The MOSART database: linking the SART CORS clinical database to the population-based Massachusetts PELL reproductive public health data system.

Although Assisted Reproductive Technology (ART) births make up 1.6 % of births in the US, the impact of ART on subsequent infant and maternal health is not well understood. Clinical ART treatment records linked to population data would be a powerful tool to study long term outcomes among those treated or not by ART. This paper describes the development of a database intended to accomplish this task. We constructed the Massachusetts Outcomes Study of Assisted Reproductive Technology (MOSART) database by linking the Society of Assisted Reproductive Technologies Clinical Outcomes Reporting System (SART CORS) and the Massachusetts (MA) Pregnancy to Early Life Longitudinal (PELL) data systems for children born to MA resident women at MA hospitals between July 2004 and December 2008. PELL data representing 282,971 individual women and their 334,152 deliveries and 342,035 total births were linked with 48,578 cycles of ART treatment in SART CORS delivered to MA residents or women receiving treatment in MA clinics, representing 18,439 eligible women of whom 9,326 had 10,138 deliveries in this time period. A deterministic five phase linkage algorithm methodology was employed. Linkage results, accuracy, and concordance analyses were examined. We linked 9,092 (89.7 %) SART CORS outcome records to PELL delivery records overall, including 95.0 % among known MA residents treated in MA clinics; 70.8 % with full exact matches. There were minimal differences between matched and unmatched delivery records, except for unknown residency and out-of-state ART site. There was very low concordance of reported use of ART treatment between SART CORS and PELL (birth certificate) data. A total of 3.4 % of MA children (11,729) were identified from ART assisted pregnancies (6,556 singletons; 5,173 multiples). The MOSART linked database provides a strong basis for further longitudinal ART outcomes studies and supports the continued development of potentially powerful linked clinical-public health databases.