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Validation of algorithms to ascertain clinical conditions and medical procedures used during pregnancy.

机译:验证算法确定妊娠期间使用的临床条件和医疗程序。

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PURPOSE: To evaluate the validity of health plan administrative and claims data to identify pre-gestational and gestational diabetes, obesity, and ultrasounds among pregnant women. METHODS: A retrospective study was conducted using the administrative and claims data of three health plans participating in the HMO Research Network. Diagnoses, drug dispensings, and procedure codes were used to identify diabetes, obesity, and ultrasounds among women who were pregnant between January 2006 and December 2008. A random sample of medical charts (n = 222) were abstracted. Positive predictive values (PPVs) were calculated. Sensitivity also was calculated for obesity among women for whom body mass index data were available in electronic medical records at two sites. RESULTS: Overall, 190 of 222 cases of diabetes (86%) were confirmed (82% for gestational diabetes and 74% for pre-gestational diabetes). The PPV for codes to identify ultrasounds was 80%. Whereas the PPV for obesity-related diagnosis codes was high (93%), and the sensitivity was low (33%). CONCLUSIONS: Health plan administrative and claims data can be used to accurately identify pre-gestational and gestational diabetes and ultrasounds. Obesity is not consistently coded.
机译:目的:评估卫生计划行政和索赔数据的有效性,以识别孕妇中的妊娠前和妊娠期糖尿病,肥胖症和超声波。方法:采用参与HMO研究网络的三个卫生计划的行政和索赔数据进行了回顾性研究。诊断,药物分配和程序代码用于鉴定2006年1月至2008年1月期间怀孕的糖尿病,肥胖症和超声波。抽象了一种随机的医学图表(n = 222)。计算阳性预测值(PPV)。对于两个地点的电子医疗记录中可用的妇女肥胖的肥胖而计算敏感性。结果:总体而言,190例患有190例糖尿病(86%)(86%)(妊娠期糖尿病82%,妊娠前糖尿病患者为74%)。用于识别超声波的代码的PPV为80%。虽然肥胖相关诊断码的PPV高(93%),敏感性低(33%)。结论:健康计划行政和索赔数据可用于准确识别妊娠前和妊娠期糖尿病和超声波。肥胖并不一致编码。

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