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一般实践研究数据库中的妊娠识别。

The identification of pregnancies within the general practice research database.

机构信息

University of NC School of Public Health, Chapel Hill, NC, USA.

出版信息

Pharmacoepidemiol Drug Saf. 2010 Jan;19(1):45-50. doi: 10.1002/pds.1862.

DOI:10.1002/pds.1862
PMID:19823973
Abstract

BACKGROUND

The United States is moving toward active drug safety surveillance using sources such as administrative claims and electronic medical records, but use of these data for studying teratogenicity has been challenging, as they typically do not allow for the easy identification of pregnancies. Our goal was to develop and validate an algorithm for the identification of pregnancies in the general practice research database (GPRD) that could be used to study pregnancy outcomes.

METHODS

The algorithm identified pregnancies in women 15-45-year-old that were pregnant between 1 January 1987 and 31 December 2006. We identified live births, stillbirths, and spontaneous and elective terminations within a woman's record. We validated the algorithm using the additional clinical details maternity (ACDM) file and de-identified free-text records.

RESULTS

We analyzed 16,035,394 records from 3,093,927 individuals and identified 383,184 women who had a total of 580,356 pregnancies. There were 415,221 full-term live births, 3080 pre- or post-term births, 1834 multi-fetus deliveries, 86,408 spontaneous abortions or miscarriages, 72 164 elective terminations, and 1649 stillbirths or fetal deaths. A marker of pregnancy care was identifiable for 86.3% of the 580,356 pregnancies. The internal validation steps indicated that the algorithm produced consistent results with the ACDM file.

CONCLUSIONS

We were successful in identifying a large number of pregnancies in the GPRD. Our use of a hierarchical approach to identify pregnancy outcomes builds upon the methods suggested in previous work, while implementing additional steps to minimize potential misclassification of pregnancy outcomes.

摘要

背景

美国正在转向使用行政索赔和电子病历等来源进行主动药物安全监测,但由于这些数据通常无法轻易识别妊娠,因此将其用于研究致畸性一直具有挑战性。我们的目标是开发和验证一种可用于研究妊娠结局的一般实践研究数据库(GPRD)中妊娠的识别算法。

方法

该算法识别了年龄在 15-45 岁之间、1987 年 1 月 1 日至 2006 年 12 月 31 日期间妊娠的女性的妊娠情况。我们在女性的记录中确定了活产、死产以及自然和选择性足月终止妊娠的情况。我们使用附加临床详细信息产妇(ACDM)文件和去识别的自由文本记录验证了该算法。

结果

我们分析了来自 3093927 个人的 16035394 条记录,确定了 383184 名女性,她们总共经历了 580356 次妊娠。其中有 415221 次足月活产,3080 次早产或过期产,1834 次多胎分娩,86408 次自然流产或流产,72164 次选择性终止妊娠,1649 次死产或胎儿死亡。580356 次妊娠中有 86.3%可识别妊娠护理的标记。内部验证步骤表明,该算法与 ACDM 文件产生的结果一致。

结论

我们成功地在 GPRD 中识别出了大量妊娠。我们使用分层方法来识别妊娠结局,这是对以前工作中提出的方法的扩展,同时实施了其他步骤来最小化妊娠结局的潜在分类错误。

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