Development and validation of claims-based algorithms to identify pregnancy based on data from a university hospital in Japan

التفاصيل البيبلوغرافية
العنوان: Development and validation of claims-based algorithms to identify pregnancy based on data from a university hospital in Japan
المؤلفون: Kentaro Tajima, Tomofumi Ishikawa, Aoi Noda, Fumiko Matsuzaki, Kei Morishita, Ryusuke Inoue, Noriyuki Iwama, Hidekazu Nishigori, Junichi Sugawara, Masatoshi Saito, Taku Obara, Nariyasu Mano
المصدر: Current Medical Research and Opinion. 38:1651-1654
بيانات النشر: Informa UK Limited, 2022.
سنة النشر: 2022
مصطلحات موضوعية: Adult, Databases, Factual, Japan, Pregnancy, Electronic Health Records, Humans, Female, General Medicine, Algorithms, Hospitals
الوصف: When using administrative data, validation is essential since these data are not collected for research purposes and misclassification can occur. Thus, this study aimed to develop algorithms identifying pregnancy and to evaluate the validity of administrative claims data in Japan. All females who visited the Tohoku University Hospital Department of Obstetrics in 2018 were included. The diagnosis, medical procedure, medication, and medical service addition fee data were utilized to identify pregnancy, with the electronic medical records set as the gold standard. Combination algorithms were developed using predefined pregnancy-related claims data with a positive predictive value (PPV) ≥80%. Sensitivity (SE), specificity (SP), PPV, and negative predictive value (NPV) with their corresponding 95% confidence intervals (CIs) were calculated for these combination algorithms. This study included 1757 females with a mean age of 32.8 (standard deviation: 5.9) years. In general, the individual claims data were able to identify pregnancy with a PPV ≥80%; however, the number of pregnancies identified using a single claims data was limited. Based on the combination algorithm with all of the categories, including diagnosis, medical procedure, medication, and medical service addition, the calculated SE, SP, PPV, and NPV were 73.4% (95% CI: 71.2%–75.4%), 96.9% (95% CI: 89.3%–99.6%), 99.8%,(95% CI: 99.4%–100.0%), and 12.3% (95% CI: 9.6%–15.4%), respectively. The combination algorithm to identify pregnancy demonstrated a high PPV and moderate SE. The algorithm validated in this study is expected to accelerate future studies that aim to identify pregnancies and evaluate pregnancy outcome.
تدمد: 1473-4877
0300-7995
URL الوصول: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::34d485421d2fcae4f327e9e2e1c3e031
https://doi.org/10.1080/03007995.2022.2101817
حقوق: OPEN
رقم الأكسشن: edsair.doi.dedup.....34d485421d2fcae4f327e9e2e1c3e031
قاعدة البيانات: OpenAIRE