Laboratory of Clinical Pharmacy, Graduate School of Pharmaceutical Sciences, Tohoku University, Sendai 980-8574, Japan.
Division of Preventive Medicine and Epidemiology, Tohoku Medical Megabank Organization, Tohoku University, Sendai 980-8573, Japan.
Int J Environ Res Public Health. 2022 Apr 16;19(8):4864. doi: 10.3390/ijerph19084864.
This study aimed to develop and validate claims-based algorithms for identifying live birth, fetal death, and cesarean section by utilizing administrative data from a university hospital in Japan. We included women who visited the Department of Obstetrics at a university hospital in 2018. The diagnosis, medical procedures, and medication data were used to identify potential cases of live birth, fetal death, and cesarean section. By reviewing electronic medical records, we evaluated the positive predictive values (PPVs) and the accuracy of the end date of pregnancy for each claims datum. "Selected algorithm 1" based on PPVs and "selected algorithm 2" based on both the PPVs and the accuracy of the end date of pregnancy were developed. A total of 1757 women were included, and the mean age was 32.8 years. The PPVs of "selected algorithm 1" and "selected algorithm 2" were both 98.1% for live birth, 99.0% and 98.9% for fetal death, and 99.7% and 100.0% for cesarean section, respectively. These findings suggest that the developed algorithms are useful for future studies for evaluating live birth, fetal death, and cesarean section with an accurate end date of pregnancy.
本研究旨在利用日本某大学医院的管理数据开发和验证基于索赔的算法,以识别活产、胎儿死亡和剖宫产。我们纳入了 2018 年在某大学医院妇产科就诊的女性。使用诊断、医疗程序和药物数据来识别潜在的活产、胎儿死亡和剖宫产病例。通过审查电子病历,我们评估了每个索赔数据的阳性预测值(PPV)和妊娠期末的准确性。基于 PPV 开发了“选择算法 1”,基于 PPV 和妊娠期末的准确性开发了“选择算法 2”。共纳入 1757 名女性,平均年龄为 32.8 岁。“选择算法 1”和“选择算法 2”的活产 PPV 均为 98.1%,胎儿死亡的 PPV 分别为 99.0%和 98.9%,剖宫产的 PPV 分别为 99.7%和 100.0%。这些发现表明,开发的算法对于未来评估活产、胎儿死亡和剖宫产以及准确的妊娠期末日期的研究是有用的。