Los Angeles American Indian and Alaska Native Project ^[1]
Technical Memo 4:
AIAN Health Insurance Coverage

Jonathan Ong and Paul Ong

Los Angeles  ani, 2011; Decker, 2012). Even with the public programs, approximately one in six Americans is uninsured.

Health insurance coverage is particularly important for AIANs because they have relatively more medical problems. Other people have noted this in terms of morbidity and mortality as well (Jones, 2006; Barnes, Adams, and Powell-Griner, 2010; Kaiser Commission on Medicaid and the Uninsured, 2000; UCLA Center for Health Disparity Research, 2012; Belluck, 2009; The Henry J. Kaiser Family Foundation, 2009). This can be seen in the ACS PUMS data for Los Angeles (see table 1). AIANs are more than one and a half times as likely to have a disability[2] than the total population. The bottom of the table reports disability rates by age categories. Not surprising, the disability rate varies significantly with age, with the rate climbing in each age bracket, in part because some disabilities are only counted for older age groups, but largely because of the increases in chronic disabilities as people age. Overall and within each category, AIANs experience significantly higher disability rates than non-Hispanic whites (NHW) and the total population.

Table 1: Percent Disabled by Age
	Total Population	AIAN Alone	Multiracial AIAN	NHW
Total	9.8%	15.3%	15.9%	13.0%
0–17	2.8%	7.0%	5.5%	2.3%
18–39	3.8%	9.0%	10.7%	3.8%
40–64	10.9%	17.9%	22.8%	11.3%
65+	40.8%	49.9%	48.1%	40.4%

 

Despite the greater health care needs of AIANs, they have less access to health care because of higher rates of being uninsured and less access to private insurance. Nearly one in four AIANs alone is uninsured compared to less than one in eight NHWs.

The next section covers how health insurance coverage varies by key demographic, economic, and health characteristics. Part III compares coverage by private insurance. Part IV examines coverage for AIANs compared to other groups when these factors are controlled for, and Part V examines usage of IHS. The conclusion contains recommendations for future research and comments on policy implications.

Part II: Uninsurance Rates

Health care coverage varies by race, as well as by other characteristics such as age, gender, income level, and disability status. There are various types and sources of health coverage, which can be categorized into two broad categories, government-run public health care or insurance from a private health insurer. While public health care extends coverage to those who might not otherwise have health insurance, such as the poor or elderly, private health insurance tends to provide better health coverage. Even including public health care, more than one in five people in Los Angeles have no health insurance or coverage.

AIANs are more likely to be uninsured than NHWs, less likely to have private coverage than NHWs, and more likely to have increased reliance on only public forms of health coverage. AIANs alone are more likely to be uninsured and less likely to have private coverage (either private only or private and public) than the total population; they had increased reliance on public-only insurance when compared to the total population. Multiracial AIANs had lower levels of uninsured compared to the total population, but also lower levels of insurance in each category than NHWs (see table 2).

Table 2: Type of Health Coverage
	Total Population	AIAN Alone	Multi-racial AIAN	NHW
Uninsured	22.8%	24.3%	18.4%	11.6%
Private and Public	6.1%	7.1%	7.2%	11.5%
Private Only	47.8%	40.1%	48.9%	62.2%
Public Only	23.3%	28.5%	25.6%	14.7%

 

The percentage of uninsured tends to be low for youths who are primarily covered by their parents or other sources of health care. However, as they leave the age bracket, they often lose health insurance from these sources. Over time they are more likely to obtain a job with health care benefits, and the elderly have access to Medicare. Within each age group, multiracial AIANs tend to be better insured than the total population, but are not as well covered as NHWs. AIANs alone are more comparable to the total population.

There are gender differences. Women tend to be better insured than men, but AIAN-alone men are more likely to be uninsured than other men and AIAN women were more likely to be insured than other women, although both genders were not as insured as NHWs of either gender. Multiracial AIANs of both genders were better off, but still not as insured as NHWs.

People with low incomes relative to the federal poverty level tend either not to have jobs with health coverage benefits or not to be able to purchase it. This is partially offset by programs such as Medicaid for people with low income and Medicare for the elderly. AIANs alone are less insured than the total population in all income brackets except the lowest, and fare worse than NHWs at all levels. AIANs in combination are between the levels for the total population and NHWs except at the highest bracket.

Insurance companies are often prohibitive when accepting people with preexisting conditions, meaning that at the time this data was collected, disabled people were less likely to be covered. One in four AIANs alone with a disability did not have coverage, compared to one in eight for NHWs. AIANs in combination fared better, with one in five with a disability having no coverage, which was better than the total population, but not near the level of NHWs (see table 3).

Table 3: Percent Uninsured
	Total Population	AIAN Alone	Multi-racial AIAN	NHW
Uninsured	23%	24%	18%	12%
Percent Uninsured by Age
0–17	10%	8%	8%	5%
18–39	36%	35%	30%	20%
40–64	26%	29%	20%	13%
65+	3%	2%	2%	1%
Percent Uninsured by Gender
Male	25%	29%	21%	14%
Female	20%	19%	16%	10%
Percent Uninsured by Income-to-Poverty Ratio
Less than 125% of Poverty	32%	28%	24%	22%
125–249%	32%	36%	27%	21%
250–499%	20%	23%	16%	13%
Over 500%	7%	9%	8%	5%
Percent Uninsured by Disability Status
With a Disability	24%	25%	20%	12%
Without a Disability	12%	21%	10%	7%

 

The type of coverage affects health care access, with private coverage being the most desirable. Medicaid is less accepted than private insurance. Medicare is mixed, less accepted than private for primary care, but more accepted for specialized care (Bishop, Federman, and Keyhani, 2011). Differences are likely due to different reimbursement rates. There is a form of private insurance that is less accepted, capitated reimbursement (Decker, 2012). The reimbursement rates for a medical procedure vary with the type of insurance. For example, Medicaid (MediCal in California) offers a lower reimbursement amount than private insurance for the same treatment. Table 4 reports the percent covered by private insurance. AIANs alone have substantially lower rates of private health insurance than the general population and especially NHWs. AIANs in combination fare only slightly better by this metric than the overall population, but still do not come near the levels of NHWs. While almost three out of four NHWs have some private coverage, the figure is much lower for AIANs, around one-half.

 

Part III: Private Coverage

 

Private insurance is usually provided by an employer or union as part of a benefits package or is purchased as an individual. There is a large drop in the insurance rates for the elderly, since most of them are out of the labor force and rely on Medicare, which is public health coverage. Minority youth who are not NHW have low rates of private coverage, most likely because their parents do not have access to employer-based health coverage (and people with Medicaid are not included). The pattern of AIANs alone being worse off than the rest of the population and NHWs remains constant, as does the pattern of AIANs in combination being mostly between the levels of the rest of the population and NHWs.

 

The gender gap is small for most groups, with one exception, but there remains a sizable difference between AIAN-alone men and women. AIANs alone still tend to be worse off than the rest of the population and AIANs in combination still tend to be worse off than NHWs.

 

As income relative to the federal poverty level increases, so does the level of private coverage, but NHWs have far higher levels of private coverage at every income bracket, AIANs in combination are similar to the rest of the population, and AIANs alone are worse off than the rest of the population.

 

Coverage for people with a disability also follows the same pattern: AIANs alone are more disadvantaged than the rest of the population and AIANs in combination are between the total population and NHWs.

 

Table 4: Percent without Private Coverage
	Total Population	AIAN Alone		Multi-racial AIAN		NHW
Without Private Coverage	46%	53%		44%		26%
Percent without Private Coverage by Age
0–17	51%	64%		46%		19%
18–39	47%	51%		44%		25%
40–64	38%	45%		40%		22%
65+	57%	66%		52%		43%
Percent Without Private Coverage by Gender
Male	46%	55%		44%		27%
Female	46%	50%		44%		26%
Percent Without Private Coverage by Income-to-Poverty Ratio
Less than 125% of Poverty	80%	82%	79%		61%
125–249%	60%	69%	60%		48%
250–499%	33%	37%	26%		23%
Over 500%	13%	16%	13%		10%
Percent Without Private Coverage by Disability Status
With a Disability	65%	68%	59%		54%
Without a Disability	44%	50%	41%		22%

 

Part IV: Residual AIAN Effect beyond Observable Factors

The analysis in the previous section shows that health insurance rates vary significantly by age, gender, poverty status, and disability. These factors help explain the low coverage for AIANs. For example, because AIANs are more likely to be poor, they are more likely to have less access to private insurance. While the above analysis is useful, it does not tell us whether the observed factors working together explain the entire gap between AIANs and others, particularly the gap relative to NHWs. This section summarizes the results of a multivariate analysis that simultaneously accounts for the observed demographic, economic, and health characteristics. Details of the model are in Appendix A. Table 5 reports the unadjusted and adjusted gap between AIANs and non-AIANS, and between AIANs to NHWs.

Multiracial AIANs are less likely to have no insurance and less likely to have private coverage when compared to non-AIANs, but not when compared to NHWs and an especially large difference when it comes to private coverage. The difference is even greater for AIANs alone who are worse off than non-AIANs and NHWs. Although adjusting reduces the differences in most cases, there is still a significant difference across racial lines especially when compared to NHWs. When adjusted for several variables, AIAN-alone insurance coverage is on par with the rest of the population; they still have less private coverage and maintain large disparities with NHWs.

Table 5: Estimated Difference in Insurance Status Between AIANs and NH Whites
	AIAN Alone minus	Multiracial AIAN minus	AIAN Alone minus	Multiracial AIAN minus
	non-AIAN	non-AIAN	NHW	NHW
Uninsured
Unadjusted	1.4%	-4.5%	12.6%	6.8%
Adjusted	0.0%	-3.8%	8.3%	4.3%
No Private Insurance
Unadjusted	6.7%	-2.1%	26.4%	17.6%
Adjusted	5.4%	-3.3%	21.7%	14.0%

 

Part V: Indian Health Services

AIANs are unique because they potentially have access to Indian Health Services (IHS). This program is the result of treaties, laws, executive orders, and Supreme Court rulings resulting in agreements between the United States government and federally recognized tribes to provide essential services for the health of AIANs. IHS operates under a government-to-government relationship established in 1787 and is based on Article I, Section 8 of the US Constitution. It is federally funded and operates off a $4.3 billion annual budget as of 2011, but it is not considered an entitlement program.

IHS covers AIANs and partially extends to non-AIAN members of their households, either providing direct service through IHS facilities or select non-IHS facilities through Contract Health Services (CHS). However, the requirements for CHS are stricter, CHS facilities are situated near tribal lands, and the number of IHS facilities is limited, particularly in urban areas.

Despite being a checkbox in the ACS's health coverage question, IHS is tabulated as neither public nor private health insurance or coverage. People who only have access to IHS but no other form of insurance or coverage are counted as being uninsured. In Los Angeles, AIANs make up 41% of people with IHS. The rest consists of people of other races, including nearly one-fifth that is NHW. However, even among AIANs, IHS usage in Los Angeles County is rare. Less than 5% of AIANs alone and less than 1% of multiracial AIANs use it. This is extraordinarily low compared with the national levels: 40% of AIANs alone and 10% of multiracial AIANs are covered.[3]

Part V: Conclusion and Recommendations

The analysis shows that AIANs have greater health care needs but less access because of higher rates of being uninsured and lower odds of having private coverage. AIANs alone tend to be worse off than the total population, and multiracial AIANs tend to be worse off than NHWs. Demographic, socioeconomic, and disability factors contribute to the disparity in insurance rates, but even after accounting for these factors, AIANs have lower levels of health coverage than NHWs.

The status of health care coverage will change dramatically in the coming years with the restructuring of health care, making new research in the future vital to our understanding, depending on how things play out under healthcare reform. This includes changes to health care both on a federal level and its implementation at a local one.

Part of the Affordable Care Act (aka Obamacare) calls for a mandate on individual health insurance requiring it for every person in Public Law 111-148. This law was passed, and despite legal challenges to the individual mandate, it was upheld by the Supreme Court. Consequently, in the near future people will have to find health coverage. Because AIANs have low insurance rates, mandatory health insurance raises the question of how people will afford insuring themselves and their families. Although some AIANs may be exempt, it is not clear how it will affect the AIAN population in Los Angeles.

Another source of potential dramatic change is the "fiscal cliff." It comes from the inability of the White House and Congress to pass a budget to address the deficit and national debt. This resulted in a temporary agreement to extend Bush tax cuts until the end of 2012, and if a budget could not be passed, beginning in 2013, the tax cuts would expire and there would be a series of automatic cuts to government spending, including entitlement programs such as Medicare and Medicaid. However, even if a budget is passed, in order to reduce national spending, some cuts will likely be made to the same entitlement programs. Either way it is likely that Medicare and Medicaid will see some restructuring and budget cuts. Because of AIANs' increased reliance on public health care of some sort, changes to the extent of coverage could have disproportionately large effects on them.

The findings also raise many questions requiring further and more detailed research. This includes the observed gender disparity for AIANs alone in private coverage, the low health coverage for working-age AIANs alone, and low numbers enrolled in IHS due to lack of funding or other barriers. While the census shows that AIANs are more likely to be disabled, more analysis with other sources is needed to expand knowledge and details of the nature, magnitude, and causes of the health problems facing AIANs and future policy implications.

References

Barnes, M., Patricia F. Adams, and Eve Powell-Griner. "Health Characteristics of the American Indian or Alaska Native Adult Population: United States, 2004–2008." National Health Statistics Reports 20. March 9, 2010.

Belluck, Pam. "New Hopes on Health Care for American Indians." The New York Times. Dec. 2 2009: A1. The New York Times. Dec. 1, 2009. http://www.nytimes.com/2009/12/02/health/02indian.html?pagewanted=all.

Bishop, Tara F., Alex D. Federman, and Salomeh Keyhani. "Declines in Physician Acceptance of Medicare and Private Coverage." Archives of Internal Medicine 171:12 (2011): 1117–1119.

Decker, Sandra L. "In 2011 Nearly One-Third of Physicians Said They Would Not Accept New Medicaid Patients, But Rising Fees May Help." Health Affairs 31:8 (2011): 1673–1679.

Kaiser Commission on Medicaid and the Uninsured. "Health Insurance Coverage and Access to Care among American Indians and Alaska Natives." June 2000. http://kaiserfamilyfoundation.files.wordpress.com/health-insurance-coverage-and-access-to-care-among-american-indians-and-alaska-natives.pdf.

Henry J. Kaiser Family Foundation. "American Indians and Alaska Natives: Health Coverage and Access to Care." February 2004. http://kff.org/disparities-policy/fact-sheet/american-indians-and-alaska-natives-health-coverage/.

Johnson, Carrie L., Daniel L. Dickerson, Delight E. Satter, and Steven P. Wallace. "American Indians and Behavioral Health Issues in California: Implications for Culturally Appropriate Treatment." UCLA Center for Health Policy Research: Health Disparities. March 2012. http://healthpolicy.ucla.edu/publications/Documents/PDF/AIbehavioralhealthmar2012.pdf.

Jones, David S. "The persistence of American Indian Health Disparities." American Journal of Public Health, 96:12 (December 2006): 2122–2134.

Smith, Lauren M., and Delight E. Satter. " Health Care Reform: A focus on American Indians and Alaska Natives (AIAN) in California." UCLA Center for Health Policy Research: Health Disparities. April 2012. 1–2. http://healthpolicy.ucla.edu/publications/Documents/
PDF/HCRAIANapr2012.pdf.

Urban Indian Health Institute. "Affordability of Healthcare for Urban American Indians and Alaska Natives." November 2012. http://www.uihi.org/wp-content/uploads/2012/11/Fact-sheet_NHIS_Affordability-of-health-care.pdf.

 

We would like to thank our sponsors, The California Wellness Foundation, Los Angeles County Board of Supervisor Don Knabe, and the UCLA Center for the Study of Inequality for their generous  support. We would also like to thank the authors, Paul Ong and  Jonathan Ong, as well as the American Indian Studies Center for supporting this project.

 

Appendix A

For this memo, logistic regressions are used to control for the independent effects of observed factors. We examine two outcomes, being uninsured and not having private coverage. The logistic functions are defined as:

Probability (Being Uninsured) = e^bX/(1+e^bX)

Where Being Uninsured ⊂ (1,0)

 

Probability (No Private Coverage) = e^bX/(1+e^bX)

Where No Private Coverage ⊂ (1,0)

 

X is the vector of independent variables, and b is a vector of coefficients. Maximum likelihood is used to estimate the parameters. The following is a list of the variables and their functional forms. Sex is designated by a dichotomous variable for being male (1=yes, 0=no), and having at least one disability is designated by another dichotomous variable. We include both a continuous linear and a second-order term (squared) for age and the income-to-poverty ratio because their effects are not linear, as observed in Part II. There is a dichotomous variable indicating when the poverty ratio is not reported by the Bureau of the Census, and another for those in households with a capped top value of 5.01 times the federal poverty level. We include dummy variables to capture any residual effects of being AIAN alone or being AIAN in combination. One set of regressions compares AIANs with non-AIANS, and another set compares AIANs to non-Hispanic whites. Table A1 Reports the logit regression results.

 

Table A1: Logit Results Dependent Variable: Without Insurance Coverage
	Model 1		Model 2		Model 3		Model 4
	Without Insurance				Without Private Insurance
Relative to	non-AIAN		NHW		non-AIAN		NHW
Intercept	-2.819	***	-3.0502	***	1.9466	***	0.2079	*
Age	0.1578	***	0.1498	***	-0.0112	***	0.00665	*
Age Squared /100	-0.2056	***	-0.2042	***	0.0188	***	0.00367
Male	0.3351	***	0.4192	***	0.1483	***	0.2365	***
Poverty Ratio	-0.024		-0.1358		-0.9208	***	-0.4719	***
Poverty Ratio Squared	-0.078	***	-0.0488	***	0.0362	***	-0.0245
Top Poverty Ratio	-0.3683	***	-0.4898	***	-0.3232	***	-0.1458
Missing Poverty Ratio	-1.05	***	-1.348	***	-1.8344	***	-1.2625	***
With a Disability	-0.7118	***	-0.4897	***	0.6275	***	0.7882	***
AIAN Alone	-0.00028		0.47	***	0.2189		0.8716	***
AIAN in Combination	-0.2142		0.2418		-0.1311		0.5624	***
Likelihood Ratio	18351.32		3,756		30,774		7,052
Sample Size	289490		90229		289490		90229
*p<.01, ** p<.001, *** p<.0001
Dependent Variables: Without Insurance (models 1 & 2); Without Private Insurance (models 3 & 4)

 

 

Relative to non-AIANs (models 1 & 3); Relative to NH Whites (models 2 & 4)

 

The primary results are the gap in coverage after controlling for the observed factors. These adjusted differences in the probability of not being covered (DPr) are calculated by using the following equation:

DPr=B(p(1-p))*Dx

B is the estimated coefficient for the variable of interest (i.e., being AIAN), p is the observed probability of not being covered, and Dx is the difference in the independent variable, which by definition is equal to one.

 

Appendix B