These papers sit alongside the Indian Health Financing Series rather than inside it. They are grouped below by subject: how specific financing mechanisms work, and how the American Community Survey shapes what is known about AI/AN health coverage.
Financing Mechanisms
The IHS-OMB Rate and FMAP: An Underappreciated Driver of Indian Health Program Medicaid Financing
Edward J. Fox, PhD — September 2026
This paper argues that the IHS-OMB encounter rate and the Federal Medical Assistance Percentage (FMAP) are two distinct financing levers — one sets what the provider is paid, the other sets who pays it — and that conflating them obscures why their combination, not either mechanism alone, changes the fiscal calculus a state faces when deciding whether to expand Medicaid-covered services through Indian Health Programs. Using the 2000–2026 Lower-48 outpatient rate history and the Urban Indian Organization experience under the COVID-era 100% FMAP extension as evidence, the paper works through the conceptual distinction in detail; the dollar magnitude of the subsidy for IHS/Tribal programs and the cost of closing the parallel UIO gap are treated separately in Paper III and Paper VII.
Companion table: IHS Medicaid Encounter Rate and Inflation, 2000–2026 (PDF, 2 pages). Annual Lower-48 outpatient rates excluding Medicare, dollar and percentage changes, and CPI-U all-items and medical-care inflation. Includes calculation notes and references. The rate rises from $172 in 2000 to $826 in 2026; full-year 2026 inflation is pending, and the 2025 CPI averages use 11 available months. Updated November 5, 2026.
Making Indian Health Financing Policy: Federal and State Rulemaking, Implementation, and Tribal Consensus Revised — October 2026
Edward J. Fox, PhD — September 2026
This paper argues that Indian health financing policy is not a single process but a set of distinct pathways, each with its own governmental actors and its own bottleneck — some resolved entirely through federal rulemaking (Medicare-like rates, the VA Federal Ceiling Price), some requiring state-by-state Medicaid implementation after federal action (the encounter rate, the nineteen-year “received through” dispute), some executed facility-by-facility (the VA-I/T/U reimbursement agreement), and one that has not yet succeeded at all (the 2020 effort to extend the encounter rate to Medicare outpatient payment). Drawing on a recovered 1998 Northwest Portland Area Indian Health Board study, it also shows that effective tribal-state consultation predates the 2009 federal consultation requirement by more than a decade, and argues that the most consequential step in any of these pathways — the work tribes do to reach a unified position before approaching a state or federal government — rarely appears in the documentary record at all. A section added in October 2026 treats compliance (OIG oversight, state billing rules, and the compliance officer’s place in a Tribal health program) as the obligation that determines whether a program keeps what those pathways provide.
IHS Budget FY2021–FY2025: Five-Year Analysis and Section 105(l) Research
Edward J. Fox, PhD — October 2026
This paper compares selected IHS budget categories over FY2021–FY2025, including Health Services with PRC/CHEF shown separately, Contract Support Costs, Facilities, and Section 105(l) Tribal leases. It examines changes in each category’s share of the total program-level budget, explains why COVID-19 funding is not separately analyzed, and discusses the distinction between Section 105(l) enacted estimates, operating-plan estimates, and later-reported actual costs. The paper identifies the FY2025 lease figures as a reconciliation question rather than assuming the difference alone proves a funding shortfall.
Read the paper → · Data tables · Excel tables
Companion analysis: IHS Operating Funding, FY2021–FY2025: A Parallel Analysis Excluding Facilities and Health IT — an AI-written working paper in the AI Sandbox.
Who Kept Pace? IHS Budget History, FY2020–FY2027 New — November 2026
Edward J. Fox, PhD — November 2026. Drafted with AI assistance (Claude, Anthropic); research design, data choices, interpretation and conclusions are the author’s.
This paper argues that the IHS accounts that buy care for patients did not keep pace with medical prices from FY 2021 to FY 2026, while the accounts the law requires IHS to pay in full grew fastest. Purchased/Referred Care, held at $996.8 million from FY 2023 through FY 2026, lost nearly 10 percent of its purchasing power, about $107 million in FY 2026 alone, and Health Services outside Electronic Health Record modernization has lost ground every year since FY 2023. Contract Support Costs and Section 105(l) leases, paid in full by statute and court order, account for most of the budget’s growth. A typology of IHS Areas by dependence on PRC shows the loss falls hardest where Tribes have no Indian hospital and where states have not expanded Medicaid.
Read the paper → · Graphics 18A–18B · Five-Year Analysis
Medicare, Medicaid, and Total CMS Investment in the AI/AN IHS-Access Population Revised — November 2026
Edward J. Fox, PhD — March 2026, revised November 2026. Drafted with AI assistance (Claude, Anthropic); research design, data choices, interpretation and conclusions are the author’s.
This paper estimates Medicare and Medicaid (CMS) spending on people who report access to IHS in the 2024 ACS 5-Year PUMS — 1,523,017 people of all races, of whom 1,294,264 are American Indian and Alaska Native alone or in combination — using 2024 National Health Expenditure rates. About half of those reporting IHS access have no CMS coverage; CMS spending on the rest is estimated at $9.2–12.5 billion a year, spent wherever they receive care rather than paid to IHS-funded programs. The paper also compares the ACS Medicaid count with the CMS/IHS Data Match, which found 941,168 AI/AN IHS registrants enrolled in Medicaid in 2023. The November 2026 revision corrects how the paper describes the Data Match, which counts enrollment only and contains no spending data, and clarifies that the ACS counts cover all races.
Data and the American Community Survey
How the American Community Survey Has Strengthened Tribal Health Finance
Edward J. Fox, PhD — September 2026
This essay argues that the American Community Survey (ACS) gave Tribal health programs something the decennial census structurally could not — current, recurring, small-area estimates of demographic composition, income, and insurance status — and that this shift has strengthened Tribal health finance across four distinct fronts: timelier data for funding formulas and needs assessments, a working tool for program planning and progress tracking, statistically reliable small-area estimates for historically undercounted Tribal populations, and a common evidentiary language with CMS, IHS, and state Medicaid agencies. Drawing on the 2009 Fox and Boerner report, its ongoing State Health Insurance Status Report, its Resolution 18-22 data-quality advocacy, and CRIHB’s parallel CMS-TTAG work, the essay traces how national and regional Tribal organizations have used the ACS both as an analytic tool and as a subject of advocacy in its own right — while noting the survey’s real limits, including small-sample margins of error and a self-identified race and ethnicity category that does not map cleanly onto Tribal enrollment or IHS eligibility.
The American Community Survey and Indian Country: What Is at Stake in the 2030 Census Debate?
Edward J. Fox, PhD — September 2026
This essay argues that the real stakes in the Census Bureau’s September 2026 proposal to eliminate race and ethnicity questions from the 2030 decennial short form are less about that form itself — which the proposal does not restrict from also being asked on the ACS — and more about the twenty-year statistical infrastructure that Indian Country, Indian health organizations, and researchers have built on top of the ACS since it replaced the Census long form in 2010. Tracing the ACS’s history, its distinct value for AI/AN populations (including health insurance data unavailable before 2008), and the accumulated institutional knowledge required to interpret two decades of changing race and ethnicity definitions, the essay argues that continuity and transparency — not any single question on any single form — are what the current Census debate actually puts at risk for Indian Country.
NCAI Resolution PSC-26-073 and the American Community Survey: Why More Analysis and Consultation Are Needed New — November 2026
Edward J. Fox, PhD — November 2026. Drafted with AI assistance (Claude, Anthropic); research design, data choices, interpretation and conclusions are the author’s.
This brief commends NCAI and the drafters of Resolution PSC-26-073 for calling attention to the Census Bureau’s proposed 2030 changes, and supports the resolution’s call for more consultation and a Tribal-specific impact analysis. It argues that the case is stronger than the resolution makes it: the benefits of ACS estimates depend on careful identification of AI/AN people, longitudinal comparison depends on consistency, and the strengths and weaknesses of the current ACS, its recent changes, and the proposed changes have not yet been weighed for AI/AN people and Indian Tribes.
Read the brief → · NCAI Resolution PSC-26-073 (NCAI) · NCAI Census consultation resources
Who Was Added? Hispanic Origin, Nativity, and IHS Coverage in the 2019–2021 AI/AN Increase New — October 2026
Edward J. Fox, PhD — October 2026
This paper argues that the 55 percent jump in the AI/AN population count between the 2019 and 2021 American Community Surveys is a change in who answered the race question as AI/AN, not a change in the population Tribal health programs serve. The entire increase fell among people reporting no IHS coverage; more than half came from Hispanic respondents, led by people of Mexican and Central American origin, consistent with the 2020 question’s new examples of Latin American Indigenous groups; and most of the added respondents were born in the United States. The paper is careful about what these patterns do not mean: being Hispanic and being AI/AN are not exclusive, and birth outside the United States does not rule out IHS eligibility. Its practical point is about denominators — after 2020, IHS-related financing measures must be anchored to the IHS-connected population, not the AI/AN count alone.
Read the paper → · Data tables
The 2020 Race Question by State: AI/AN Counts and IHS Coverage, 2019–2024 New — October 2026
Edward J. Fox, PhD — October 2026
This companion paper argues that the 2020 race question change raised AI/AN counts least where the IHS-connected population is largest, and most where it is smallest. Across the 39 states with more than 1,500 AI/AN people reporting IHS coverage, the count rose 7 percent between 2019 and 2021 in states where half or more of AI/AN residents reported IHS coverage, 33 percent where a quarter to a half did, and 80 percent where fewer than a quarter did — and the new level held through 2024. For state-level Indian health financing, the AI/AN count now reliably describes the IHS-connected population only in the highest-IHS states; everywhere else, IHS-related measures should be anchored to that population directly.
Read the paper → · Data tables
Who Was Added, by Income: The 2020 Race Question and the AI/AN Income Profile, 2019–2024 New — October 2026
Edward J. Fox, PhD — October 2026
This third companion paper argues that the population added to the AI/AN count after the 2020 race question change is not only less connected to the Indian Health Service but also higher-income than the AI/AN population it joined. Of the roughly 3.57 million AI/AN people without IHS coverage added between 2019 and 2024, only 18 percent had incomes within the Medicaid expansion limit, while the income profile of AI/AN people reporting IHS coverage barely moved. As a result, AI/AN-wide income and eligibility measures now look better than they are for the people Indian health programs serve — the share within the Medicaid expansion limit fell from 28.6 to 24.0 percent across all AI/AN people, but only from 33.5 to 31.9 percent among the IHS-connected population.
Read the paper → · Data tables
Who Medicaid Could Reach: Income Relative to Poverty Among American Indians and Alaska Natives Reporting IHS Coverage, 2020–2024 New — October 2026
Edward J. Fox, PhD — October 2026
This analysis argues that the American Indians and Alaska Natives most connected to the Indian Health Service are also the ones whose incomes most often fall within reach of Medicaid, which makes Medicaid expansion and the 100 percent federal match for services delivered through IHS and Tribal programs more consequential for this population than for any comparison group. Among AI/AN people reporting IHS coverage in the 2020–2024 ACS, 34 percent have incomes at or below 138 percent of poverty, 45 percent fall in the Marketplace premium tax credit range, and 21 percent are above 400 percent — compared with 18 percent and 42 percent at the two ends for non-AI/AN people. Nearly four in five IHS-connected AI/AN people are within reach of Medicaid or the Marketplace, so public and subsidized coverage are the core of their financing, not a supplement.
Read the paper → · Data tables
Who Can Be Billed, and Who Could Be Enrolled: Medicaid and Medicare among American Indian and Alaska Native People with Access to IHS Draft — November 2026
Edward J. Fox, PhD — November 2026. Drafted with assistance from Claude (Anthropic); questions, analysis choices and conclusions are the author’s.
This paper argues that about half of American Indian and Alaska Native people reporting access to IHS have a public payer an IHS-funded program can bill, and shows where the rest are. In 2024, 47 percent had Medicaid, Medicare or both, up from 42 percent in 2019, with wide differences by state. About 167,000 people reporting access to IHS have incomes under 139 percent of poverty and no Medicaid, down from about 223,000 in 2015–2019, and 64 percent of them live in Oklahoma, Arizona, New Mexico and South Dakota. Comparing 2015–2019 with 2020–2024, Medicaid coverage rose in every group of states whenever they expanded, so the effect of the late expansions cannot yet be separated from the continuous-enrollment years; the paper sets out how to repeat the comparison with the 2024–2028 ACS release.
Read the paper → · Companion: What Medicaid Data Cannot Yet Tell · Who Medicaid Could Reach · Also on the AI Sandbox
What Medicaid Data Cannot Yet Tell Indian Health Programs: Access to IHS, the CMS–IHS Medicaid Data Match, and a Proposal for the Next Match Draft — November 2026
Edward J. Fox, PhD — November 2026. Drafted with assistance from Claude (Anthropic); questions, analysis choices and conclusions are the author’s.
This paper argues that published data cannot tell Tribal leaders who receives care at an IHS-funded program while enrolled in Medicaid, or how much Medicaid pays those programs. The number of American Indian and Alaska Native people reporting access to IHS fell 8 percent between 2015–2019 and 2020–2024; the 2020 race question change does not explain the drop, it came entirely in the lower income bands, and the paper concludes that we don’t know why. It shows that matched Medicaid enrollment among IHS registrants rose 12 percent from 2019 to 2023, largely during continuous enrollment, and proposes how the next CMS–IHS Medicaid Data Match could follow patients from enrollment to visits to payment, using the IHS workload definition. It weighs the risk that a national Medicaid payment total could be used against appropriations, and leaves to Tribal leaders whether the proposed changes are worth their effort and risks.
Read the paper → · Who Medicaid Could Reach · Also on the AI Sandbox
Facilities and Capacity
The IHS Facilities List, June 2023: What the Official Count Shows New — October 2026
Edward J. Fox, PhD — October 2026
This paper argues that the IHS facilities list counts places, not capacity, and that growth in the count should not be read as growth in access. The June 2023 list, the most recent IHS has released, names 1,008 sites: Tribes operate 792 of the 932 IHS and Tribal sites, only 695 are the five standard facility types, and only 54 percent report patient workload to IHS. Matched site by site against the 2019 list, the 22 percent growth since then is about 248 entries added and 65 removed, with about 119 continuing sites relabeled — much of it existing behavioral health, substance abuse and dental programs listed for the first time. The paper supersedes the facility estimates in Paper IV-D.
Also Available Elsewhere on This Site
IHCIA Reauthorization: History and Participants →
Two essays on how the Indian Health Care Improvement Act reauthorization was built, 1999–2010: Who Built the Indian Health Care Improvement Act? (a discussion draft, with a documented roster of participants) and Building Consensus: NPAIHB’s Role in the IHCIA Reauthorization.
Hank Adams and the Policy Process →
How Hank Adams worked every stage of the policy process, from problem definition to evaluation, traced in his own testimony, the Twenty Points and the Policy Review Commission record, with lessons for implementation today.
Turning Tribal Health Clinic Data into Management Information →
Now on the Health Information Systems page of Managing a Tribal Health Program, alongside the practical guidance it supports.
Data Tables →
American Community Survey tabulations behind these papers, each with key figures and a downloadable spreadsheet.
Looking for AI-written papers? The AI Sandbox holds papers produced mostly by AI tools on Indian health finance questions, with my review notes where I have added them. They are not my work and are kept separate from the papers on this page.
Hank Adams: Related Papers and Graphics →
Explore the policy-cycle and leadership graphics, related papers, case studies, and source records together.