利用联合索赔和临床数据集研究罕见病的潜在病例。

Pub Date : 2018-01-01 DOI:10.4018/ijhisi.2018040101
Kevin J Bennett, Joshua Mann, Lijing Ouyang
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引用次数: 8

摘要

考虑到行政索赔和医学衍生数据集的数据质量问题,从多种来源组合衍生的数据集可能更有效地用于研究。本文的目的是将基于电子病历的数据仓库与国家管理数据联系起来,以研究罕见病个体;描述:描述和比较它们的特征;并利用数据探索研究。这些方法纳入2009-2014年间具有三种罕见病诊断代码之一的受试者;脊柱裂、肌肉萎缩症和脆性X综合征。组合数据的结果提供了每个数据集本身不包含的附加信息。在合并的数据集中,可以同时检查种族/民族、医生和其他门诊就诊数据、收费和支付以及总体利用率等数据。还讨论了将这些数据集结合起来可以成为研究罕见疾病人群的有用工具。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

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Utilizing Combined Claims and Clinical Datasets for Research Among Potential Cases of Rare Diseases.

With data quality issues with administrative claims and medically derived datasets, a dataset derived from a combination of sources may be more effective for research. The purposes of this article is to link an EMR-based data warehouse with state administrative data to study individuals with rare diseases; to describe and compare their characteristics; and to explore research with the data. These methods included subjects with diagnosis codes for one of three rare diseases from the years 2009-2014; Spina Bifida, Muscular Dystrophy, and Fragile X Syndrome. The results from the combined data provides additional information that each dataset, by itself, would not contain. The simultaneous examination of data such as race/ethnicity, physician and other outpatient visit data, charges and payments, and overall utilization was possible in the combined dataset. It is also discussed that combining such datasets can be a useful tool for the study of populations with rare diseases.

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