Lack of access to care, funding limitations, cultural, and social barriers are challenges specific to tribal communities that have led to adverse cancer outcomes among American Indians/Alaska Natives (AI/AN). While the cancer navigator model has been shown to be effective in other underserved communities, it has not been widely implemented in Indian Country. We conducted in-depth interviews with 40 AI/AN patients at tribal clinics in Idaho and Oregon. We developed the survey instrument in partnership with community members to ensure a culturally appropriate semi-structured questionnaire. Questions explored barriers to accessing care, perceptions of the navigator program, satisfaction, and recommendations. AI/AN cancer patients reported physical, emotional, financial, and transportation barriers to care, but most did not feel there were any cultural barriers to receiving care. Navigator services most commonly used included decision making, referrals, transportation, scheduling appointments, and communication. Satisfaction with the program was high. Our study provides a template to develop a culturally appropriate survey instrument for use with an AI/AN population, which could be adapted for use with other indigenous patient populations. Although our sample was small, our qualitative analysis facilitated a deeper understanding of the barriers faced by this population and how a navigator program may best address them. The results reveal the strengths and weakness of this program, and provide baseline patient satisfaction numbers which will allow future patient navigator programs to better create evaluation benchmarks.
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American Indians and Alaska Natives (AI/ANs) experience a high burden of mortality and other disparities compared with the general population. Life tables are an important population health indicator; however, federal agencies have not produced life tables for AI/ANs, largely due to racial misclassification on death certificates. Our objective was to correct this misclassification and create life tables for AI/ANs who resided in the Pacific Northwest region of the U.S., making comparisons with the general population.
To correct racial misclassification, we conducted probabilistic record linkages between death certificates from three Northwest states-Idaho, Oregon, and Washington State-issued during 2008-2010, and AI/AN patient registration records. We calculated mortality rates and generated period life tables for AI/ANs and non-Hispanic white (NHW) Americans.
Overall life expectancy at birth for Northwest AI/ANs was 72.8 years, which was 6.9 years lower than that of NHW Americans. Male AI/ANs had a lower life expectancy (70.9 years) than female AI/ANs (74.6 years). The disparity in life expectancy between AI/ANs and their NHW counterparts was higher for females (with AI/ANs living 7.3 years fewer than NHW females) than for males (with AI/ANs living 6.7 years fewer than NHW males). The greatest disparity in mortality rates was seen among young adults.
Data linkage with a registry of known AI/ANs allowed us to generate accurate life tables that had not previously been available for this population and revealed disparities in both life expectancy at birth and survival across the life span. These results represent an important tool to help AI/AN communities as they monitor their health and promote efforts to eliminate health disparities.
The objectives of this study were to evaluate racial misclassification in a statewide trauma registry and to describe the epidemiology of trauma among the Washington American Indian and Alaska Native (AI/AN) population.
We performed probabilistic record linkage between the Washington Trauma Registry (2005-2009) and Northwest Tribal Registry, a dataset of known AI/AN. AI/AN patients were compared with caucasians on demographic, injury and clinical outcome factors. A multivariable model estimated odds of mortality.
Record linkage increased ascertainment of AI/AN cases in the trauma registry 71%, from 1777 to 3039 cases. Compared with caucasians, AI/AN trauma patients were younger (mean age=36 vs 47 years, p15: 21.4% vs 20.5%, p=0.63), and no difference was observed in mortality after adjustment for covariates (p=0.58).
Linkage to a state trauma registry improved data quality by correcting racial misclassification, allowing for a comprehensive description of injury patterns for the AI/AN population. AI/AN sustained more severe injuries with similar postinjury outcomes to caucasians. Future efforts should focus on primary prevention for this population, including increased use of seat belts and child safety seats and reduction of interpersonal violence and suicide.
To evaluate and adjust for American Indian and Alaska Native (AI/AN) racial misclassification in two hospital discharge datasets in the Pacific Northwest.
Oregon (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.
Record 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.
Researchers used Link Plus 2.0 software (Atlanta, GA, USA) for linkages and SAS 9.4 (Cary, NC, USA) for statistical analyses.
In 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.
Correction 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.
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