Using Record Linkage to Improve Race Data Quality for American Indians and Alaska Natives in Two Pacific Northwest State Hospital Discharge Databases
Using Record Linkage to Improve Race Data Quality for American Indians and Alaska Natives in Two Pacific Northwest State Hospital Discharge Databases
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DOI：
10.1111/1475-6773.12331
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发表时间：
2015-08-01
影响因子：
3.4
通讯作者：
Weiser, Thomas
中科院分区：
文献类型：
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作者：
Bigback, Kristyn M.;Hoopes, Megan;Weiser, Thomas
目的评价和调整太平洋西北地区两家医院出院数据中美国印第安人和阿拉斯加原住民（AI/AN）种族错误分类。区域（2010-2011年）和华盛顿（2011年）的医院出院数据集与西北部落登记处（NTR）相关联，该登记处登记了在西北印第安人卫生设施获得服务的AI/AN个人。研究设计记录链接用于将州医院记录与NTR进行匹配。如果与NTR匹配并被编码为非ai /AN或缺少比赛数据，则认为状态记录被错误分类。通过比较关联前和关联后、年龄调整后的出院率来评估误分类的影响。数据收集/提取方法研究人员使用Link Plus 2.0软件（Atlanta， GA， USA）进行关联，使用SAS 9.4 （Cary， NC， USA）进行统计分析。在俄勒冈州，55.4%的匹配记录被错误分类（66.5%的匹配记录被错误编码为白人，22.1%的匹配记录缺少种族信息）。在华盛顿，44.9%的匹配记录被错误分类（61.8%被错误编码为白人，32.7%的人缺少种族信息）。这种联系使俄勒冈州和华盛顿州的AI/AN住院率分别提高了31.8%和33.9%。与非西班牙裔白人（NHW）相比，关联增加了AI/AN住院的比率（RR），俄勒冈州从0.81增加到1.07，华盛顿州从1.21增加到1.62。结论通过与已知AI/AN个体参考文件的链接对出院数据集中的种族进行校正是太平洋西北地区AI/AN卫生保健分析研究与行政数据集相结合的重要第一步。
ObjectiveTo evaluate and adjust for American Indian and Alaska Native (AI/AN) racial misclassification in two hospital discharge datasets in the Pacific Northwest.Data Sources/Study SettingOregon (2010-2011) and Washington (2011) hospital discharge datasets were linked with the Northwest Tribal Registry (NTR), a registry of AI/AN individuals who accessed services at Indian health facilities in the Northwest.Study DesignRecord linkage was used to match state hospital records to the NTR. A state record was considered misclassified if it matched the NTR and was coded as non-AI/AN or missing race data. Effect of misclassification was evaluated by comparing prelinkage and postlinkage, age-adjusted hospital discharge rates.Data Collection/Extraction MethodsResearchers used Link Plus 2.0 software (Atlanta, GA, USA) for linkages and SAS 9.4 (Cary, NC, USA) for statistical analyses.Principal FindingsIn Oregon, 55.4 percent of matching records were misclassified (66.5 percent miscoded white, and 22.1 percent were missing race information). In Washington, 44.9 percent of matching records were misclassified (61.8 percent miscoded white, and 32.7 percent were missing race information). Linkage increased ascertainment of AI/AN hospitalizations by 31.8 percent in Oregon and 33.9 percent in Washington. Linkage increased the rate ratio (RR) for AI/AN hospitalizations in comparison to non-Hispanic whites (NHW) from 0.81 to 1.07 in Oregon, and from 1.21 to 1.62 in Washington.ConclusionCorrection of race in hospital discharge datasets through linkage with a reference file of known AI/AN individuals is an important first step before analytic research on AI/AN health care in the Pacific Northwest can be accomplished with administrative datasets.