Abstract
OBJECTIVES: To develop an algorithm to identify pregnancy episodes in women at childbearing age using SIDIAP (Information System for the Improvement of Research in Primary Care) data (Catalunya, Spain).To describe drugs dispensed during gestation. DESIGN: Construction of an algorithm to identify all pregnancy episodes occurred from January 2011 to June 2020 in women aged 12-50. The variables used to create the algorithm include first day of last menstrual period, reasons for pregnancy termination and diagnoses registered in the primary healthcare records. Population-based cohort study including the pregnancy episodes identified by the algorithm. SETTING: Catalonia, Spain. PARTICIPANTS: All women aged 12-50 with at least one pregnancy episode occurred during January 2011-June 2020. INTERVENTIONS: No interventions performed. PRIMARY AND SECONDARY OUTCOME MEASURES: Identification of pregnancy episodes through an algorithm and description of drug exposure. 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 B(12) plus folic acid (19.7%) and non-steroidal anti-inflammatory drugs (NSAIDs, 15.1%). The supplements were more frequently dispensed at least twice, and the drugs for acute conditions were mainly dispensed only once during the pregnancy episode. CONCLUSIONS: We developed an algorithm to automatically identify the pregnancy periods in SIDIAP.We described prescription drugs used during pregnancy. The most used ones were 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. TRIAL REGISTRATION NUMBER: EUPAS37675.