Tomofumi Ishikawa1, Taku Obara2,3,4, Hidekazu Nishigori2,5, Keiko Miyakoda4, Ryusuke Inoue6, Tetsuro Hoshiai5, Masatoshi Saito5, Nobuo Yaegashi2,4,5, Nariyasu Mano1,3. 1. Laboratory of Clinical Pharmacy, Tohoku University Graduate School of Pharmaceutical Sciences, Sendai, Miyagi, Japan. 2. Environment and Genome Research Center, Tohoku University Graduate School of Medicine, Sendai, Miyagi, Japan. 3. Department of Pharmaceutical Sciences, Tohoku University Hospital, Sendai, Miyagi, Japan. 4. Tohoku University Tohoku Medical Megabank Organization, Sendai, Miyagi, Japan. 5. Department of Gynecology and Obstetrics, Tohoku University Graduate School of Medicine, Sendai, Miyagi, Japan. 6. Department of Medical Informatics, Tohoku University Graduate School of Medicine, Sendai, Miyagi, Japan.
Abstract
PURPOSE: To develop and assess algorithms to determine the onset of pregnancy and delivery date using health administrative data from a university hospital in Japan. METHODS: All women who were hospitalized in the maternity ward and had at least one pregnancy that ended with a delivery during the period of January 2014 and December 2015 were included in this study. The true delivery date was obtained from the electronic medical records and was used as a gold standard. The onset of pregnancy was calculated by subtracting the gestational age at birth from the delivery date based on the electronic medical records and was also used as a gold standard. The administrative data-based algorithms to identify (1) the onset of pregnancy estimated from the gestational age recorded as part of a diagnosis during a specific visit and (2) the delivery date estimated using the delivery-related diagnosis, procedure, or prescription were compared with the gold-standard data. RESULTS: Of the 1705 women included in this study, the onset of pregnancy was determined in 1704 subjects with 1582 (92.8%) within ± 7 days from the gold-standard date of pregnancy onset. The delivery date was determined in 1654 subjects, and 1594 (96.4%) were within ± 7 days before the true delivery date using the algorithm of "selected" diagnosis and a surgical procedure followed by some other delivery-related data. CONCLUSIONS: The algorithms developed in this study are expected to accelerate future studies for real-world exposure and quantify drug safety during pregnancy using Japanese health care administrative databases.
PURPOSE: To develop and assess algorithms to determine the onset of pregnancy and delivery date using health administrative data from a university hospital in Japan. METHODS: All women who were hospitalized in the maternity ward and had at least one pregnancy that ended with a delivery during the period of January 2014 and December 2015 were included in this study. The true delivery date was obtained from the electronic medical records and was used as a gold standard. The onset of pregnancy was calculated by subtracting the gestational age at birth from the delivery date based on the electronic medical records and was also used as a gold standard. The administrative data-based algorithms to identify (1) the onset of pregnancy estimated from the gestational age recorded as part of a diagnosis during a specific visit and (2) the delivery date estimated using the delivery-related diagnosis, procedure, or prescription were compared with the gold-standard data. RESULTS: Of the 1705 women included in this study, the onset of pregnancy was determined in 1704 subjects with 1582 (92.8%) within ± 7 days from the gold-standard date of pregnancy onset. The delivery date was determined in 1654 subjects, and 1594 (96.4%) were within ± 7 days before the true delivery date using the algorithm of "selected" diagnosis and a surgical procedure followed by some other delivery-related data. CONCLUSIONS: The algorithms developed in this study are expected to accelerate future studies for real-world exposure and quantify drug safety during pregnancy using Japanese health care administrative databases.