COVID-19 Among American Indian and Alaska Native Persons - 23 States, January 31-July 3, 2020.

Although non-Hispanic American Indian and Alaska Native (AI/AN) persons account for 0.7% of the U.S. population,* a recent analysis reported that 1.3% of coronavirus disease 2019 (COVID-19) cases reported to CDC with known race and ethnicity were among AI/AN persons (1). To assess the impact of COVID-19 among the AI/AN population, reports of laboratory-confirmed COVID-19 cases during January 22†-July 3, 2020 were analyzed. The analysis was limited to 23 states§ with >70% complete race/ethnicity information and five or more laboratory-confirmed COVID-19 cases among both AI/AN persons (alone or in combination with other races and ethnicities) and non-Hispanic white (white) persons. Among 424,899 COVID-19 cases reported by these states, 340,059 (80%) had complete race/ethnicity information; among these 340,059 cases, 9,072 (2.7%) occurred among AI/AN persons, and 138,960 (40.9%) among white persons. Among 340,059 cases with complete patient race/ethnicity data, the cumulative incidence among AI/AN persons in these 23 states was 594 per 100,000 AI/AN population (95% confidence interval [CI] = 203-1,740), compared with 169 per 100,000 white population (95% CI = 137-209) (rate ratio [RR] = 3.5; 95% CI = 1.2-10.1). AI/AN persons with COVID-19 were younger (median age = 40 years; interquartile range [IQR] = 26-56 years) than were white persons (median age = 51 years; IQR = 32-67 years). More complete case report data and timely, culturally responsive, and evidence-based public health efforts that leverage the strengths of AI/AN communities are needed to decrease COVID-19 transmission and improve patient outcomes.

COVID-19 Mortality Among American Indian and Alaska Native Persons - 14 States, January-June 2020.

American Indian/Alaska Native (AI/AN) persons experienced disproportionate mortality during the 2009 influenza A(H1N1) pandemic (1,2). Concerns of a similar trend during the coronavirus disease 2019 (COVID-19) pandemic led to the formation of a workgroup* to assess the prevalence of COVID-19 deaths in the AI/AN population. As of December 2, 2020, CDC has reported 2,689 COVID-19-associated deaths among non-Hispanic AI/AN persons in the United States.† A recent analysis found that the cumulative incidence of laboratory-confirmed COVID-19 cases among AI/AN persons was 3.5 times that among White persons (3). Among 14 participating states, the age-adjusted AI/AN COVID-19 mortality rate (55.8 deaths per 100,000; 95% confidence interval [CI] = 52.5-59.3) was 1.8 (95% CI = 1.7-2.0) times that among White persons (30.3 deaths per 100,000; 95% CI = 29.9-30.7). Although COVID-19 mortality rates increased with age among both AI/AN and White persons, the disparity was largest among those aged 20-49 years. Among persons aged 20-29 years, 30-39 years, and 40-49 years, the COVID-19 mortality rates among AI/AN were 10.5, 11.6, and 8.2 times, respectively, those among White persons. Evidence that AI/AN communities might be at increased risk for COVID-19 illness and death demonstrates the importance of documenting and understanding the reasons for these disparities while developing collaborative approaches with federal, state, municipal, and tribal agencies to minimize the impact of COVID-19 on AI/AN communities. Together, public health partners can plan for medical countermeasures and prevention activities for AI/AN communities.

Identification of American Indians and Alaska Natives in Public Health Data Sets: A Comparison Using Linkage-Corrected Washington State Death Certificates.

CONTEXT: Efforts to address disparities experienced by American Indians/Alaska Natives (AI/ANs) have been hampered by a lack of accurate and timely health data. One challenge to obtaining accurate data is determining who "counts" as AI/AN in health and administrative data sets. OBJECTIVE: To compare the effects of definition and misclassification of AI/AN on estimates of all-cause and cause-specific mortality for AI/AN in Washington during 2015-2016. DESIGN: Secondary analysis of death certificate data from Washington State. Data were corrected for AI/AN racial misclassification through probabilistic linkage with the Northwest Tribal Registry. Counts and age-adjusted rates were calculated and compared for 6 definitions of AI/AN. Comparisons were made with the non-Hispanic white population to identify disparities. SETTING: Washington State. PARTICIPANTS: AI/AN and non-Hispanic white residents of Washington State who died in 2015 and 2016. MAIN OUTCOME MEASURES: Counts and age-adjusted rates for all-cause mortality and mortality from cardiovascular diseases, cancer, and unintentional injuries. RESULTS: The most conservative single-race definition of AI/AN identified 1502 AI/AN deaths in Washington State during 2015-2016. The least conservative multiple-race definition of AI/AN identified 2473 AI/AN deaths, with an age-adjusted mortality rate that was 48% higher than the most conservative definition. Correcting misclassified AI/AN records through probabilistic linkage significantly increased mortality rate estimates by 11%. Regardless of definition used, AI/AN in Washington had significantly higher all-cause mortality rates than non-Hispanic whites in the state. CONCLUSIONS: Reporting single-race versus multiple-race AI/AN had the most consequential effect on mortality counts and rates. Correction of misclassified AI/AN records resulted in small but statistically significant increases in AI/AN mortality rates. Researchers and practitioners should consult with AI/AN communities on the complex issues surrounding AI/AN identity to obtain the best method for identifying AI/AN in health data sets.

Drug, Opioid-Involved, and Heroin-Involved Overdose Deaths Among American Indians and Alaska Natives - Washington, 1999-2015.

The opioid epidemic has resulted in a threefold increase in drug overdose deaths in the United States during 1999-2015 (1). Whereas American Indians/Alaska Natives (AI/AN) have experienced larger increases in drug overdose mortality than have other racial/ethnic groups in the United States (2), little is known about the regional impact of opioids in tribal and urban AI/AN communities. To address this data gap, death records from the Washington State Center for Health Statistics, corrected for misclassification of AI/AN race, were examined to identify trends and disparities in drug, opioid-involved, and heroin-involved overdose mortality rates for AI/AN and non-Hispanic whites (whites) in Washington. Although AI/AN and whites had similar overdose mortality rates during 1999-2001, subsequent overdose rates among AI/AN increased at a faster rate than did those among whites. During 2013-2015, mortality rates among AI/AN were 2.7 and 4.1 times higher than rates among whites for total drug and opioid-involved overdoses and heroin-involved overdoses, respectively. Washington death certificates that were not corrected for misclassification of AI/AN race underestimated drug overdose mortality rates among AI/AN by approximately 40%. National statistics on the opioid epidemic, which report that overdose mortality rates are significantly higher among whites than among AI/AN, are not reflective of regional prevalences, disparities, and trends. Comprehensive efforts to address the opioid epidemic in AI/AN communities rely on strong partnerships between tribal governments and local, state, and federal entities. Additional measures are needed for community-based surveillance, treatment, and prevention to effectively respond to the epidemic across diverse tribal and urban AI/AN communities.

Relation of comorbidities and patient navigation with the time to diagnostic resolution after abnormal cancer screening.

BACKGROUND: Whether patient navigation improves outcomes for patients with comorbidities is unknown. The aims of this study were to determine the effect of comorbidities on the time to diagnostic resolution after an abnormal cancer screening test and to examine whether patient navigation improves the timeliness and likelihood of diagnostic resolution for patients with comorbidities in comparison with no navigation. METHODS: A secondary analysis of comorbidity data collected by Patient Navigation Research Program sites using the Charlson Comorbidity Index (CCI) was conducted. The participants were 6,349 patients with abnormal breast, cervical, colon, or prostate cancer screening tests between 2007 and 2011. The intervention was patient navigation or usual care. The CCI data were highly skewed across projects and cancer sites, and the CCI scores were categorized as 0 (CCI score of 0 or no comorbidities identified; 76% of cases); 1 (CCI score of 1; 16% of cases), or 2 (CCI score ≥ 2; 8% of cases). Separate adjusted hazard ratios for each site and cancer type were obtained, and then they were pooled with a meta-analysis random effects methodology. RESULTS: Patients with a CCI score ≥ 2 had delayed diagnostic resolution after an abnormal cancer screening test in comparison with those with no comorbidities. Patient navigation reduced delays in diagnostic resolution, with the greatest benefits seen for those with a CCI score ≥ 2. CONCLUSIONS: Persons with a CCI score ≥ 2 experienced significant delays in timely diagnostic care in comparison with patients without comorbidities. Patient navigation was effective in reducing delays in diagnostic resolution among those with CCI scores > 1. Cancer 2017;123:312-318. © 2016 American Cancer Society.

American Indian and Alaska Native Cancer Patients' Perceptions of a Culturally Specific Patient Navigator Program.

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.

The impact of patient navigation on the delivery of diagnostic breast cancer care in the National Patient Navigation Research Program: a prospective meta-analysis.

Patient navigation is emerging as a standard in breast cancer care delivery, yet multi-site data on the impact of navigation at reducing delays along the continuum of care are lacking. The purpose of this study was to determine the effect of navigation on reaching diagnostic resolution at specific time points after an abnormal breast cancer screening test among a national sample. A prospective meta-analysis estimated the adjusted odds of achieving timely diagnostic resolution at 60, 180, and 365 days. Exploratory analyses were conducted on the pooled sample to identify which groups had the most benefit from navigation. Clinics from six medical centers serving vulnerable populations participated in the Patient Navigation Research Program. Women with an abnormal breast cancer screening test between 2007 and 2009 were included and received the patient navigation intervention or usual care. Patient navigators worked with patients and their care providers to address patient-specific barriers to care to prevent delays in diagnosis. A total of 4675 participants included predominantly racial/ethnic minorities (74 %) with public insurance (40 %) or no insurance (31 %). At 60 days and 180 days, there was no statistically significant effect of navigation on achieving timely diagnostic care, but a benefit of navigation was seen at 365 days (aOR 2.12, CI 1.36-3.29). We found an equal benefit of navigation across all groups, regardless of race/ethnicity, language, insurance status, and type of screening abnormality. Patient navigation resulted in more timely diagnostic resolution at 365 days among a diverse group of minority, low-income women with breast cancer screening abnormalities. Trial registrations clinicaltrials.gov Identifiers: NCT00613275, NCT00496678, NCT00375024, NCT01569672.

Effect of patient navigation on satisfaction with cancer-related care.

PURPOSE: Despite growing popularity of patient navigation (PN) as a means to improve cancer care quality and reduce cancer-related disparities, there are few well-designed controlled trials assessing the impact of PN on patient outcomes like satisfaction with care. The present controlled study examined effect of PN on satisfaction with cancer-related care. METHODS: Patients who presented with a symptom or abnormal screening test (n = 1788) or definitive diagnosis (n = 445) of breast, cervical, colorectal, or prostate cancer from eight Patient Navigator Research Program sites were included in one of two groups: intervention (PN) or comparison (usual care or usual care plus cancer educational materials). Trained patient navigators met with intervention group participants to help them assess and identify resources to address barriers to cancer diagnostic or treatment care. Using a validated instrument, we assessed participants' satisfaction with their cancer diagnostic or treatment care up to 3 months after diagnostic resolution of a cancer-related abnormality or within 3 months of initiation of cancer treatment. RESULTS: Overall, patients reported high satisfaction with diagnostic care and cancer treatment. There were no statistically significant differences between PN and control groups in satisfaction with cancer-related care (p > 0.05). Hispanic and African American participants were less likely to report high satisfaction with cancer care when compared to White patients. Middle-aged participants with higher education, higher household income, private insurance, owning their own home, working full-time, and those whose primary language is English had higher satisfaction with cancer-related diagnostic care. CONCLUSIONS: PN had no statistically significant effect on patients' satisfaction with cancer-related care. Further research is needed to define the patient populations who might benefit from PN, content of PN that is most useful, and services that might enhance PN. TRIAL REGISTRATIONS: clinicaltrials.gov identifiers: NCT00613275 , NCT00496678 , NCT00375024 , NCT01569672.

Impact of patient navigation in eliminating economic disparities in cancer care.

BACKGROUND: Patient navigation may reduce cancer disparities associated with socioeconomic status (SES) and household factors. This study examined whether these factors were associated with delays in diagnostic resolution among patients with cancer screening abnormalities and whether patient navigation ameliorated these delays. METHODS: This study analyzed data from 5 of 10 centers of the National Cancer Institute's Patient Navigation Research Program, which collected SES and household data on employment, income, education, housing, marital status, and household composition. The primary outcome was the time to diagnostic resolution after a cancer screening abnormality. Separate adjusted Cox proportional hazard models were fit for each SES and household factor, and an interaction between that factor and the intervention status was included. RESULTS: Among the 3777 participants (1968 in the control arm and 1809 in the navigation intervention arm), 91% were women, and the mean age was 44 years; 43% were Hispanic, 28% were white, and 27% were African American. Within the control arm, the unemployed experienced a longer time to resolution than those employed full-time (hazard ratio [HR], 0.85; P = .02). Renters (HR, 0.81; P = .02) and those with other (ie, unstable) housing (HR, 0.60; P < .001) had delays in comparison with homeowners. Never married (HR, 0.70; P < .001) and previously married participants (HR, 0.85; P = .03) had a longer time to care than married participants. There were no differences in the time to diagnostic resolution with any of these variables within the navigation intervention arm. CONCLUSIONS: Delays in diagnostic resolution exist by employment, housing type, and marital status. Patient navigation eliminated these disparities in the study sample. These findings demonstrate the value of providing patient navigation to patients at high risk for delays in cancer care.

Barriers to health care contribute to delays in follow-up among women with abnormal cancer screening: Data from the Patient Navigation Research Program.

BACKGROUND: There is limited understanding of the association between barriers to care and clinical outcomes within patient navigation programs. METHODS: Secondary analyses of data from the intervention arms of the Patient Navigation Research Program were performed, which included navigated participants with abnormal breast and cervical cancer screening tests from 2007 to 2010. Independent variables were: 1) the number of unique barriers to care (0, 1, 2, or ≥3) documented during patient navigation encounters; and 2) the presence of socio-legal barriers originating from social policy (yes/no). The median time to diagnostic resolution of index screening abnormalities was estimated using Kaplan-Meier cumulative incidence curves. Multivariable Cox proportional hazards regression examined the impact of barriers on time to resolution, controlling for sociodemographics and stratifying by study center. RESULTS: Among 2600 breast screening participants, approximately 75% had barriers to care documented (25% had 1 barrier, 16% had 2 barriers, and 34% had ≥3 barriers). Among 1387 cervical screening participants, greater than one-half had barriers documented (31% had 1 barrier, 11% had 2 barriers, and 13% had ≥3 barriers). Among breast screening participants, the presence of barriers was associated with less timely resolution for any number of barriers compared with no barriers. Among cervical screening participants, only the presence of ≥2 barriers was found to be associated with less timely resolution. Both types of barriers, socio-legal and other barriers, were found to be associated with delay among breast and cervical screening participants. CONCLUSIONS: Navigated women with barriers resolved cancer screening abnormalities at a slower rate compared with navigated women with no barriers. Further innovations in navigation care are necessary to maximize the impact of patient navigation programs nationwide.

Costs and outcomes evaluation of patient navigation after abnormal cancer screening: evidence from the Patient Navigation Research Program.

BACKGROUND: Navigators can facilitate timely access to cancer services, but to the authors' knowledge there are little data available regarding their economic impact. METHODS: The authors conducted a cost-consequence analysis of navigation versus usual care among 10,521 individuals with abnormal breast, cervical, colorectal, or prostate cancer screening results who enrolled in the Patient Navigation Research Program study from January 1, 2006 to March 31, 2010. Navigation costs included diagnostic evaluation, patient and staff time, materials, and overhead. Consequences or outcomes were time to diagnostic resolution and probability of resolution. Differences in costs and outcomes were evaluated using multilevel, mixed-effects regression modeling adjusting for age, race/ethnicity, language, marital status, insurance status, cancer, and site clustering. RESULTS: The majority of individuals were members of a minority (70.7%) and uninsured or publically insured (72.7%). Diagnostic resolution was higher for navigation versus usual care at 180 days (56.2% vs 53.8%; P = .008) and 270 days (70.0% vs 68.2%; P < .001). Although there were no differences in the average number of days to resolution between the 2 groups (110 days vs 109 days; P = .63), the probability of ever having diagnostic resolution was higher for the navigation group versus the usual-care group (84.5% vs 79.6%; P < .001). The added cost of navigation versus usual care was $275 per patient (95% confidence interval, $260-$290; P < .001). There was no significant difference in stage distribution among the 12.4% of patients in the navigation group vs 11% of the usual-care patients diagnosed with cancer. CONCLUSIONS: Navigation adds costs and modestly increases the probability of diagnostic resolution among patients with abnormal screening test results. Navigation is only likely to be cost-effective if improved resolution translates into an earlier cancer stage at the time of diagnosis.

Impact of patient navigation on cancer diagnostic resolution among Northwest Tribal communities.

The patient navigator model has not been widely implemented in American Indian/Alaska Native (AI/AN) communities, but may be effective in improving cancer outcomes for this population. Subjects were enrolled from eight clinics at Tribes throughout the Northwest (n = 1,187). Four clinics received navigation. Time between abnormal finding and definitive diagnosis was recorded. We examined whether odds of obtaining definitive diagnosis by 60, 90, and 365 days differed between the two groups. The odds of definitive diagnosis within 365 days for navigated subjects was 3.6 times (95 % CI, 1.47, 8.88; p = 0.01) the odds for control subjects. The outcome at 60 and 90 days did not significantly differ between the two groups. Our findings indicate that patient navigation did not significantly impact chance of diagnosis by 60 or 90 days from abnormal finding. However, it did improve the chance of avoiding extreme delays in obtaining a definitive diagnosis.

Do better-rated navigators improve patient satisfaction with cancer-related care?

Patient navigation has emerged as a promising strategy for addressing racial-ethnic and socioeconomic disparities in cancer-related care. However, little is known about the impact of patients' perception of the quality of navigation on patient outcomes. We examined the impact of better-rated navigators on patients' satisfaction with cancer-related care. The sample included 1,593 adults (85.8% with abnormal cancer screening and 14.2% with confirmed cancer diagnosis) who received patient navigation. We defined better-rated navigators as those scoring above the first quartile of mean scores on the Patient Satisfaction with Interpersonal Relationship with Navigator scale. We defined patient satisfaction based on scores above or below the median of the Patient Satisfaction with Cancer-Related Care (PSCC) scale. We controlled for patient and site characteristics using backward selection logistic regression analyses. Among patients with abnormal screening, having a better-rated navigator was associated with higher score on the PSCC (p < 0.05). After controlling for other bivariate predictors of satisfaction (e.g., age, race, income, and household size), navigation by better-rated navigators was associated with a greater likelihood of having higher patient satisfaction [odds ratio (OR), 1.38; 95% confidence interval (CI), 1.05-1.82]. Similar findings between better-rated navigators and score on the PSCC were found for participants with diagnosed cancer (OR, 3.06; 95% CI, 1.56-6.0). Patients navigated by better-rated navigators reported higher satisfaction with their cancer-related care.

Analysis of combined data from heterogeneous study designs: an applied example from the patient navigation research program.

BACKGROUND: The Patient Navigation Research Program (PNRP) is a cooperative effort of nine research projects, with similar clinical criteria but with different study designs. To evaluate projects such as PNRP, it is desirable to perform a pooled analysis to increase power relative to the individual projects. There is no agreed-upon prospective methodology, however, for analyzing combined data arising from different study designs. Expert opinions were thus solicited from the members of the PNRP Design and Analysis Committee. PURPOSE: To review possible methodologies for analyzing combined data arising from heterogeneous study designs. METHODS: The Design and Analysis Committee critically reviewed the pros and cons of five potential methods for analyzing combined PNRP project data. The conclusions were based on simple consensus. The five approaches reviewed included the following: (1) analyzing and reporting each project separately, (2) combining data from all projects and performing an individual-level analysis, (3) pooling data from projects having similar study designs, (4) analyzing pooled data using a prospective meta-analytic technique, and (5) analyzing pooled data utilizing a novel simulated group-randomized design. RESULTS: Methodologies varied in their ability to incorporate data from all PNRP projects, to appropriately account for differing study designs, and to accommodate differing project sample sizes. LIMITATIONS: The conclusions reached were based on expert opinion and not derived from actual analyses performed. CONCLUSIONS: The ability to analyze pooled data arising from differing study designs may provide pertinent information to inform programmatic, budgetary, and policy perspectives. Multisite community-based research may not lend itself well to the more stringent explanatory and pragmatic standards of a randomized controlled trial design. Given our growing interest in community-based population research, the challenges inherent in the analysis of heterogeneous study design are likely to become more salient. Discussion of the analytic issues faced by the PNRP and the methodological approaches we considered may be of value to other prospective community-based research programs.

Indian Health Service Care System and Cancer Stage in American Indians and Alaska Natives.

PURPOSE: We aimed to determine whether the association between late-stage cancer and American Indian/Alaska Native (AI/AN) race differed by enrollment in the Indian Health Service Care System (IHSCS). METHODS: We used Surveillance, Epidemiology, and End Results (SEER) data linked to Medicare files to compare the odds of late-stage breast, colorectal, lung, or prostate cancer between non-Hispanic Whites (NHWs) (n=285,993) and AI/ANs with (n=581) and without (n=543) IHSCS enrollment. RESULTS: For AI/ANs without IHSCS enrollment, the odds of late-stage disease were higher in AI/ANs compared with NHWs for breast (OR=3.17, 95%CI: 1.82-5.53) and for prostate (OR=2.59, 95%CI:1.55-4.32) cancer, but not for colorectal or lung cancers. Among AI/ANs with IHSCS enrollment, there was not a significant association between late-stage disease and AI/AN race for any of the four cancers evaluated. CONCLUSION: Our results suggest that enrollment in the IHSCS reduced the disparity between AI/ANs and NHWs with respect to late-stage cancer diagnoses.

Stressful Life Events and Self-Reported Postpartum Depressive Symptoms 13-24 Months After Live Birth Among Non-Hispanic American Indian/Alaska Native Mothers in Oregon: Results from a Population-Based Survey.

OBJECTIVES: We explored the association between stressful life events and postpartum depressive symptoms among non-Hispanic American Indian and Alaska Native (AI/AN) mothers. METHODS: We analyzed self-reports of stressful life events and depressive symptoms from 298 AI/AN respondents and conducted logistic regression to examine their association. RESULTS: Of the AI/AN mothers who responded, 29.7% reported depressive symptoms during their second postpartum year. Partner-related and traumatic stressful life events were significantly associated with increased risk of postpartum depressive symptoms. CONCLUSIONS: AI/AN women should receive intensive screening for depression through the second postpartum year. Programs that address stressful life events may be part of a plan to decrease postpartum depression.

Cancer Treatment Delays in American Indians and Alaska Natives Enrolled in Medicare.

To assess whether timing of initial post-diagnosis cancer care differs between American Indian and Alaska Native (AI/AN) and non-Hispanic White (NHW) patients, we accessed SEER-Medicare data for breast, colorectal, lung, and prostate cancers (2001-2007). Medicare claims data were examined for initiation of cancer-directed treatment. Overall, AI/ANs experienced longer median times to starting treatment than NHWs (45 and 39 days, p < .001) and lower rates of treatment initiation (HR[95%CI]: 0.86[0.79-0.93]). Differences were largest for prostate (HR: 0.80[0.71-0.89]) and smallest for breast cancer (HR: 0.96[0.83-1.11]). American Indians / Alaska Natives also had elevated odds of greater than 10 weeks between diagnosis and treatment compared with NHWs (OR[95% CI]: 1.37[1.16-1.63]), especially for prostate cancer (OR: 1.41[1.14-1.76]). Adjustment for comorbidity and socio-demographic factors attenuated associations except for prostate cancer. In this insured population, we observed evidence that AI/ANs start cancer therapy later than NHWs. The modest magnitude of delays suggests that they are unlikely to be a determinant of survival disparities.

Cancer Stage in American Indians and Alaska Natives Enrolled in Medicaid.

INTRODUCTION: Nationally, a greater proportion of American Indians and Alaska Natives (AI/ANs) are diagnosed with advanced-stage cancers compared with non-Hispanic whites. The reasons for observed differences in stage at diagnosis between AI/ANs and non-Hispanic whites remain unclear. METHODS: Medicaid, Indian Health Service Care Systems, and state cancer registry data for California, Oregon, and Washington (2001-2008, analyzed in 2014-2015) were linked to identify AI/ANs and non-Hispanic whites diagnosed with invasive breast, cervical, colorectal, lung, or prostate cancer. Logistic regression was used to estimate ORs and 95% CIs for distant disease versus local or regional disease, in AI/ANs compared with non-Hispanic white case patients. RESULTS: A similar proportion of AI/AN (31.2%) and non-Hispanic white (35.5%) patients were diagnosed with distant-stage cancer in this population (AOR=1.03, 95% CI=0.88, 1.20). No significant differences in stage at diagnosis were found for any individual cancer site. Among AI/ANs, Indian Health Service Care Systems eligibility was not associated with stage at diagnosis. CONCLUSIONS: In contrast to the general population of the U.S., among Medicaid enrollees, AI/AN race is not associated with later stage at diagnosis. Cancer survival disparities associated with AI/AN race that have been observed in the broader population may be driven by factors associated with income and health insurance that are also associated with race, as income and insurance status are more homogenous within the Medicaid population than within the broader population.

Impact of Patient Navigation Interventions on Timely Diagnostic Follow Up for Abnormal Cervical Screening.

OBJECTIVE: As part of the Patient Navigation Research Program, we examined the effect of patient navigation versus usual care on timely diagnostic follow-up, defined as clinical management for women with cervical abnormalities within accepted time frames. METHODS: Participants from four Patient Navigation Research Program centers were divided into low- and high-risk abnormality groups and analyzed separately. Low-risk participants (n = 2088) were those who enrolled with an initial Pap test finding of atypical squamous cells of undetermined significance (ASCUS) with a positive high-risk human papillomavirus (HPV) serotype, atypical glandular cells, or low-grade squamous intraepithelial lesion (LGSIL). High-risk participants were those with an initial finding of high-grade squamous intraepithelial lesion (HGSIL) (n = 229). A dichotomous outcome of timely diagnostic follow-up within 180 days was used for the low-risk abnormality group and timely diagnostic follow-up within 60 days for the high-risk group, consistent with treatment guidelines. A logistic mixed-effects regression model was used to evaluate the intervention effect using a random effect for study arm within an institution. A backward selection process was used for multivariable model building, considering the impact of each predictor on the intervention effect. RESULTS: Low-risk women in the patient navigation arm showed an improvement in the odds of timely diagnostic follow-up across all racial groups, but statistically significant effects were only observed in non-English-speaking Hispanics (OR 5.88, 95% CI 2.81-12.29). No effect was observed among high-risk women. CONCLUSION: These results suggest that patient navigation can improve timely diagnostic follow-up among women with low-risk cervical abnormalities, particularly in non-English-speaking Hispanic women.

Disparities in life expectancy of pacific northwest American Indians and Alaska natives: analysis of linkage-corrected life tables.

OBJECTIVES: 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. METHODS: 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. RESULTS: 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. CONCLUSION: 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.