OBJECTIVES: We aimed to develop an algorithm to identify pregnancy episodes for all women aged from 12 to 50 between January 2011 to June 2020 using data from SIDIAP (Information System for the Improvement of Research in Primary Care) database, Catalunya, Spain. With the pregnancies identified by the algorithm we aimed to describe the drugs dispensed during gestation.
DESIGN: Construction of an algorithm to identify all pregnancy episodes occurred from January 2011 to June 2022 in women at childbearing age. Population-based cohort study including the pregnancy episodes identified by the algorithm.
SETTING: Primary health care in Catalonia, Spain.
PARTICIPANTS: All women from 12 to 50 with at least one pregnancy episode occurred from January 2011 to June 2020.
INTERVENTIONS: As an observational study, no interventions were performed.
PRIMARY AND SECONDARY OUTCOME MEASURES: Identification of pregnancy episodes through an algorithm and description of drug exposure during these episodes.
RESULTS: We identified 327,865 pregnancy episodes in 250,910 people with a mean age of 31.3 years. During the study period, 83.4% of the episodes were exposed to at least one drug. The most frequent groups dispensed were: iron preparations (48% of pregnancy episodes), iodine therapy (40.2%), analgesics and antipyretics (28%), penicillins (19.8%), vitamin B12 combined with folic acid (19.7%) and non-steroidal anti-inflammatory drugs (NSAID, 15.1%). The supplements were more frequently dispensed at least twice, and the drugs indicated in acute conditions were mainly dispensed only once during the pregnancy episode.
CONCLUSIONS: We have developed an algorithm to automatically identify the pregnancy periods in SIDIAP database. We have described the prescription drugs used during pregnancy. The most used ones were recommended supplements, analgesics, NSAID or antibiotics. SIDIAP might be an efficient database to study drug safety during pregnancy and the consequences of drug use in the offspring.
