Building a Data Linkage Foundation for Mother-Child Pharmacoepidemiology Research

A mother-child data linkage approach using data from the information system for the development of research in primary care (SIDIAP) in Catalonia

BACKGROUND

Large-scale clinical databases containing routinely collected electronic health records (EHRs) data are a valuable source of information for research studies. For example, they can be used in pharmacoepidemiology studies to evaluate the effects of maternal medication exposure on neonatal and pediatric outcomes. Yet, this type of studies is infeasible without proper mother-child linkage.

METHODS

We leveraged all eligible active records (N = 8,553,321) of the Information System for Research in Primary Care (SIDIAP) database. Mothers and infants were linked using a deterministic approach and linkage accuracy was evaluated in terms of the number of records from candidate mothers that failed to link. We validated the mother-child links identified by comparison of linked and unlinked records for both candidate mothers and descendants. Differences across these two groups were evaluated by means of effect size calculations instead of p-values. Overall, we described our data linkage process following the GUidance for Information about Linking Data sets (GUILD) principles.

RESULTS

We were able to identify 744,763 unique mother-child relationships, linking 83.8 % candidate mothers with delivery dates within a period of 15 years. Of note, we provide a record-level category label used to derive a global confidence metric for the presented linkage process. Our validation analysis showed that the two groups were similar in terms of a number of aggregated attributes.

CONCLUSIONS

Complementing the SIDIAP database with mother-child links will allow clinical researchers to expand their epidemiologic studies with the ultimate goal of improving outcomes for pregnant women and their children. Importantly, the reported information at each step of the data linkage process will contribute to the validity of analyses and interpretation of results in future studies using this resource.

Development and evaluation of an algorithm to link mothers and infants in two US commercial healthcare claims databases for pharmacoepidemiology research

BACKGROUND

Administrative healthcare claims databases are used in drug safety research but are limited for investigating the impacts of prenatal exposures on neonatal and pediatric outcomes without mother-infant pair identification. Further, existing algorithms are not transportable across data sources. We developed a transportable mother-infant linkage algorithm and evaluated it in two, large US commercially insured populations.

METHODS

We used two US commercial health insurance claims databases during the years 2000 to 2021. Mother-infant links were constructed where persons of female sex 12-55 years of age with a pregnancy episode ending in live birth were associated with a person who was 0 years of age at database entry, who shared a common insurance plan ID, had overlapping insurance coverage time, and whose date of birth was within ± 60-days of the mother's pregnancy episode live birth date. We compared the characteristics of linked vs. non-linked mothers and infants to assess similarity.

RESULTS

The algorithm linked 3,477,960 mothers to 4,160,284 infants in the two databases. Linked mothers and linked infants comprised 73.6% of all mothers and 49.1% of all infants, respectively. 94.9% of linked infants' dates of birth were within ± 30-days of the associated mother's pregnancy episode end dates. Characteristics were largely similar in linked vs. non-linked mothers and infants. Differences included that linked mothers were older, had longer pregnancy episodes, and had greater post-pregnancy observation time than mothers with live births who were not linked. Linked infants had less observation time and greater healthcare utilization than non-linked infants.

CONCLUSIONS

We developed a mother-infant linkage algorithm and applied it to two US commercial healthcare claims databases that achieved a high linkage proportion and demonstrated that linked and non-linked mother and infant cohorts were similar. Transparent, reusable algorithms applied to large databases enable large-scale research on exposures during pregnancy and pediatric outcomes with relevance to drug safety. These features suggest studies using this algorithm can produce valid and generalizable evidence to inform clinical, policy, and regulatory decisions.

Building a Data Linkage Foundation for Mother-Child Pharmacoepidemiology Research

BACKGROUND

Expanding our understanding of the effects of maternal medication exposure through research is a public health priority and will help inform both clinical and policy decision making, ultimately improving outcomes for pregnant women and their children.

OBJECTIVE

Our objective was to describe a linked-data research platform that facilitates studies of pregnancy medication exposures and policy changes on maternal and child health outcomes.

METHODS

Mothers receiving Medicaid benefits were probabilistically linked with newborns in the Tennessee Medicaid program (TennCare) through three distinct linkage processes. Medicaid claims data and state birth and fetal death certificate records (vital records) were used to identify and link potential mothers, deliveries, and newborn children. The linkage process started with the creation of a merged pool of potential mothers and eligible deliveries, which was linked to vital records and to children's records. In the last step, linked records from the preceding steps were combined into the final Mother-child linked records. For each data linkage step, rubrics and scoring systems for exact and partial matches and mismatches among key linkage fields were applied and used to examine the strength of the probabilistic linkages. Summary linkage yields for year 2013 are reported for illustration purposes.

RESULTS

Among the 84,253 potential deliveries, 1,761,557 eligible potential mothers, and 51,400 eligible children identified in Tennessee Medicaid records in 2013, a total of 60,265 of these records were uniquely linked to vital records, including 46,172 (77%) with linked mother-child-vital records. Among the 51,400 eligible children records identified in Tennessee Medicaid for that year, 97% (50,053) had at least one link to vital records or a mother-delivery record. In linked records, the median maternal age was 24 years, and the median gestational age was 39 weeks. About 33% of pregnant women underwent cesarean birth, and 1% of births were classified as complicated deliveries.

CONCLUSIONS

Supplementing existing Medicaid claims data with birth certificate records complements administrative claims information and allows for detailed assessments of pregnancy exposures and policy changes on mother and child outcomes.