Anthony Mary S, Armstrong Mary Anne, Getahun Darios, Scholes Delia, Gatz Jennifer, Schulze-Rath Renate, Postlethwaite Debbie, Merchant Maqdooda, Alabaster Amy L, Chillemi Giulia, Raine-Bennett Tina, Xie Fagen, Chiu Vicki Y, Im Theresa M, Takhar Harpreet S, Fassett Michael, Grafton Jane, Cronkite David, Ichikawa Laura, Reed Susan D, Hui Siu Lui, Ritchey Mary E, Saltus Catherine W, Andrews Elizabeth B, Rothman Kenneth J, Asiimwe Alex, Lynen Richard, Schoendorf Juliane
RTI Health Solutions , Research Triangle Park, NC, USA.
Kaiser Permanente Northern California , Oakland, CA, USA.
Clin Epidemiol. 2019 Jul 23;11:635-643. doi: 10.2147/CLEP.S201044. eCollection 2019.
To validate algorithms identifying uterine perforations and intrauterine device (IUD) expulsions and to ascertain availability of breastfeeding status at the time of IUD insertion.
Four health care systems with electronic health records (EHRs) participated: Kaiser Permanente Northern California (KPNC), Kaiser Permanente Southern California (KPSC), Kaiser Permanente Washington (KPWA), and Regenstrief Institute (RI). The study included women ≤50 years of age with an IUD insertion. Site-specific algorithms using structured and unstructured data were developed and a sample validated by EHR review. Positive predictive values (PPVs) of the algorithms were calculated. Breastfeeding status was assessed in a random sample of 125 women at each research site with IUD placement within 52 weeks postpartum.
The study population included 282,028 women with 325,582 IUD insertions. The PPVs for uterine perforation were KPNC 77%, KPSC 81%, KPWA 82%, and RI 47%; PPVs for IUD expulsion were KPNC 77%, KPSC 87%, KPWA 68%, and RI 37%. Across all research sites, breastfeeding status at the time of IUD insertion was determined for 94% of those sampled.
Algorithms with a high PPV for uterine perforation and IUD expulsion were developed at 3 of the 4 research sites. Breastfeeding status at the time of IUD insertion could be determined at all research sites. Our findings suggest that a study to evaluate the associations of breastfeeding and postpartum IUD insertions with risk of uterine perforation and IUD expulsion can be successfully conducted retrospectively; however, automated application of algorithms must be supplemented with chart review for some outcomes at one research site due to low PPV.
验证识别子宫穿孔和宫内节育器（IUD）脱落的算法，并确定放置IUD时母乳喂养状况的可得性。
四个拥有电子健康记录（EHRs）的医疗保健系统参与了研究：北加利福尼亚凯撒医疗集团（KPNC）、南加利福尼亚凯撒医疗集团（KPSC）、华盛顿凯撒医疗集团（KPWA）和雷根斯特里夫研究所（RI）。研究纳入了年龄≤50岁且放置了IUD的女性。利用结构化和非结构化数据开发了特定地点的算法，并通过EHR审查对一个样本进行了验证。计算了算法的阳性预测值（PPV）。在每个研究地点，对产后52周内放置IUD的125名女性的随机样本进行了母乳喂养状况评估。
研究人群包括282,028名女性，共放置了325,582个IUD。子宫穿孔的PPV分别为：KPNC 77%、KPSC 81%、KPWA 82%、RI 47%；IUD脱落的PPV分别为：KPNC 77%、KPSC 87%、KPWA 68%、RI 37%。在所有研究地点，94%的抽样对象的IUD放置时的母乳喂养状况得以确定。
四个研究地点中的三个开发出了对子宫穿孔和IUD脱落具有高PPV的算法。所有研究地点均可确定IUD放置时的母乳喂养状况。我们的研究结果表明，一项评估母乳喂养和产后IUD放置与子宫穿孔及IUD脱落风险之间关联的研究可以成功地进行回顾性研究；然而，由于PPV较低，在一个研究地点，对于某些结果，算法的自动应用必须辅以图表审查。
