Why poor quality of ethnicity data should not preclude its use for identifying disparities in health and healthcare
Why poor quality of ethnicity data should not preclude its use for identifying disparities in health and healthcare
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DOI：
10.1136/qshc.2006.019059
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发表时间：
2007-06-01
影响因子：
--
通讯作者：
Jacobson, Bobbie
中科院分区：
文献类型：
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作者：
Aspinall, Peter J.;Jacobson, Bobbie
背景：需要高质量的数据来确定健康和保健方面的种族差异，并应对种族关系治理方面的挑战。目的：识别常规健康和保健数据集中种族数据的不完备性，并调查使用次优数据的分析策略的效用。方法：由政府办公室地区分析常规数据集中的种族数据不完备性，并全面回顾和评估关于适当分析策略的文献，以解决此类数据的使用。结果：关于健康和医疗保健的种族编码常规数据集的可用性有限，有效的种族编码具有很大的变异性：尽管少数具有较高的完整性水平，大多数是穷人(特别是医院事件统计数据、药物治疗数据和非医务人员)。此外，在质量上也存在两倍以上的地区差异。组织因素似乎是造成这种差异的主要因素，这些因素是可以改变的，但在实践中很难改变。本文讨论了使用质量不佳的数据的各种分析策略的优点和局限性，并探索了它们如何回答与种族不平等有关的重要悬而未决的问题。结论：只有通过使用数据，即使是质量不佳的数据，并保持接近它，医疗保健组织才能提高质量。
Background: Data of quality are needed to identify ethnic disparities in health and healthcare and to meet the challenges in governance of race relations. Yet concerns over completeness, accuracy and timeliness have been long-standing and inhibitive with respect to the analytical use of the data.Aims: To identify incompleteness of ethnicity data across routine health and healthcare datasets and to investigate the utility of analytical strategies for using data that is of suboptimal quality.Methods: An analysis by government office regions of ethnicity data incompleteness in routine datasets and a comprehensive review and evaluation of the literature on appropriate analytical strategies to address the use of such data.Results: There is only limited availability of ethnically coded routine datasets on health and healthcare, with substantial variability in valid ethnic coding: although a few have high levels of completeness, the majority are poor (notably hospital episode statistics, drug treatment data and non-medical workforce). In addition, there is also a more than twofold regional difference in quality. Organisational factors seem to be the main contributor to the differentials, and these are amenable-yet, in practice, difficult-to change. This article discusses the strengths and limitations of a variety of analytical strategies for using data of suboptimal quality and explores how they may answer important unresolved questions in relation to ethnic inequalities.Conclusions: Only by using the data, even when of suboptimal quality, and remaining close to it can healthcare organisations drive up quality.