segal, Almut G. Winterstein

Research output: Contribution to journalArticle

1 Scopus citations


Purpose: The state-assigned Case ID number in the Medicaid Analytic eXtract (MAX) allows for potential linkage of mothers to infants. No validation of respective linkage algorithms is available. We established and validated an algorithm within MAX that links mothers to infants and to identify factors influencing successful mother-infant linkage. Methods: We identified all mother-infant pairs in FL and TX birth certificates records (BCR) that could be linked individually to MAX records (1999-2005 for FL and 1999-2010 for TX) based on Social Security Number (gold standard pairs). Case ID linkage performance was evaluated as the proportion of gold standard mother-infant pairs that were identified by the algorithm (sensitivity) and the proportion of algorithm defined mother-infant pairs that were correctly linked. Generalized estimating equations were used to calculate the probability for successful Case ID algorithm linkage versus non-linkage using maternal and infant characteristics. Results: We identified 323,160 gold standard pairs in FL BCR and MAX and 1,025,350 in TX BCR and MAX. Depending on Medicaid enrollment the algorithm sensitivity ranged from 85.51% to 87.96% in FL and 19.60% to 35.75% in TX. In both states, positive predictive value exceeded 99%, regardless of enrollment periods. Determinants for successful linkage varied across states, but suggested better results for younger mothers, minority women, and those with lower educational achievement. Conclusions: Our algorithm can correctly link liveborn infants to their mothers. The algorithm's sensitivity in identifying pairs varied across states, but PPV was consistently high. Linkage performance was associated with certain characteristics that may affect representativeness of successfully linked pairs.

Original languageEnglish (US)
Pages (from-to)1222-1230
Number of pages9
JournalPharmacoepidemiology and drug safety
Issue number9
StatePublished - Sep 1 2019

All Science Journal Classification (ASJC) codes

  • Pharmacology (medical)
  • Epidemiology


  • Case ID
  • Medicaid
  • pharmacoepidemiology
  • pregnancy
  • validation

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