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利用临床信息提高质量测量:以儿童服用第二代抗精神病药物后体重指数变化为例。

Enhancing Quality Measurement With Clinical Information: A Use Case of Body Mass Index Change Among Children Taking Second Generation Antipsychotics.

机构信息

Department of Health Outcomes and Biomedical Informatics, College of Medicine, University of Florida (T Huo, Q Li, MI Cardel, DJ Lemas, H Xu, J Woodard, KE Muller, and EA Shenkman), Gainesville, Fla.

Department of Health Outcomes and Biomedical Informatics, College of Medicine, University of Florida (T Huo, Q Li, MI Cardel, DJ Lemas, H Xu, J Woodard, KE Muller, and EA Shenkman), Gainesville, Fla.

出版信息

Acad Pediatr. 2022 Apr;22(3S):S140-S149. doi: 10.1016/j.acap.2021.11.012.

Abstract

OBJECTIVE

We sought to examine the extent to which body mass index (BMI) was available in electronic health records for Florida Medicaid recipients aged 5 to 18 years taking Second-Generation Antipsychotics (SGAP). We also sought to illustrate how clinical data can be used to identify children most at-risk for SGAP-induced weight gain, which cannot be done using process-focused measures.

METHODS

Electronic health record (EHR) data and Medicaid claims were linked from 2013 to 2019. We quantified sociodemographic differences between children with and without pre- and post-BMI values. We developed a linear regression model of post-BMI to examine pre-post changes in BMI among 4 groups: 1) BH/SGAP+ children had behavioral health conditions and were taking SGAP; 2) BH/SGAP- children had behavioral health conditions without taking SGAP; 3) children with asthma; and 4) healthy children.

RESULTS

Of 363,360 EHR-Medicaid linked children, 18,726 were BH/SGAP+. Roughly 4% of linked children and 8% of BH/SGAP+ children had both pre and post values of BMI required to assess quality of SGAP monitoring. The percentage varied with gender and race-ethnicity. The R for the regression model with all predictors was 0.865. Pre-post change in BMI differed significantly (P < .0001) among the groups, with more BMI gain among those taking SGAP, particularly those with higher baseline BMI.

CONCLUSION

Meeting the 2030 Centers for Medicare and Medicaid Services goal of digital monitoring of quality of care will require continuing expansion of clinical encounter data capture to provide the data needed for digital quality monitoring. Using linked EHR and claims data allows identifying children at higher risk for SGAP-induced weight gain.

摘要

目的

我们旨在研究在接受第二代抗精神病药物(SGAP)的 5 至 18 岁佛罗里达州医疗补助受助人的电子健康记录中,体重指数(BMI)的可用性程度。我们还试图说明如何使用临床数据来识别最有可能因 SGAP 引起体重增加的儿童,而这是无法通过关注过程的措施来完成的。

方法

从 2013 年到 2019 年,将电子健康记录(EHR)数据和医疗补助索赔进行了关联。我们量化了有和没有 BMI 值的儿童之间在社会人口统计学方面的差异。我们开发了一个 BMI 的线性回归模型,以检查 4 组儿童的 BMI 前后变化:1)BH/SGAP+ 儿童有行为健康问题并正在服用 SGAP;2)BH/SGAP- 儿童有行为健康问题但未服用 SGAP;3)患有哮喘的儿童;4)健康儿童。

结果

在 363360 名 EHR 医疗补助关联儿童中,有 18726 名是 BH/SGAP+。大约 4%的关联儿童和 8%的 BH/SGAP+儿童都有 BMI 的前后值,以评估 SGAP 监测的质量。该百分比随性别和种族而异。带有所有预测因子的回归模型的 R 值为 0.865。BMI 的前后变化在各组之间存在显著差异(P<0.0001),服用 SGAP 的儿童的 BMI 增加更多,尤其是那些基线 BMI 较高的儿童。

结论

要实现 2030 年医疗保险和医疗补助服务中心(Centers for Medicare and Medicaid Services)的数字监测医疗质量目标,将需要继续扩大临床接触数据的捕获范围,以提供数字质量监测所需的数据。使用关联的 EHR 和索赔数据可以识别出因 SGAP 引起体重增加风险较高的儿童。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b811/9092621/7ae5884fb2aa/nihms-1795600-f0001.jpg

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