Examining Race and Ethnicity Information in Medicare Administrative Data
Examining Race and Ethnicity Information in Medicare Administrative Data
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DOI：
10.1097/mlr.0000000000000608
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发表时间：
2017-12-01
期刊：
影响因子：
3
通讯作者：
Joynt, Karen E.
中科院分区：
文献类型：
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作者：
Filice, Clara E.;Joynt, Karen E.
医疗保险受益人的健康状况和健康结果存在种族和民族差异。减少这些差异是国家的首要任务，而拥有有关个人种族和民族的高质量数据对于研究人员来说至关重要。然而，使用医疗保险数据来识别种族和民族并不简单。目前，医疗保险很大程度上依赖社会保障管理局的数据来获取有关医疗保险受益人种族和民族的信息。直接自我报告的种族和民族信息是针对 Medicare 受益人的子集收集的，但不是为了在 Medicare 管理记录中填充种族/民族信息而明确收集的。由于历史数据收集实践的原因，医疗保险有关种族和族裔的管理数据的质量因种族/族裔群体的不同而存在很大差异；白人和黑人的数据通常比其他种族/族裔群体的数据准确得多。通过使用最近应用于医疗保险管理数据库的估算算法，西班牙裔和亚洲/太平洋岛民受益人的识别得到了改进。为了提高医疗保险受益人种族/民族数据的准确性，研究人员开发了地理编码和姓氏分析等技术，间接分配医疗保险受益人的种族和民族。然而，这些技术相对较新，数据可能无法广泛获得。了解识别种族和族裔的不同方法的优点和局限性将有助于研究人员选择适合其特定目的的最佳方法，并帮助政策制定者解释使用这些措施的研究。
Racial and ethnic disparities are observed in the health status and health outcomes of Medicare beneficiaries. Reducing these disparities is a national priority, and having high-quality data on individuals' race and ethnicity is critical for researchers working to do so. However, using Medicare data to identify race and ethnicity is not straightforward. Currently, Medicare largely relies on Social Security Administration data for information about Medicare beneficiary race and ethnicity. Directly self-reported race and ethnicity information is collected for subsets of Medicare beneficiaries but is not explicitly collected for the purpose of populating race/ethnicity information in the Medicare administrative record. As a consequence of historical data collection practices, the quality of Medicare's administrative data on race and ethnicity varies substantially by racial/ethnic group; the data are generally much more accurate for whites and blacks than for other racial/ethnic groups. Identification of Hispanic and Asian/Pacific Islander beneficiaries has improved through use of an imputation algorithm recently applied to the Medicare administrative database. To improve the accuracy of race/ethnicity data for Medicare beneficiaries, researchers have developed techniques such as geocoding and surname analysis that indirectly assign Medicare beneficiary race and ethnicity. However, these techniques are relatively new and data may not be widely available. Understanding the strengths and limitations of different approaches to identifying race and ethnicity will help researchers choose the best method for their particular purpose, and help policymakers interpret studies using these measures.