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Racial Misclassification of American Indians and Alaska Natives by Indian Health Service Contract Health Service Delivery Area

机译:通过印度卫生服务合同卫生服务提供地区对美洲印第安人和阿拉斯加原住民的种族分类错误

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Objectives. We evaluated the racial misclassification of American Indians and Alaska Natives (AI/ANs) in cancer incidence and all-cause mortality data by Indian Health Service (IHS) Contract Health Service Delivery Area (CHSDA). Methods. We evaluated data from 3 sources: IHS-National Vital Statistics System (NVSS), IHS-National Program of Cancer Registries (NPCR)/Surveillance, Epidemiology and End Results (SEER) program, and National Longitudinal Mortality Study (NLMS). We calculated, within each data source, the sensitivity and classification ratios by sex, IHS region, and urban–rural classification by CHSDA county. Results. Sensitivity was significantly greater in CHSDA counties (IHS-NVSS: 83.6%; IHS-NPCR/SEER: 77.6%; NLMS: 68.8%) than non-CHSDA counties (IHS-NVSS: 54.8%; IHS-NPCR/SEER: 39.0%; NLMS: 28.3%). Classification ratios indicated less misclassification in CHSDA counties (IHS-NVSS: 1.20%; IHS-NPCR/SEER: 1.29%; NLMS: 1.18%) than non-CHSDA counties (IHS-NVSS: 1.82%; IHS-NPCR/SEER: 2.56%; NLMS: 1.81%). Race misclassification was less in rural counties and in regions with the greatest concentrations of AI/AN persons (Alaska, Southwest, and Northern Plains). Conclusions. Limiting presentation and analysis to CHSDA counties helped mitigate the effects of race misclassification of AI/AN persons, although a portion of the population was excluded. Accurate determinations of disease and mortality are a critical first step toward addressing disease burden and health disparities. American Indian/Alaska Native (AI/AN) populations experience some of the greatest health disparities in the country compared with other racial and ethnic groups. 1–3 Health and mortality status assessments for AI/AN populations are often hindered by a lack of complete and accurate data on race and ethnicity in surveillance and vital statistics systems. AI/AN populations are more likely to be misclassified as another race than other racial groups in cancer registries, resulting in underestimates of cancer incidence. 4–10 Similarly, misclassification of AI/AN race is a common problem on death certificates, 11–18 on which ascertainment of race is usually provided by a funeral director. As a result, mortality estimates for the AI/AN population in the United States have been significantly underestimated. 13 A study of racial/ethnic misclassification on US death certificates, which compared self-identified race from the US Census Bureau’s Current Population Survey (CPS) to the race recorded on death certificates for a sample of decedents in the National Longitudinal Mortality Study (NLMS) database, found markedly higher race misclassification of AI/AN persons (30%) compared with persons of other races that varied substantially by degree of geographic co-ethnic concentration. 13 For example, AI/AN decedents who died in counties with high concentrations of AI/AN populations were significantly more likely to be classified correctly on death certificates than those who died outside of these counties. 13 Similarly, a study comparing the National Cancer Institute’s (NCI) Surveillance, Epidemiology, and End Results (SEER) Program with NLMS found that SEER data considerably underreported AI/AN persons. 19 A project matching Indian Health Service (IHS) patient registration records with the National Death Index (NDI) records of persons who died from 1986 to 1988 showed that the percentage of inconsistent classifications of AI/AN race varied from 1.2% in the Navajo IHS Area to 30.4% in the California IHS Area. 20 The IHS provides primary health care to approximately 2.2 million enrolled members of federally recognized tribes, a number equivalent to approximately 64% of the United States estimated 3.4 million AI/AN population. 21,22 Health care services for AI/AN individuals are provided in more than 670 IHS and tribal health care facilities, mostly in rural and isolated areas. 23 Eligible AI/AN persons can receive health care at any IHS facility, but complex rules govern and restrict the delivery of contract health services for specialty medical care that is not available at IHS facilities. 24 One eligibility requirement for contract health services is residence within the Contract Health Service Delivery Area (CHSDA) of the tribe in which the patient is enrolled. The geographic composition of the CHSDAs follows county boundaries and is established for each federally recognized tribe by the IHS. 25 Details of the IHS regions (Northern Plains, Alaska, Southern Plains, Pacific Coast, East, and Southwest) and CHSDA areas are provided elsewhere 26 and shown in Figure A (available as a supplement to the online version of this article at http://www.ajph.org ). Record linkages with IHS patient enrollment data are 1 method for addressing misclassification of AI/AN race in central cancer registries and in vital statistics mortality data; such linkages have been found to be both timely and cost effective. 8,26–29 An additional method to reduce the impact of r
机译:目标。我们通过印第安人健康服务(IHS)合同健康服务提供地区(CHSDA)评估了美洲印第安人和阿拉斯加原住民(AI / AN)在癌症发病率和全因死亡率数据中的种族错误分类。方法。我们评估了3个来源的数据:IHS国家生命统计系统(NVSS),IHS国家癌症登记计划(NPCR)/监视,流行病学和最终结果(SEER)计划以及国家纵向死亡率研究(NLMS)。我们在每个数据源中计算了按性别,IHS地区以及CHSDA县进行的城乡分类的敏感性和分类比率。结果。 CHSDA县(IHS-NVSS:83.6%; IHS-NPCR / SEER:77.6%; NLMS:68.8%)的敏感性显着高于非CHSDA县(IHS-NVSS:54.8%; IHS-NPCR / SEER:39.0%) ; NLMS:28.3%)。分类比率显示,与非CHSDA县(IHS-NVSS:1.82%; IHS-NPCR / SEER:2.56)相比,CHSDA县(IHS-NVSS:1.20%; IHS-NPCR / SEER:1.29%; NLMS:1.18%)的错误分类更少%; NLMS:1.81%)。在农村县和AI / AN人员最集中的地区(阿拉斯加,西南和北部平原),种族分类错误较少。结论。尽管仅一部分人口被排除在外,但仅限于CHSDA县的展示和分析有助于减轻AI / AN人员种族分类错误的影响。准确确定疾病和死亡率是解决疾病负担和健康差异的关键的第一步。与其他种族和民族相比,美洲印第安人/阿拉斯加原住民(AI / AN)人口在该国遇到一些最大的健康差异。 1-3对AI / AN人群进行健康和死亡率状况评估通常会因缺乏监视和生命统计系统中有关种族和种族的完整而准确的数据而受到阻碍。与癌症登记处的其他种族群体相比,AI / AN人群更有可能被误认为另一个种族,从而导致对癌症发生率的低估。 4–10同样,AI / AN种族的错误分类是死亡证明上的常见问题,11–18通常由which仪馆长确定种族。结果,美国AI / AN人群的死亡率估计值被大大低估了。 13一项针对美国死亡证明书的种族/种族错误分类研究,该研究比较了美国人口普查局当前人口调查(CPS)的自我识别种族与国家纵向死亡率研究(NLMS)中死者样本中的死亡证明记录的种族。 )数据库,发现与其他种族的人相比,AI / AN人的种族错误分类显着更高(30%),而其他种族的人在地理上共同种族集中度的差异也很大。 13例如,在AI / AN人口高度集中的县中死亡的AI / AN后裔比在这些县以外死亡的人更有可能在死亡证明上正确分类。 13同样,一项将美国国家癌症研究所(NCI)的监测,流行病学和最终结果(SEER)计划与NLMS进行比较的研究发现,SEER数据严重低估了AI / AN患者。 19将印度卫生局(IHS)病人登记记录与1986年至1988年死亡的人的国家死亡指数(NDI)记录相匹配的项目显示,AI / AN种族分类不一致的百分比在纳瓦霍IHS中为1.2%加州IHS区域的面积增加到30.4%。 20 IHS为大约220万联邦认可部落的已注册成员提供初级医疗保健,这一数字大约相当于美国估计的AI / AN人口340万的约64%。 21,22超过670个IHS和部落医疗机构(主要在农村和偏远地区)为AI / AN个人提供了医疗服务。 23合格的AI / AN人员可以在任何IHS设施中获得医疗保健,但是复杂的规则控制并限制了IHS设施无法提供的专项医疗保健合同医疗服务的交付。 24合同医疗服务的一项资格要求是居住在患者所在部落的合同医疗服务提供区(CHSDA)中。 CHSDA的地理组成遵循县边界,并由IHS为每个联邦认可的部落确定。 25其他地方提供了IHS区域(北部平原,阿拉斯加,南部平原,太平洋海岸,东部和西南)和CHSDA区域的详细信息,这些区域在其他地方提供26并显示在图A中(可作为http://www.ibm.com/en/us/en/en/en/en/us/en/en/en/en/en/en/en/http://www.microsoft.com/en/us/en/us/en/en/en/en/en/en/en/en/en_en_en_en_en_en_en_en_en_en.aspx作为本文的在线版本的补充)。 //www.ajph.org)。与IHS患者入院数据的记录联系是解决中央癌症登记处和生命统计死亡率数据中AI / AN种族分类错误的一种方法。已经发现这种联系既及时又具有成本效益。 8,26–29减少r影响的另一种方法

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