Development of algorithms to determine the onset of pregnancy and delivery date using health care administrative data in a university hospital in Japan

• Published in: Pharmacoepidemiology and drug safety Vol. 27; no. 7; pp. 751 - 762
• Main Authors: Ishikawa, Tomofumi, Obara, Taku, Nishigori, Hidekazu, Miyakoda, Keiko, Inoue, Ryusuke, Hoshiai, Tetsuro, Saito, Masatoshi, Yaegashi, Nobuo, Mano, Nariyasu
• Format: Journal Article
• Language: English
• Published: England Wiley Subscription Services, Inc 01.07.2018
• Subjects: administrative data; Algorithms; beginning of pregnancy; Diagnosis; Electronic health records; Electronic medical records; Gestational age; Medical records; obstetric delivery; pharmacoepidemiology; Pharmacovigilance; Pregnancy; Japan; electronic medical records; obstetric delivery; pregnancy; beginning of pregnancy; gestational age; administrative data; pharmacoepidemiology
• ISSN: 1053-8569; 1099-1557; 1099-1557
• DOI: 10.1002/pds.4444

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.